overview of a part of maasvlakte i, port of rotterdam

Cover photograph:

OverviewofapartofMaasvlakteI,PortofRotterdam

Source:http://www.skyscrapercity.com/showthread.php?t=164137&page=11

(accessed27/6/2010)

An analysis of vessel behaviour based on AIS data

Application of AIS data in a nautical traffic model

Document: Finalreport

Placeanddate: Delft,June28th2010

Author: ThijsdeBoer

Email: [email protected]

University: DelftUniversityofTechnology

Faculty: FacultyofCivilEngineering&Geosciences

Department: HydraulicEngineering

Graduationcommittee:

Prof.ir.H.Ligteringen(graduationcommitteechair) Professor Ports & Waterways, Delft University of Technology

Dr.ir.W.Daamen Assistant professor Transport & Planning, Delft University of Technology

Ir.R.W.P.Seignette Program manager, Port Planning & Development, Port of Rotterdam

Ir.C.VanderTak Senior Project Manager, Marin’s Nautical Centre MSCN

Ir.Y.Koldenhof Project Manager, Marin’s Nautical Centre MSCN


Page -I-

Preface

ThismasterthesisisthelastpieceofworkinmymastereducationinHydraulicEngineeringattheDelftUniversityofTechnology.ThelargestpartoftheresearchhasbeencarriedoutinDelftandWageningen,althoughIhavehadseveralthesis-relatedmeetingsatotherlocationsintheNetherlands.

InthereportacasestudyofananalysisofAIS(AutomaticIdentificationSystem)isgiven.Bydoingthisanalysis,moreinsightisobtainedintothepaththatvesselstakeandtheaccompanyingvesselspeed,inportareas.Theresultsoftheanalysisaremadegeneric,tomakeitpossibletoimplementtheminmaritimemodels.

Iwouldliketothankthemembersofmygraduationcommittee,Prof.ir.H.Ligteringen,Dr.ir.W.DaamenfromtheDelftUniversityofTechnology,Ir.R.W.P.SeignettefromthePortofRotterdamandIr.C.VanderTakandIr.Y.KoldenhoffromMarinfortheirsupportandfeedbackgivenduringthetimespanofmythesis.

Furthermoremygratitudegoestofollowingpeoplethathelpedmewithvariouspartsofmyresearch.ErnstBoltfromRijkswaterstaat,forprovidinginformationandinsightinthemaritimemodelsthatexistnowadays.BenvanScherpenzeelfromthePortofRotterdam,forextendingmyknowledgeinthepracticalsideofthestory.DannydeRooandCorvanderScheldefromthePortofRotterdamforprovidingtheportmapandcurrentdata.

IwouldalsoliketothankErwinvanIperenfromMarin,forhisvaluable‘onthejob’supportandfeedback.Nexttohim,IwouldliketogiveabigthankstoallmycolleaguesatMarin,whogavemeaveryenjoyabletimeinWageningen.And,lastbutnoleast,mygirlfriendandfamilyfortheirsupportduringtheexecutionofmythesis!

ThijsdeBoer Delft,June2010

Page -II-

SummaryFromDecember2004onwardseveryseagoingvesselover300GrossTonnage(GT)isobligedtobeequipedwithanAutomaticIdentificationSystem(AIS).NowadaysalsoinlandvesselsareincreasinglyusingAIS.ThemainfunctionsofAISarecollisionavoidanceandanaidtonavigation.Alsocoastalauthori-ties(security)andVesselTrafficServices(trafficmanagement)useAIS.Thesystemisvaluableforsearchandrescueactionsandinmaritimemodellingaswell.

ThequalityofAISmessageshasbeentopicofseveralresearches.AnAISmessagecanbedividedintothreetypesofdata:static,voyagerelatedanddynamic.MosterrorsarefoundinthedescriptionofDes-tination,Estimatedtimeofarrival,Draught,VesselTypeandNavigationalStatus.Exceptforvesseltype,thesedataarevoyagerelated.Thistypeofdatahastobechangedmanually,whichisasourceoferrors.Thestaticdataareaddedduringinstallationofthesystemanddonotchangehereafterandarethuslesspronetoerrors.Thedynamicdatadependonthevessel’snavigationalinstrumentsandarequitereliable.

MaritimemodelsuseAISdatamainlytodeterminethetrafficinput.AISdataalsoimprovetheinsightintothenauticalnetworksthathavetobemodelled.Inportareas,AISdataisnotoftenusedforthesepur-poses,asintheseareasthetrafficimageisdisturbedbyvesselsthatarenotAISequipped.AISdatacanpotentiallybeusedtoinvestigateindividualvesselbehaviour,butnoextensiveuseismadeofthisyet.

Roughlytwotypesofmaritimemodelsexist.Onetypesimulatestheoverallnauticaltrafficandtheotherusesindividualvessels.Aproblemforthemodelsthatsimulatevesselbehaviouristhesocalledhumanfactor.MostmodelstrytosimulatethisbehaviourusingFuzzy-technologyorBayesiannetworks.

AcasestudyisperformedtoseeifananalysisofAISdatacandescribevesselbehaviourinthePortofRotterdamarea.Ascasearea,thepathbetweentheNorthSeaandtheAmazonehaven(MaasvlakteI)isused.Thevesselpathandspeed,aswellastheinfluenceofvesselsize,wind,currentandvisibilityisdetermined.Theinfluenceofthevesselsizeistakenintoaccount,bycreatingfivedifferentclasses(<10,000;10,000-40,000;40,000-70,000;70,000-100,000;>100,00dwt).

Therearesignificantdiferencesbetweenthesizeclasses,aswellforthevesselpathasthevesselspeed.Ingeneral,largervesselssailmoretothemiddleofthechannelandsailslower.Theyalsohaveamorenarrowdistributionoverthewaterway.Thevesselpositionandthevesselspeedarenormallydistributedoverthewaterway.Thereisnosignificantrelationshipfoundbetweenthelocationinthecrosssectionandthevesselspeed.

Therearesomeexceptionstothegeneralconclusionsdescribedinthepreviousparagraph.Vesselsofthesizeclass70,000-100,000dwtsailsignificantlyslowerthanvesselsofthelargestsizeclass.Thismightbecausedbythefactthatthelargestvesselsusemoretugsandthereforehavealargermanoeuvrabilityintheportarea.Thismakesitpossibleforthemtomaintainahigherspeed.

IncomingvesselssailbackwardsorforwardsintotheAmazonehaven,dependingonhowtheyareloaded.ThiscausesroughlytwodifferentvesselpathsintheBeerkanaal,becauseinbothcasesthevesselswanttotakethewidestbend,asthisisamoreeasymanoeuvre.Vesselsthatleavetheportclearlyshowsomedeviationtowardsthenorthorsouth.Thisindicatesthattheyalreadyadapttheircoursetowardstheirnextdestination(e.g.directionofAntwerporHamburg).

Alsotheinfluenceoftheexternalcircumstanceswind,currentandvisibilityareexamined.Allthreearefoundtohaveaninfluenceonbothvesselpathandspeed.Exceptforthevisibilitynosignificantdiffer-

Page -III-


encesininfluencearefoundbetweenthedifferentsizeclasses.IntheMaasmond,highcrosswindsandcrosscurrentsleadtoadeviationfromtheaveragepathinthedirectiontheexternalinfluenceisworkingandtoalowerspeed.Ingeneral,windandcurrentfrombehindthevesselleadtoahighervesselspeed.

Toobtainmoregenericrules,Thecaseareaissplitintoseveralparts.Ineverypart,thegeneralisedvesseldistributionandvesselspeeddistributionarederivedinanumberofcrosssections.Theinfluenceoftheexternalcircumstancesisgeneralisedaswell.Thesecauseashiftinthenormaldistributionsoverthewater-way.Finally,theinteractionbetweenvesselscanbeanalysedbyusingAISdata.Inthisthesisanexampleofthisisgiven.

Fourcurrentlyexistingmaritimemodels(Samson,HarbourSim,MartramandDymitri)aretestedtotheoutputofthecasestudy,toseeiftheresultscanbeimplemented.Noneofthemodelscanimmediatelyimplementtheresults.InMartram,theresultscanbeimplementedbymakingonlyasmallamountofadjustments.HarbourSimneedstobeadaptedmore,mainlytoincludethevessel(speed)distributionoverthewaterway.Itisverydifficulttoimplementtheresultsintheothertwomodels,astheyarenotmeantfornauticaltrafficsimulation(Samson)orhaveadifferentapproachforsimulating(Dymitri).

Therearethreeimportantrecommendationsforfutureresearch.First,differenttypesofvesselsshouldbeinvestigated,asinthisthesisonlycontainervesselswheretakenintoaccount.Secondly,moreresearchshouldbeperformedtoobtainabetterinsightintheinfluenceoftheexternalcircumstances.Inthisway,externalinfluencescanbedescribedmorepreciseandalsorelationshipbetweenthemandthevesselsizemightbederived.Finally,thevessel-vesselinteractionshouldbeexamined.Thisclearlyisthenextstepindescribingthevesselbehaviourinaportarea.

Page-IV-

Preface

Summary

Tableofcontents

Listoffigures

Listoftables

1 Introduction............................................................................................................................ 21.1 Background................................................................................................................ 21.2 Nauticaltrafficmodellingprograms.......................................................................... 31.3 Problemdefinition..................................................................................................... 31.4 Researchquestions.................................................................................................... 31.5 Researchapproach.................................................................................................... 41.6 Reportoutline........................................................................................................... 5

2 AutomaticIdentificationSystem............................................................................................. 82.1 Introduction............................................................................................................... 82.2 AISmessage............................................................................................................... 82.3 ErrorsinAISmessages............................................................................................... 92.4 Improvingsafetyofnavigationandotherapplications........................................... 102.5 Conclusions.............................................................................................................. 11

3 Maritimemodelling.............................................................................................................. 143.1 Thebasicprincipleofmaritimemodellingprograms.............................................. 143.2 TypeI:Thegeometricmodel................................................................................... 163.3 TypeII:MaritimeTrafficSimulationPrograms......................................................... 173.4 UseofAISinmodels................................................................................................ 193.5 Existingmaritimemodels........................................................................................ 20

4 Casestudysetup.................................................................................................................. 264.1 Approachcasestudy................................................................................................ 264.2 Location................................................................................................................... 264.3 Casestudyoutline................................................................................................... 29

5 Averagevesselpathandspeed............................................................................................. 325.1 Datasets.................................................................................................................. 325.2 Accuracyofthedatasets......................................................................................... 335.3 Theinfluenceofvesselsize..................................................................................... 375.4 Vesselandvesselspeeddistribution....................................................................... 425.5 Conclusions............................................................................................................. 54

Table of contents

Page-V-


6 Externalinfluences............................................................................................................... 586.1 Wind........................................................................................................................ 586.2 Current.................................................................................................................... 666.3 Visibility................................................................................................................... 706.4 Conclusions.............................................................................................................. 72

7 Interaction............................................................................................................................ 747.1 Interactioninthecasestudyarea........................................................................... 747.2 MethodI.................................................................................................................. 747.3 MethodII................................................................................................................. 777.4 Conclusion............................................................................................................... 78

8 Genericrules......................................................................................................................... 808.1 Definingwaterways................................................................................................. 808.2 Averagebehaviour................................................................................................... 838.3 Externalinfluences.................................................................................................. 858.4 Implementationinmaritimemodels....................................................................... 868.5 Conclusions.............................................................................................................. 87

9 Conclusions&recommendations......................................................................................... 909.1 Conclusions.............................................................................................................. 909.2 Recommendations................................................................................................... 90

References

Appendices

Page-VI-

Figure1.1 Worldseabornetrade1968-2008,.......................................................................... 2

Figure1.2 Reportoutline.......................................................................................................... 5

Figure3.1 Twovesselswithdifferent,overlappingsafetydomains........................................ 14

Figure3.2 Thebasicprincipleofthecalculationofcollisionrisk............................................ 15

Figure3.3 Thebasicprincipleofthecalculationofcollisionrisk,reflectedinprobabilities... 16

Figure3.4 Crossingwaterwayswithriskareaofship-shipcollision........................................ 17

Figure4.1 OverviewoftheportofRotterdam,theMaasvlakteIisindicated

bytheredcircle;................................................................................................... 27

Figure4.2 OverviewofMaasvlakteI,theAmazonehavenisindicatedbyaredellipse;........ 27

Figure4.3 PlotofthevesseltracksattheentranceoftheBeerkanaal.................................. 28

Figure4.4 PlotofthevesseltracksattheentranceoftheAmazonehaven............................ 28

Figure5.1 Calculationdifferencesbetweenaveragevesselpaths.......................................... 34

Figure5.2 Thecumulativedistributionfunctionofthedifferencesbetween

two average tracks, ............................................................................................... 35

Figure5.3 Averagepathofoutgoingvessels,sizeclasses<10,000dwt(green)

and>100,000dwt(blue)....................................................................................... 37

Figure5.4 Speeddevelopmentandtherelativedifferencebetweenthetracks(blue)......... 41

Figure5.5 OverviewofallAISmessagessentfromspecificareas.......................................... 43

Figure5.6 Crosssectionsonthevesseltrajectories,............................................................... 44

Figure5.7 Spatialdistributiononlocation3(seeFigure73),................................................ 45

Figure5.8 Spatialdistributionforthevesselsizeclass<10,000;incomingatlocation3(left)

and>100,000;outgoingatlocation2(right)......................................................... 47

Figure5.9 Thespatialvesseldistributionofthevesselsizeclass10,000-40,000,.................. 47

Figure5.10 Thespatialvesseldistributionofthevesselsizeclass40,000-70,000;

incomingatlocation3........................................................................................... 49

Figure5.11 Thespatialvesseldistributionofthevesselsizeclass70,000-100,000;outgoingat

location1(left)and3(right).................................................................................. 50

Figure5.12 Thespatialdistributiononlocation4forincoming(left)andoutgoing(right)

vesselsfromsizeclass>100,000dwt..................................................................... 51

List of figures

Page-VII-


Figure5.13 Thedifferenceinthevesselpathwhensailingforwards(red)orbackwards(blue)

intotheAmazonehaven......................................................................................... 51

Figure5.14 Vesselspeeddistributiononlocations1to4,forsizeclass70,000-100,000dwt;

incomingvessels.................................................................................................... 53

Figure5.15 Vesselspeeddistributionoverthecrosssectionsatlocations1to4................... 54

Figure6.1 PartIandpart2...................................................................................................... 58

Figure6.2 AverageheadinginMaasmondandBeerkanaal.................................................... 59

Figure6.3 Influenceofcrosswindonthechosenpathofindividualvesselsat

the’Maasmond’trajectory.................................................................................... 60

Figure6.4 BoxplotoftheinfluenceofcrosswindsintheMaasmond..................................... 61

Figure6.5 LinearrelationshipregardingtheinfluenceofcrosswindsintheMaasmond........ 62

Figure6.6 TheinfluenceofcrosswindsonthevesselspeedintheMaasmond...................... 62

Figure6.7 Developmentoftheaveragevesselheadingforthewholesizeclass>100,000dwt

andthepartofthevesselsthatencounterstrongcrosswindfromstarboardside.63

Figure6.8 Theinfluenceofparallelwindonthechosenpathandvesselspeedinthe

Maasmond............................................................................................................ 64

Figure6.9 Theinfluenceofcrosswindsonthevesselpathandvesselspeed

intheBeerkanaal................................................................................................... 64

Figure6.10 Theinfluenceofwindfrombehindandfromthefrontofthevessel

onthevesselpathintheBeerkanaal..................................................................... 65

Figure6.11 TheinfluenceofparallelwindonthevesselspeedintheBeerkanaal

forincoming(left)andoutgoing(right)vessels..................................................... 65

Figure6.12 Overviewofthedifferentcurrentregimesinthecasearea................................. 67

Figure6.13 Theinfluenceofcrosscurrentonthevesselpath(left)

andspeed(right)inpart1..................................................................................... 68

Figure6.14 Developmentofthevesselheadingunderinfluenceofastrongcrosscurrent

(green)comparedtotheaverageheading(blue).................................................. 68

Figure6.15 Theinfluenceofparallelcurrentonthevesselpath(left)

andspeed(right)inpart1.................................................................................... 69

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Figure6.16 Theinfluenceofparallelcurrentonthevesselpath(left)andspeed(right)

inpart2................................................................................................................ 69

Figure6.17 Theinfluenceofparallelcurrentonthevesselpathinpart4(Beerkanaal)......... 70

Figure6.18 Theinfluenceoflowvisibilityonthedeviationfromtheaveragepath

intheBeerkanaal.................................................................................................. 71

Figure7.1 ExplanationCPAandTCPA...................................................................................... 75

Figure7.2 AnexampleofinteractionshortlybeforetheentranceintotheBeerkanaal......... 75

Figure7.3 Developmentofthevesselspeed(left)andvesselheading(right)compared

totheaverageofthesizeclass70,000-100,000dwt(discontinuousline)............ 76

Figure7.4 Exampleoftheinteractionofanoutliers(purpletriangle)withanothervessel,

afterplottingthewholetrafficimage.................................................................... 78

Figure8.1 Overviewofthedifferentcurrentregimesinthecasearea................................... 80

Figure8.2 Overviewofthesimplifiedwaterway(blue)inpart1........................................... 81

Figure8.3 Overviewofthesimplifiedwaterwayinpart2...................................................... 81



Figure8.6 Thecrosssectionsthatareinvestigatedinpart1................................................. 83

Figure8.7 Distributionoverthewaterwayatcrosssection1-C.............................................. 84

Figure8.8 Thespeeddistributionforincomingvesselsatcrosssection1-C.......................... 84

Figure8.9 Theinfluenceofcrosscurrentonthevesselpathatpart1.................................. 86

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Page -X-

Table2.1 Numbersofvesselstransmittingerrorsbyyear...................................................... 10

Table5.1 Numberoftracksineachdataset............................................................................ 33

Table5.2 Comparisonoftheaveragetracks,calculatedbyrespectively50%and100%

ofthedata............................................................................................................. 34

Table5.3 The95%confidenceintervalsinmetersforthedistancebetweentwoaverage

tracksofonevesselsizeclass................................................................................ 35

Table5.4 Comparisonofthespeedoftheaveragetracks,calculatedbyrespectively50%

and100%ofthedata............................................................................................ 36

Table5.5 The95%confidenceintervalsinpercentagesforthespeeddifferencebetween

twoaveragetracksofonevesselsizeclass............................................................ 36

Table5.6 Comparisonoftheaveragetracksfromdifferentvesselsizeclasses,forincoming

vessels................................................................................................................... 38

Table5.7 Comparisonoftheaveragetracksfromdifferentvesselsizeclasses,foroutgoing

vessels................................................................................................................... 38

Table5.8 95%confidenceintervalsinmetersforthedifferencebetweentheaverage

trajectoriesoftwovesselsizeclasses.................................................................... 39

Table5.9 95%confidenceintervalsinmetersforthedifferencebetweentheaveragetrajecto-

riesoftwovesselsizeclasses,forthetrajectorywithintheport’sbreakwater.... 39

Table5.10 Comparisonoftheaveragespeedfromdifferentvesselsizeclasses,for

incomingvessels................................................................................................... 40

Table5.11 Comparisonoftheaveragespeedfromdifferentvesselsizeclasses,for

outgoingvessels................................................................................................... 40

Table5.12 95%confidenceintervalsinpercentagesforthedifferencebetweenthespeeds

oftwovesselsizeclasses....................................................................................... 40

Table5.13 Skewnessforthedifferentdatasetsatlocations1to4........................................ 46

Table5.14 Excesskurtosisforthedifferentdatasetsatlocations1to4................................ 46

Table5.15 Resultsoftheχ2-testsforthefittingoftheassumednormaldistributionto

thedifferentdatasets........................................................................................... 48

List of tables

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Table5.16 Coefficientsofdetermination(R2)forthespatialvesseldistribution................... 49

Table5.17 Coefficientsofdetermination(R2)forthevesselspeeddistributionin

locations1to4...................................................................................................... 52

Table6.1 Windspeedclasses.................................................................................................. 59

Table6.2 Currentvelocityclasses............................................................................................ 67

Table8.1 Characteristicsofthedifferentsizeclassesincrosssection1-C.............................. 85

Table8.2 Vesselspeedcharacteristicsofthedifferentsizeclassesincrosssection1-A......... 85

Chapter 1

Chapter 8

Chapter 5

Descrip�on the func�ons of AIS and an inves�ga�on of the quality of AIS messages

Research ques�on 1: What are the possibili�es and limita�ons of AIS data, when using it in mari�me modelling research?

Chapter 4

Chapter 3

Chapter 2 Subques�on 1-A: What are the possibili�es and limita�ons of AIS (data)?

Introduc�on of AIS , mari�me traffic simula�on programs. Problem defini�on and research ques�ons .

Explana�on of the characterics of mari�me models and how AIS is used in the models nowadays.

Subques�on 1-B: What are the main characteris�cs of mari�me traffic simula�on programs?

Subques�on 1-C: How is AIS used in the development of mari�me models nowadays?

Research ques�on 2: Can the exact nau�cal behaviour of vessels in the port of Ro�erdam be described using sta�s�cal equa�ons, following from an analysis of AIS data ?

A descrip�on of the case study that is used in this thesis

Analysis of the average vessel path and vessel speed, as well as an inves�ga�on of the influence of vessel size.

Subques�on 2-A: What factors are important in a vessel’s exact path and vessel speed an to what extent?

Deriva�on of generic rules, based on the outcomes of the case study. Also a discussion of the possibility to implement

these rules into currently exis�ng mari�me models. Subques�on 3-B: Is it possible to implement the derived equa�ons into a currently exis�ng mari�me model or should a new model be developed?

Research ques�on 3: Is it possible to develop derive generic mari�me model rules that describe the vessel behaviour in a port area?

Subques�on 3-A: How can these specific equa�ons be made generic?

Chapter Content Subques�on answered

Chapter 6 Analysis of the influence of the external circumstances wind, current and visibility on the vessel path and speed

Subques�on 2-B: How do interac�ons with other vessels influence a vessel’s course?Chapter 7 Analysis of the influence of the vessel-vessel interac�on.

Introduction

Chapter1

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Introduction

1 Introduction

1.1 Background

Maritimetransporthasalwaysbeenveryimportantininternationaltrade.Especiallysincetheintroductionofthecontainerinthefifties,maritimetransporthasrapidlyincreasedduetoitscost-efficiency(Figure1.1).Thishasledtoanenormousgrowthofthetrafficintensityinportsallovertheworld.Notonlythenumberofvesselshasincreased,alsothevessel-sizehasbeendeveloping.1

Figure 1.1 World seaborne trade 1968-2008, source: www.marisec.org

Withtheabovementioneddevelopmentsinmaritimetransport,safetyandcapacityissuescomeup.TheInternationalMaritimeOrganization(IMO)2hasbeenveryimportantfortheimprovementofsafetyatsea.Thisorganisation,establishedin1948inGeneva,maintainsseveraltreatiesthataimtoimprovethenauti-calsafety.AnexampleofsuchatreatyisSOLAS(SafetyofLifeatSea),whichgivesrulesandguidelinestopreventaccidents.Oneoftheserulesistheobligationforseagoingvesselslargerthan300GrossTonnage(GT)tocarryanAutomaticIdentificationSystem(AIS)sinceDecember2004.

VesselsequippedwithAIScarryaninstrumentwhichtransmitsandreceivesdataaboutthevesseloveradedicatedVHF(VeryHighFrequency)radioband.Thetimeintervalinwhichthisisdonedependsonthespeedofthevesselandrangesfrom2secondsto10secondswhensailing.Thedatacontainsthegeneralinformationofavesselaswellasitsposition,speed,heading,originanddestination,cargoandcurrentdraft.Thisinformationispickedupbyothervesselsandcoastalauthorities.Theothervesselsuseitfornavi-

1 Internationalchamberofshipping(ICS)&Internationalshippingfederation(ISF),

http://www.marisec.org/shippingfacts/,accessed:26/1/2010

2 MoreinformationregardingtheIMOandtheSOLAStreatycanbefoundinAppendixA.

Page-3-


gationalpurposes,whiletheauthoritiescanuseitforidentification(security)andcommunication.3 More informationregardingthecharacteristicsanduseofAIScanbefoundinchapter2.

1.2 Nautical traffic modelling programs

Besidesinternationalrulesandguidelines,awaytoimproveanddeterminesafetyandcapacityisbytheuseofmaritimemodels.Especiallyinportplanninganddesign,modellingprogramscanbeaveryvaluabletool.Theycanforexampledemonstratetheeffectivenessofdifferentriskcontrolmeasures;therebyassistingtheevaluationofalternatives(Seignette,2005).Differenttypesofmodelsexisttosupportdecisionsinthedevelopmentofportinfrastructure.Someofthesemodels(FastTimeManoeuvringSimulationPrograms)describeavessel’smotioningreatdetail,bytakingintoaccountexternalinfluencessuchaswindandcur-rents.Animportantoutputofsuchamodelistheprecisepathasinglevesseltakesinacertainportareaandthecontrolsitapplies.Therisksfollowingfromtheinteractionbetweenvesselshoweverisnotsimu-lated,becausemostlythemodellingofmultiplevesselssimultaneouslyisnotdone(Pimontel,2007).

Inanothertypeofmodel,themaritimetrafficmodellingprograms,multiplevesselsaretakenintoaccount.Thismakesitpossibletocalculatesafetyandcapacityofacertainwaterway.Theseprogramshoweverdonotreachthesamelevelofdetailofthefasttimemanoeuvringmodels.Somemodelstrytoapproximatethevesselbehaviour,butmostofthemdonotsimulateexactvesselmovements.Thismeansthatalsothevesselinteractionwithothervesselsandinfrastructureisnotsimulated.Especiallyinbusy,closedwater-wayslikeportsthismakesitverydifficulttoquantifynauticalriskssufficiently.

1.3 Problem definition

Asmentionedabove,currentmaritimemodelsdonotsufficientlysimulatetheexactvesselbehaviourandinteractionwithothervessels.WiththeintroductionofAIS,anewpossibilityisavailabletogetmoreinsightintothisnauticalbehaviour.AISmessagesaresentonaveryregularbaseandthereforealotofprecisedataispresent.Thismakesitpotentiallypossibletostatisticallydescribevesselbehaviour.AIShoweverisnotoriginallydevelopedforresearchpurposes.Itisnotsurewhicherrorsanduncertaintiesarepresentandifandhowthislimitsthepossibilityofusingitinmodelling.Thereforethesedatashouldbeexaminedverycriticalbeforeusing.Thisleadstotheproblemdefinitionofthisresearch:

Theexactcourseofavesselanditsinteractionwithothervesselsandinfrastructureisnotalwayssimulatedinsufficientdetailincurrentmaritimemodels,ananalysisofAISdatamayimprovetheinsightinandmod-ellingoftheexactnauticalbehaviour.

1.4 Research questions

Theproblemdefinitionissplitupintothreeresearchquestions.Becausemodellingexactvesselbehaviourisespeciallyimportantinportareas,theportofRotterdamareaisusedasacasestudy.Eachofthequestionsisdividedintoseveralsubquestions.

3 Internationalmaritimeorganization(IMO),

www.imo.org,accessed:26/1/2010

Page-4-

Introduction

1. WhatarethepossibilitiesandlimitationsofAISdata,whenusingitinmaritimemodellingresearch?

1-AWhatarethepossibilitiesandlimitationsofAIS(data)?

1-BWhatarethemaincharacteristicsofmaritimetrafficmodellingprograms?

1-CHowisAISusedinthedevelopmentofmaritimemodelsnowadays?

2. CanthedetailednauticalbehaviourofvesselsintheportofRotterdambedescribedusingstatistical equations,followingfromananalysisofAISdata?

2-AWhichfactorsareimportantinavessel’sexactpathandspeedandtowhatextent?

2-BHowdointeractionswithothervesselsinfluenceavessel’spathandspeed?

3. Isitpossibletoderivegenericmaritimemodelrulesthatdescribevesselbehaviourina portarea?

3-AHowcanthesespecificrulesbemadegeneric?

3-BIsitpossibletoimplementthederivedequationsintoacurrentlyexistingmaritimemodelor shouldanewmodelbedeveloped?

1.5 Research approach

Theapproachusedinthisthesistoanswerthethreemainresearchquestions,canalsobesplitintothreesections.First,aliteraturestudyisneededtoobtaininsightintoAISandmaritimemodels.Afactualdescrip-tionofAIS(messages)isgiven,butalsoinsightinthequalityofAISdata,toanswersubquestion1-A.Togetinformationregardingmaritimemodels,anoverviewisgivenoftheapproachofmaritimemodelsnowa-days.AlsotheuseofAISdatainthesemodelsisinvestigated.

Researchquestion2isansweredbyusingacasestudy.Byusingaspecifiedarea,aselectioninvesseltracksthatareexaminedcanbemade.Itmakesitalsopossibletocomparethederivedresultswitheachothermoreeasy.Inthiscasestudy,firsttheinfluenceofthevesselsizeisinvestigated.Thisisdone,becauseafterthisisknown,thevesselscanbebroughttogetherinsuitablesizeclasses.Theaveragevesselpathandspeediscalculatedforthedifferentsizeclasses.

Whentheaveragebehaviourisknown,itcanberesearchedwhatotherinfluencesdoexistthatinfluenceavessel’spathandspeed.Mainfocuswillbeontheinfluenceofexternalcircumstances,likewind.Alsothevessel-vesselinteractionwillbetakenintoaccount.Thisisdifferentfromtheotherinfluences,asinteractionsituationsaremostlyverycasespecific.Thecalculationoftheinfluenceofinteractionwillthereforeneedanapproachthatfocussesonthedetailedanalysisofindividualsituations.

Researchquestion3isdividedintotwosubquestions.Thefirstsubquestionhandlesthederivationofgener-icrules.Thesecanbemade,bysimplifyingthenauticalinfrastructurefromthecasestudytomorestandardtypesofwaterways.Theresultsfromthecasestudycanthanbegeneralised.Thesecondquestionscon-cernsthepossibilitytoimplementtheserulesinanexistingmaritimemodel.Toanswerthisquestion,thespecificcharacteristicsofseveralmaritimemodelsusednowadaysareelaborated.

Page-5-


1.6 Report outline

Researchquestions1anditssubquestionswillbeansweredinchapters2and3.Question2,includingsubquestions,ishandledinchapters4-7.Theanswertoquestion3anditssubquestionsisgiveninchapter8.Figure1.2showsthereportoutlinegraphically.

Chapter 1

Chapter 8

Chapter 5

Descrip�on the func�ons of AIS and an inves�ga�on of the quality of AIS messages

Research ques�on 1: What are the possibili�es and limita�ons of AIS data, when using it in mari�me modelling research?

Chapter 4

Chapter 3

Chapter 2 Subques�on 1-A: What are the possibili�es and limita�ons of AIS (data)?

Introduc�on of AIS , mari�me traffic simula�on programs. Problem defini�on and research ques�ons .

Explana�on of the characterics of mari�me models and how AIS is used in the models nowadays.

Subques�on 1-B: What are the main characteris�cs of mari�me traffic simula�on programs?

Subques�on 1-C: How is AIS used in the development of mari�me models nowadays?

Research ques�on 2: Can the exact nau�cal behaviour of vessels in the port of Ro�erdam be described using sta�s�cal equa�ons, following from an analysis of AIS data ?

A descrip�on of the case study that is used in this thesis

Analysis of the average vessel path and vessel speed, as well as an inves�ga�on of the influence of vessel size.

Subques�on 2-A: What factors are important in a vessel’s exact path and vessel speed an to what extent?

Deriva�on of generic rules, based on the outcomes of the case study. Also a discussion of the possibility to implement

these rules into currently exis�ng mari�me models. Subques�on 3-B: Is it possible to implement the derived equa�ons into a currently exis�ng mari�me model or should a new model be developed?

Research ques�on 3: Is it possible to develop derive generic mari�me model rules that describe the vessel behaviour in a port area?

Subques�on 3-A: How can these specific equa�ons be made generic?

Chapter Content Subques�on answered

Chapter 6 Analysis of the influence of the external circumstances wind, current and visibility on the vessel path and speed

Subques�on 2-B: How do interac�ons with other vessels influence a vessel’s course?Chapter 7 Analysis of the influence of the vessel-vessel interac�on.

Figure 1.2 Report outline

AutomaticIdentificationSystem

Chapter2

Page-8-

AIS

2 Automatic Identification System

ThischapterexplainstheworkingoftheAutomaticIdentificationSystem(AIS).Itindicatestheseveralfunc-tionsofAISandhowthemessagesaretransmitted.Alsothedataincludedinamessageandthequalityofthedataisdescribed.

2.1 Introduction

InDecember2000IMOdecidedtostartimplementingAISintheinternationalseatrade.TheobjectivesfortheimplementationofAISwere‘toenhancesafetyandefficiencyofnavigation,safetyoflifeatsea,andmaritimeenvironmentalprotectionthroughbetteridentificationofvessels,assistedtargettracking,andimprovedsituationalawarenessandassessmentthroughsimplifiedandadditionalinformation.AIScanalsoimprovethequalityofvesseltrafficsurveillance(VTS)andwaterwaymanagement’.(Harati-Mokhtari,et.al.2007,p.374)

FromtheobjectivesmentionedaboveroughlythreefunctionsofAIScanbedistinguished.

1.Toassistinnavigationandcollisionavoidance.

2.Topassinformationaboutavesselanditscargotocoastalstates.

3.TohelpintrafficmanagementasaVTStool.

EspeciallythefirstfunctionisaveryimportantcharacteristicofAIS.ByreceivingAISmessagesfromnearbyvessels,apreciseoverviewofthetrafficsituationaroundthevesselisderived.Becauseidentificationisdoneautomatically,communicationiseasier.Thismakesitpossibletosolvepotentiallydangeroussituationsmuchquicker.Thisandotheradvantagesareelaboratedmoreintodetailinthenextsection.

ThetimeschemeoftheintroductionofAISisdescribedintheSOLAStreaty.FromDecember2004onwardsallsea-goingvesselslargerthan300grosstonnages(GT)areobligedtohaveAISonboard.Inpracticealmosteverysea-goingcargovesselexceedsthisweightlimitandcarriesAISnowadays.FishingandinlandvesselsaswellaspleasureyachtsuseAISlessoften.TheuseofAISby-especially-inlandvesselsishoweverexpectedtoincreaserapidly.4

2.2 AIS message

VesselsthathaveanAIScarryatransponderwhichtransmitsmessagesaboutthevesseloveradedicatedVHF(VeryHighFrequency)radioband.ThefrequenciesintheVHFrangearemuchlowerthanthefrequen-ciesusedbymarineradar(whichusesSuperHighFrequencies).ThismeansthatAISmessagesaresentwithalargerwavelengthaswell.DuetothislargerwavelengthAISisabletodetecttargetsinsituationswhereradardetectionislimited.Thisisthecasearoundbends,behindhillsandothervesselsandinconditionsofrestrictedvisibilityinportsandrestrictedwaterways.

4 Currently3%oftheinlandvesselsthatvisittheportofRotterdamareequippedwithiAIS(inlandAIS).The

expectationisthat,duetonationalandEuropeanstimulationprograms,attheendof2012thisnumberhas

increasedtoalmost80%.Source:R.W.P.Seignette,portofRotterdam.

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TherearethreetypesofdatainanAISmessages:staticdata,voyagerelateddataanddynamicdata.Thecategoriesarevalidfordifferenttimeperiodsandthereforehavedifferentupdateintervals.Staticdataandvoyagerelateddataaretransmittedevery6minutes,onrequestofacompetentauthorityandwhenthedataarechanged.Thetimeintervalofthedynamicdatamessagedependsonthespeed,coursealterationandnavigationalstatusofthevessel.Whenthevesselismooredamessageissentevery3minutes.Whensailing,thistimeintervalrangesfrom2seconds(speed>23knots≈11.8m/s)to10seconds(speed<14knots≈7.2m/sandnocoursealterations).Ifneededalsoshortsafety-relatedmessagescanbesent.

StaticdataareenteredintothesystemduringtheAISinstallationandneedonlytobechangedifthenameofavesselchangesorifthevesselundergoesaconversiontoanothershiptype.Examplesofstaticdataarename,MMSI-number(MaritimeMobileServiceIdentity),vesseltype,lengthandpositionoftheAIStrans-mitteronthevessel.Voyagerelatedinformationconcernsissueslikethevessel’sdraught,destinationandETA(EstimatedTimeofArrival).Thisinformationneedstobekeptuptodatemanuallybytheship’screw,whichmakesitsensitivetoerrorsanduncertainties.

Dynamicdataoriginatefromthevesselsnavigationalinstruments;examplesarethevessel’sposition,head-ingandrateofturn.Thepositionofthevesselisreportedbythreeparameters:longitude,latitudeandapositionaccuracyreport.Thelongitudeandlatitudearegivenin1/10,000minute,whichis-inlatitudinaldi-rection-equaltoapproximately20cm.Inlongitudinaldirectionthisnumberdependsonthedistancetotheequator(Netherlands≈11cm).Thepositionaccuracyreportindicateshowaccuratethetwomentionedpositionreportsare(IALAandAISM,2004).

AdetailedoverviewofthedatainsideanAISmessagecanbefoundinAppendixB.

2.3 Errors in AIS messages

ToinvestigatethequalityofthedatainAISmessagessomesurveyshavebeenundertaken.Mostsurveysonlylookattheerrorsthatoccurinalimitednumberofparameters.Bailey,etal.(2008)studytheinfluenceoftheintroductionofAIS.InthisstudyAISmessagestransmittedbyvesselsintheDoverStraitarejudgedinthreedifferentyears.Harati-Mokhtarietal.(2007)investigatederrorsinAISmessagesbyusingthreediffer-entdatasets.Intheirstudy,static,voyage-relatedanddynamicdataareexamined.

Bailey,etal.(2008)lookedtothemaritimetrafficofoneweekintheDoverStraits.Thiswasdoneinthreedifferentyears,leadingtodatasetsof806(2004),901(2005)and940(2007)vessels.Afteranalysis,errorswerefoundinMMSI-number,CallSign,Name,Draught,DestinationandCourse.Byfarthemosterrorsoc-curredinthecategoriesDestinationandDraught.ErrorsinDestinationincludedmisspelling,emptydatafields,incomprehensibleabbreviationsandreferencestothepreviousport.Mostoftheerrorsindraughtwerelessthan1meter,butinsomecasesadifferenceofmorethan3mwasfound.

Becausethereweredatafromthreedifferentyears,itwaspossibletocreateacomparisonbetweenthoseyears.Bydoingso,theyfoundthatthepercentageofvesselsthattransmittederrorsdecreasedfrom10.4%in2004to3.5%in2007.Howevertheauthorsremarkthat,duetoseveralreasons,thislastnumbermaytosomeextentunderestimatetheactualnumberoferrors.Thisdoesnotinfluencetheirconclusionthatthenumberoferrorsisdecreasingyearonyear.ThenumbersaresummarisedinTable2.1.

Page-10-

AIS

Table 2.1 Numbers of vessels transmitting errors by year. Source: Bailey, Ellis et al., 2008

YearTotal number

of vesselsNumber of vessel

transmitting errorsPercentage of vessels

transmitting errorsNumber of errors

2004 806 84 10.4% 122

2005 901 71 7.9% 99

2007 940 33 3.5% 44

Harati-Mokhtarietal(2007)usethreedifferentdatasetstoinvestigateerrorsandinaccuraciesinthediffer-entfieldsofanAISmessage.Inoneoftheuseddatasets(‘Data-miningstudy’),8%fromatotalof400,059reportscontainederrorsconcerningMMSInumber,IMOnumber,position,courseoverground(COG),andspeedoverground(SOG).Theseerroneousreportswereinvestigatedfurther.Anotherdataset(VTS-basedstudy),containinginformationfrom94differentAISequippedvessels,wasusedfortheinvestigationoftheMMSInumber,vesseltype,ship’snameandcallsign,length,beamandnavigationalstatus.Athirddataset(ProactiveAISstudy)waspresent,butonlyusedtoinvestigateerrorsinMMSI-number.

Inthestaticdata,errorswerefoundinMMSI-number,vesseltype,vesselname,callsign,lengthandbeam.Mainsourceoferrorswasthevesseltype,whichdescriptionwasfoundtobevagueorincorrectinrespec-tively74%(VTS-basedstudy)and56%(Data-miningstudy)ofthecases.

Intheanalysisofvoyage-relateddata,thefocusoftheauthorsisondestination,ETA(EstimatedTimeofArrival)anddraught.Inthedata-miningstudy,49%containederrorsconcerningdestinationandETA.In31%oftheinvestigatedmessagesobviouserrorsinthevesselsdraughtswerereported.Theanalysisofdynamicdatafocusesonlyontheerrorsinthecategory‘NavigationalStatus’,whichforexampleindicatesifavesselissailingoranchored.Incorrectnavigationalstatusinformationwasgivenby30%ofthevessels(VTS-basedstudy).

Solvsteen(2009)alsoshowssomeresultsaboutthequalityofAISdata.HeconcludesthatmosterrorsoccurinETA(21.7%oftheobservationswerewrong),IMO-number(14.1%)andDestination(11.0%).HealsofounderrorsinRateofTurn(8.9%),Heading(7.1%),Dimensions(6.2%),Draught(5.7%),CourseoverGround(0.8%),SpeedoverGround(0.8%)andamissingshipname(0.04%).ItisnotsureifSolvsteendidnotfindanyerrorsintheotherparameters,liketheNavigationalStatus,ordidnottakethemintoaccount.

2.4 Improving safety of navigation and other applications

Asdescribedinthefirstsectionofthischapter,theprimaryfunctionofAISistoassistinnavigationandcol-lisionavoidance.OtherfunctionsarepassinginformationtocoastalauthoritiesandhelpingVTSsintrafficmanagement.Nexttothesethreefunctions,otherapplicationshavecomeupthatuseAIS.Insearchandrescueoperationsforexample,SAR(Search&Rescue)aircraftstransmittheirpositionbyAIS.

TheuseofAISbyVTSs,coastalauthoritiesandSearch&RescueoperationsisdescribedinAppendixC.Anotherexample,alreadymentionedinthefirstsection,istheuseofAISdatainmaritimemodelling;thissubjectishandledinchapter3.BelowadescriptionisgivenhowAISfulfilsitsprimaryfunctionandim-provessafetyofnavigation.

Page-11-


ThereareseveralwaysinwhichAISimprovesthesafetyofnavigation.Oneofthemhastodowiththeinformationexchangebetweenvessels.VesselsautomaticallypickupAISmessagesfromnearbyequippedvessels.OtherapplicationsmakeuseofthefactthatanAISsignalcanalsooriginatefromothersourcesthanvessels,forexampleabuoy.

WhenvesselsreceiveanAISmessagetheyautomaticallydecodeanddisplaytheinformationtotheofficeronwatch.InthiswayacompletepictureofallAISequippedshipswithinVHFrangecanbederived.BeforeAISwasused,thetrafficsituationaroundavesselwasderivedbyplottingaradarimage.TheadvantageofAIScomparedtothisradarimageisthatthevesselsareautomaticallyidentified.Inthisidentificationnotonlythenameofothervesselsisprovided,butalsoothercharacteristicssuchasshiptypeandsize.NexttothisadvantageAISisalsoabletodetecttargetsonplaceswheretheradardetectionis(temporarily)limited.

Thisgivesabetteroverviewofthesituationaroundthevessel.Becausetheidentityofthesurroundingves-selsisknownitalsoiseasiertocallonothervesselsandcommunicate.Thereforeevasivemanoeuvrescanbeagreeduponquicker,whichreducescollisionrisk.ThisclearlyshowstheadvantagesofAISoverradar.ItishowevernotpossibletorelycompletelyonthetrafficimagederivedfromAIS.ThishastodowiththefactthatAISmessagesaresentactively.IfavesselisnotequippedwithAIS,itwillnotbedetected.Radarwavesdonothavethisproblem,becausetheyaresimplyreflectedbyeveryobstacle.

ThisdisadvantageofAISismostvisibleinsituationswherealotofvesselswithandwithoutAISarepresent.Thishappensmainlyinandaroundportareas,wherecargoistransferredbetweenlargeoceanvesselsandothertransportmodessuchasinlandwaterwaytransport.Especiallyinlandvessels,butalsofishingves-eslsandrecreationalvesselsdosometimesinterfereintheseplaceswithseagoingcargovessels.InthesesituationsAISdoesnotgiveasufficienttrafficoverviewanditisbettertorelyontheradarimage.AIScanhoweverstillbeusedasanadditionalsourceofinformation,mainlyforidentificationpurposes.

AnotherinterestingabilityofAISisthetransmittingofpositionsandnamesofobjectsotherthanvessels,forexamplenavigationalaidsaslighthousesandbuoys.Thiscanbedoneintwoways.OneoptionisthatthenavigationalaidsendsAISmessageswithitsowntransmitter.Anotherwayisthathissignalissentbyanearbybasestation.Topassingshipsthisseemstocomefromtheaiditself.Thismethodisknownassyn-theticAISandcanbeinterestingwhenitisnotpossibletoequipanavigationalaidwithitsownAIStrans-mitter.AIScanalsobeusedtogivelocationswhicharenotvisible,likeawreckedship.Againabasestationsendsoutamessageandthenon-visibletargetappearsonavesselitsscreen.ThisisknownasvirtualAIS.5

2.5 Conclusions

AISisawellknownsysteminmaritimetransportnowadays.Especiallyseagoingcargovesselsareequippedwiththesystem.ThemainfunctionofAISiscollisionavoidanceandaidtonavigation.ItisalsousedbycoastalauthoritiesandVTSsforrespectivelysecurityandtrafficmanagementreasons.OtherapplicationsofAISare,amongstotherthings,searchandrescueandtheuseofdatainmaritimemodelling.

5 UKGovernmentStrategyforAIS,Departmentfortransport,UnitedKingdom,

http://www.dft.gov.uk/pgr/shippingports/ports/modern/ais/ukgovernmentstrategyforais?page=2,

accessed:17/12/2009

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AIS

SincetheintroductionofAIS,severalresearcheshavebeenperformedtoinvestigatethequalityofAISmes-sages.Everyresearchfocussesondifferentparametersandusesdatasetsfromdifferentyearsandlocations.Thereforeitisdifficulttocomparethemanddrawconclusions.Therearehoweversomesimilaritiesbe-tweenthethreeresearchesmentioned.OnecommonconclusionisthatasignificantamountofAISmes-sagescontainerrors.MostproblemswerefoundinthecategoriesDestination,ETA,Draught,VesselTypeandNavigationalStatus.ExceptfortheVesselType,thesecategoriescontaindatathathavetobeupdatedmanually.

Duetothedifferencesbetweenthethreestudiesmentioned,itisdifficulttoconcludesomethingaboutthedevelopmentofthequalityofAISdata.Harati-Mokhtarietal.(2007)findforexamplemuchhighererrorpercentagesthanBailey,EllisandSampson(2008).ThefindingsofSolvsteen(2009)lieinbetween.OnlyBai-ley,EllisandSampsonetal(2008)lookatthequalityofthedataindifferentyearsandfromtheirresearchitispossibletostatethattheAISdataqualityisimproving.Moreresearchishoweverneededtosupportthisstatement.

Number of collisions to be expected

Number of encounters Causa�on probability

Collision probability

Probability a ‘model’ encounter becomes a real

encounter

Probability that a real encounter becomes an

accident

Maritimemodelling

Chapter3

Page-14-

Maritimemodelling

3 Maritime modelling

Mostnauticalsafety-andcapacitystudiesusemaritimemodelsforthemodellingofnauticaltraffic.Almostallprogramsusethesamebasicprinciple,especiallyforthedeterminationofcollisionrisk.Thereishoweveramaincharacteristicthatdividestheseprogramsintotwotypes.Thischaracteristicconcernsthequestionifindividualvesselmovementsaresimulated.

Thefirsttype,thegeometricmodel,usesstatisticalknowledgeoftrafficintensitiesanddistributions.Noindividualvesselmovementsaresimulated.However,maritimetrafficsimulationprograms,simulateindi-vidualvesselmovements.Thischapterdescribesthebasicprincipleofmaritimemodellingprogramsaswellasthecharacteristicsandlimitationsofthetwotypesofmodelsmentioned.

3.1 The basic principle of maritime modelling programs

Moststudiesthatusemaritimemodels,aimtoderivethenauticalsafetyofacertainwaterway.Inpracticethismeansthecalculationofcollisionriskswithinapredefinedtimespan.Forthedeterminationofthis,modelscalculatethenumberofaccidentsthatcanbeexpected;thisisdoneintwosteps.Firstanumberofpotentialdangeroussituationsiscalculated.Secondly,thisnumberisusedtocalculateanumberofcolli-sionsthatistobeexpected.

Thepotentiallydangeroussituationsarecalledencounters.Inpractice,whentwovesselscometooclosetoeachother,thisiscalledanencounter.Thisraisesthequestionhowclosevesselscansailtoeachother,be-forethisis‘tooclose’.Forthis,theprincipleofvesselsafetydomainsisused.Asafetydomainisaprescribedareaaroundavessel.Iftwosafetydomainsoverlaporifavesselentersthedomainofanothervessel,theyaretooclosetoeachother;thiscountsasanencounter(seeFigure3.1).So,thesizeofthevesselsafetydomainisaleadingparameterinthedeterminationofthenumberofencounters.

Figure 3.1 Two vessels with different, overlapping safety domains.

Itishowevernotveryeasytodeterminethesizeandshapeofthisdomain,becauseitdependsonalotofparameters:characteristicsofthevesselsinvolved(e.g.speed,dimensions,manoeuvrability),thetrafficsituation(e.g.trafficintensity,widthofwaterway)andexternalinfluences(e.g.visibility,wind,waves).Dif-ferentstudieshavebeenperformedtodeterminevesselsafetydomains.However,noconsensushasbeenreachedyetonthesizeandshapeofthedomains(Pimontel,2007).

Page-15-


Differenttypesofmaritimemodelscalculatethenumberofencountersindifferentways.Thishasespeciallytodowiththemodellingofindividualvesselmovementsandtheabilityofvesselsinamodeltomanoeu-vre,therebypreventingencounters.Ingeometricmodels,wherenoindividualmovementsaresimulated,thisleadstoanoverestimationofthenumberofencountersinreality.Theothermodelsdosimulatevesselmovements,butthemanoeuvringpossibilitiesareoftenveryrestricted.Therefore,theyalsoover-estimatethenumberofencounters.

Thisover-estimationiscompensatedbythecausationprobability.Thisnumberincludestheprobabilitythatanaccidenthappens,giventheoccurrenceofanencounterinthemodel.Thecausationprobabilitycanbedividedintwoparts.Thefirstpartcompensatestheover-estimationofthenumberofencountersfollowingfromamodelrun.Thisisreflectedbytheprobabilityanencounterhappens,giventhefactthatanencoun-tersoccursinthemodelrun.Thesecondpartconcernsthefactthatanencounterisnotequaltoanacci-dent.Thisisreflectedbytheprobabilityanaccidenthappens,giventheoccurrenceofarealencounter.

Thephysicalmeaningofthecausationfactoristhepercentageofvesselsthatdoesnotmakeasufficientevasivemanoeuvrewhenneeded,topreventanaccident.Thisprincipleisusedbymaritimemodelsinthecalculationofthecausationfactor,whichisdoneintwoways.OneoptionistheuseofBayesiannetworks.Thesenetworksarebuiltinsuchawaythattheycalculatetheprobabilityavesseldoesnotrespondsuffi-cientlytopreventanaccident.Factorssuchasvisibility,stresslevelandVTSassistanceareincluded.

Anotheroptionforthederivationofthecausationfactoristheuseofhistoricalaccidentdata.Inthismethodthecausationfactorisdeterminedinsuchawaythattheoutcomeofthemodel(collisionprobabi-lity)isplausible.Historicaldataisalsousedinthefirstmethod,forthevalidationoftheBayesiannetworks.Theproblemofaccidentdataisthefactthatthesearenotalwaysavailable.Withoutthedataitisnotpos-sibletochecktheoutcomeofthemodel.Inthesesituationsitisnotpossibletoquantifynauticalrisk;onlyconclusionscanbedrawnontherelativesafetyofdifferentalternatives.

So,bycombiningthenumberofencountersandthecausationprobability,anumberofaccidentsisob-tained.Finallythistotalnumberofaccidentsisconvertedtoacollisionrisk(seeFigure3.2andFigure3.3).

Number of collisions to be expected

Number of encounters Causa�on probability

Collision probability

Probability a ‘model’ encounter becomes a real

encounter

Probability that a real encounter becomes an

accident

Figure 3.2 The basic principle of the calculation of collision risk.

Page-16-

Maritimemodelling

Figure 3.3 The basic principle of the calculation of collision risk, reflected in probabilities

C = Collision; Em = Encounter in model run; Er = Encounter to be expected in reality.

3.2 Type I: The geometric model

Insomemodelsnoindividualvesselmovementsaresimulated.Vesselssailalongapredefinedtrack,ac-cordingtoaspatialdistributionoverthewaterway.Theydonothavetheabilitytodeviatefromthesestandardroutes.Whenavesselmeetsanobstaclelikeanothervesselorashoal,italsodoesnotreact.Thisprincipleisknownasthegeometricmodel,becausethecalculationsarebasedongeometricprobability.TheprincipleisrootedintheapproachdefinedbyFujii,etal.(1974)andMacDuff(1974).(Kujala,etal.,2009,p.1353).AnexampleofamodelthatworkswiththisprincipleisSAMSON(SafetyAssessmentModelforShippingandOffshoreontheNorthSea),usedbyMarin6,mainlyfornauticalsafetystudies.

Thecalculationofcollisionriskisdonefollowingthebasicprinciplediscussedintheprevioussection.ThecausationfactorisderivedbyusingBayesiannetworksandhistoricalaccidentdataasexplained.Becausenoindividualvesselmovementsaresimulated,itisnotpossibletosimplycountthenumberofencounters.Thedeterminationofthisnumberisthereforeofinterestinthesekindofmodels.Thisisdonebyusingtwoassumptionsmentionedbefore.(Friis-HansenandSimonsen,2001)

1. Vesselssailaccordingtoanassumedorpre-specifiedspatialdistributionofthevesseltraffic overthewaterway;

2. Vesselsarenavigatingblindlywhentheseareoperatingattheconsideredwaterway.

6 MaritimeResearchInstituteNetherlands

Page-17-


Afterthedistributionsoverthedifferentwaterwayshavebeenspecified,itispossibletocalculatethenumberofencounters.Thisisdonebydefiningariskarea,wherevesselscanpotentiallyencountereachother(seeFigure3.4).Subsequently,thenumberofencountersiscalculated,usingthedimensions,speedsandthespatialdistributionoverthewaterways.Thisisdoneforallcombinationsofdifferentvesselclasses.

Figure 3.4 Crossing waterways with risk area of ship-ship collision. f (z)= vessel distribution over the waterway, different vessel classes are

denoted by i and j; z = distance to the centreline of the waterway; V = velocity of vessel; θ = angle between the waterways 1 and 2. Source: Pedersen et al. (1999), p. 4, figure 2.1 (Pedersen and Zhang, 1999)

Theexactcalculationisnottreatedhere,becausethemainfocusofthisthesisliesonmodelsthatdosimu-lateindividualvesselmovements.

3.3 Type II: Maritime Traffic Simulation Programs

Themaindifferencebetweenthegeometricmodelandmaritimetrafficsimulationprograms(MTSPs)issimulationofvesselmovements.InMTSPsthenumberofencountersiscalculatedbycountingthenumberofencountersthathappeninasimulationrun.Theoutputofasimulationrunisnotonlyanumberofencounters,butmakesitalsopossibletotakeacloserlookattheencountersituation.Thisleadstoabet-terinsightintothedifferentcausesofanencounter.Thiscanbevaluableinevaluatingtheefficiencyof,forexample,infrastructuralimprovements.

AnotheradvantageisthatthenumberofencountersiscalculatedmorepreciselybyMTSPsthanbythegeometricmodels.Thisisduetothefactthatvesselsareabletomanoeuvreinordertopreventencounters,whereasthisisnotpossibleinthegeometricmodels.Theaccuracyofthecalculationdependsonthequal-ityofthevesselsimulation.TheimprovementofthissimulationisoneofthemaintargetsforMTSPs.

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Maritimemodelling

Mostsimulationprogramsusesimplerulestosimulatevesselbehaviour.Themostimportantrulesforves-selbehaviourfollowfromtheinternationallyrecognisedCollisionRegulations(COLREGs)7.Theseregula-tionsprescribethesupposedvesselbehaviour,especiallyregardingtheinteractionwithothervessels.

TheCOLREGsgiveagoodfirstindicationofvesselbehaviour,buttwolimitationscomeup.First,theseregulationsonlygivegeneralguidelineshowvesselsshouldbehave.Nodetailedinformationconcerningtheprecisepathofavesselanditsinteractionwithothervesselsisgiven.Secondly,vesselsdonotalwaysobeytheCOLREGs.Sometimestheydeviatefromtheseguidelinesforsomereason.

So,tosimulatevesselbehaviourinamoredetailedway,additionalrulesandguidelinesshouldbeformu-lated.Itisnotveryeasytodoso,becausethevesselbehaviourgreatlydependsonthedecisionsthataremadebythehumansthatcontrolthevessel.Theirdecisionsarebasedonknowledge,experienceandcapabilities,whicharedifferentforeveryone:thehumanfactor.Neverthelessseveralmethodstodescribevesselbehaviourcanbedistinguishednowadays:fuzzylogic,rulesbasedonexpertknowledge,andBaye-siannetworks.

Fuzzylogicisamathematicaltechniquethatisusedinmodelsforthedeterminationofthehumanbehav-iour.“Infuzzylogicmodelling,largeamountsofinputdataareprocessedaccordingtovarious‘If-Then’rules,similartothosethatoccurinthehumanbrain.Weightingandaveragingoftheresultingoutputsthenleadstoasingleoutputsignal.Thisabilityoftakinginandevaluatinglargeamountsofdata,leadingtoadecisiononhowtoactiswhatmakesfuzzylogicmodellingsosuitableformodellinghumanbehaviour.”(Pimontel,2007,p.10).Nowadays,thesimulationprogramsDYMITRIusesfuzzytechnologytosimulatethehumanelement(Bolt,2006).

AnotherwayofsimulatingthehumanelementisbyusingBayesiannetworks.BarauskisandFriis-Hansen(2007)usedynamicBayesiannetworksforthemodellingofvesselbehaviourintheirmodel,calledthenumericalnavigator.Anadvantageofusingthosenetworksisthepossibilityofhavingincompleteinforma-tion.Inthenumericalnavigatormodelthevesselsarereflectedbyagents.Thoseagentshavetheabilitytointeract,anticipateandlearn.Tomodelandtotraintheagents,COLREGS’sandAISdataanalysesareused.ThepossibilitytouseAISdatainmaritimesimulationishandledinchapter4.

Athirdoptiontogetmoreinsightintovesselbehaviouristheuseofsimplelogicalrules.Theserulesareestablishedbyusingexpertknowledge.Ininterviewsseveralcaptainsgiveanoverviewoftheirbehaviourindifferentpresentedsituations.Fromthisknowledgegenericrulesthatdescribevesselbehaviourarederived.Bydoingso,itisnotneededtosimulatethehumanbrain.Thisproblemisbypassed,becauseitisalreadyincludedbytheobtainedrules.SIMDASisanexampleofamodelthatworkslikethis.

ChauvinandLardjane(2008)didsomeresearchonvesselmovementsandinteractionaswell.ByusingtheRPD(Recognition-Primed-Decision)modelofKlein8theyinvestigatedtheinteractionbetweenvesselsintheDoverStrait.Theycomeupwithsomeconclusionregardingcollisionavoidancebehaviour.Anexampleisatwhatdistancefromeachothervesselsstarttochangecoursetopreventanaccident.TheirvesseltrackdatawerebasedonmotionsobservedbyaVTS.

7 InternationalMaritimeOrganization,IMO,

http://www.imo.org/conventions/contents.asp?doc_id=649&topic_id=257,accessed:10/3/2010

8 GaryA.Klein,ARecognition-PrimedDecision(RPD)ModelofRapidDecisionMaking,

http://www.ise.ncsu.edu/nsf_itr/794B/papers/Klein_1989_AMMSR_RPDM.pdf,accessed:8/1/2010

Page-19-


3.4 Use of AIS in models

SincetheintroductionofAIS,studieshavebeenperformedonthereliabilityofAISdata,forexamplebyHarati-Mokhtarietal.(2007).Nevertheless,AISdataarealreadyusedinmanyresearchesconcerningmari-timemodels.Mostlytodeterminethenauticaltrafficdemand,animportantinputintheseprograms.AIScanhoweveralsobeusedtoanalysevesselmovements,assuggestedbyBarauskisandFriis-Hansen(2007).

3.4.1 Traffic input

InMTSPsitisveryimportantthatthetrafficdemandisassumedasrealisticaspossible.Athoroughanalysisshouldbedoneaboutvesseltype,size,destination,interarrivaldistribution,etc.AnAISmessagecontainsallthisinformationandisthereforeveryvaluabletogeneratethisinput.Alotofriskassessmentsnowadaysthereforeusethesedata,buttheyoftenalsomentionlimitations.ForexampleVanderTak(2009)usesotherdatasourcesthanAIStoobtaininformationaboutthedensityoffishingvessels.BothKujalaetal.(2009)andYlitalo(2009)mentionthelackofAISdatafromfishingvesselsaswellaspleasureboats,whichmakesitmoredifficulttoderivegoodaccidentrisks.

MoststudiesusingAISdata,investigatesafetyattheopensea.TherearefarlesssurveysconcerningportsorinlandwaterwaysthatuseAISdata.Thisiseasytounderstandfromthefactthatalotofsmallervessels(mainlyinlandvessels)donotcarryAISequipment.ForexampleIperenandKoldenhof(2008)useradardatafortheirriskassessmentstudyintheportofRotterdamarea.However,AISdataareusedinaresearchintheportarea‘Eemshaven’fortheriskassessmentofLNGvessels.Thisisonlypossiblebecausetheves-selsthatdonotcarryAISaretoosmalltodamageanLNGvessel(KoldenhofandVanderTak,2007).

AISdatacanalsobeusedtoimproveroutemodelling.Thehugeamountofavailabledata,especiallyregard-ingthepositionsofvessels,makesitpossibletogetabetterinsightintotheroutesvesselstake.VanDorpandMerrick(2009)usethispossibilityandexplainhowtheydealwitherrorsandinaccuraciesinthedata.Althoughthisimprovesthemodellingofthemaritimenetwork,itdoesnotgivemoreinformationregardingtheexactvesselbehaviour(e.g.theinteractionwitheachother).

3.4.2 Vessel movement and interaction

WithAISdata,theexactposition,headingandspeedofavesselareknownatalmosteverymoment.Thismakesittheoreticallypossibletodostatisticalanalysesonvesselbehaviour.Themostimportantcharac-teristicofthismethodisthatitdoesnottrytosimulatehumanbehaviour,becausethevesselbehaviourisalreadyknownfromtheAISdataanalysis.

DifferenterrorsthatoccurinthemessagesareaproblemwhenusingAISdataforthemodellingofvesselbehaviour.Assaidinchapter2,mosterrorsconcerntheDestination,ETA,Draught,VesselTypeandNaviga-tionalStatus.Forthemodellingofvesselbehaviourthemostimportantinformationregardsposition,speedandheading.Thesefieldscontainfewererrors.However,itmustbesaidthatinformationlikedestinationandnavigationalstatuscanmakethemappingofthenauticaltrafficmucheasier.

Oneofthemodelsthattrytoimprovethemodellingofvesselmovementsisthenumericalnavigator.BarauskisandFriis-Hansen(2007,p.5)concludethat‘StudieswillalsobeinitiatedthatbyuseofobservedAIStracksshalladjustandvalidatethewaythenumericalnavigatoroperatesthevesseltrafficinanarea’.ByadjustingtheBayesiannetworksthatdescribevesselbehaviour,theywanttotrainvessels(‘agents’)withtheresultsofAISdataanalyses.Sofarnoevidencehasbeenfoundifthisisalreadydone.

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AlsoMouetal.(2010)useAISdata,tostatisticallyanalysevesselbehaviour.ThefocusoftheauthorsisonthecorrelationoftheClosestPointofApproach(CPA)withvesselsize,speedandcourse.Fortheassess-mentofrisks,theyuseadynamicmethodbasedonSAMSON(seesection3.5forexplanationofthismari-timemodel).

3.4.3 Conclusions

AISdataarepotentiallyaveryinterestingsourceofinformationformaritimemodels.Nowadaysitismainlyusedinmaritimemodellingforthederivationofthetrafficinput,suchasinter-arrivaltime.AISdataisalsousedtogetabetterinsightintothenauticalnetworkthathastobemodelled.Inrestrictedwaterways,likeports,lessuseismadeofthedata.ThiswillbemainlyduetothefactthatintheseareasalotofvesselsarepresentthatarenotAISequipped.

ThereisaclearpotentialtouseAISdatatoobtainmoredetailedinsightinvesselbehaviour.ErrorsinAISdatamainlyoccurinfieldsthatareuseful,butnotindispensibleforthispurpose.ThereforetheycanmaketherequiredAISanalysismoredifficult,butcertainlynotimpossible.Noextensiveuseismadeofthispos-sibilityhoweversofar.Thereareplanstoincludeitinthenumericalnavigatormodel,butthestatusofthismodelisunsure.

3.5 Existing maritime models

Oneofthegoalsofthisthesisistoseeifstatisticalequationsthatdescribevesselbehaviour,canbeim-plementedincurrentlyexistingmaritimemodels.Thissectiongivesanoverviewofdifferentmodelsthatexistnowadays.Fourofthemareelaboratedabitmoreintodetail:SAMSON,HarbourSim,MARTRAMandDymitri.

Thesemodelsarechosen,becausetheygiveagoodinsightintherangeofmodelsthatisusedatthemo-ment.SAMSONclearlyisatypeImodel,thatdoesnotsimulate(individual)vesselmovements.Dymitriisattheothersideofthespectrum,asinthismodelthevesselsaresimulatedandhavealargefreedomtomanoeuvre.The4modelsarealsochosenbecausetheyare‘proventechnology’.Allofthemareworkingandhavebeenusedinseveralstudies.

3.5.1 Characteristics

ResultsoftheAISanalysisshouldincludeinformationconcerningthevesselpathandvesselspeed,butalsotheinfluenceofexternalinfluenceslikewindandcurrents.Besidesthis,itisalsotriedtoobtaininsightintheprocessofinteractionwhentwovesselsencountereachother.Oneoftheresearchquestionsistoseeiftheobtainedbehaviouralrulescanbeimplementedinacurrentlyexistingmodel.Thissectiondescribesthecharacteristicsthatareneededtodoso.

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Type1-Nauticalinfrastructure Describevesseldistributionoveracrosssectionoverthewaterway. Describethevesselspeeddistributionoverandinacrosssectionoverthewaterway. Type2-Vesselrelatedcharacteristics Distinguishbetweenstaticcharactericsasvesselsizeandvesseltype. Distinguishbetweendynamiccharacteristics,forexamplevesseldestination. Type3-Externalcircumstances Takeexternalinfluenceslikewind,currentandvisibilityintoaccount. Type4-Theinteractionwithothervessels Abilitytoincludedeviationfromthepredefinedpathandspeedbecauseofinteractionwithother vessels.

Thefirsttypeisimportantasthevesselswillhavea‘naturaldeviation’.Thismeansthattwovesselsthathaveexactlythesamecharacteristicsandarebothsubjecttothesameexternalinfluences,willnotchoosetesamerouteandspeed.Thisisforexampleduetointernalcircumstances,likethetraining,experienceandpreferencesofthecaptainsofthevessels.Thismeansthatmodels,iftheywanttoimplementthebehav-iouralrules,shouldnotfixatethevessellocationatonepointinthecrosssectionoverthewaterway.Alsoforthevesselspeeditshouldbepossibletodescribeanaturaldeviationfromtheaverage.

Thesecondtypehandlestheinfluenceofthevesselcharacteristics.Thevesselpathandspeedneedtohaveacertaindistributionoveracrosssectioninthewaterway,asexplainedabove.Thisshapeandlocationofthisdistributionmighthoweververywellbedependentonthevesselcharacteristics.Amodelshouldthereforebeabletomakeadivisioninvesselclasses.Theseclassesshouldincludevesselandvesselspeeddistributionsoveracrosssectioninthewaterway,differentforeachvesselclass.

Thethirdtypeindicatesthatexternalinfluencesshouldbetakenintoaccount.Thisiscanbedonesimilarlyasthetypehandledabove.Externalinfluencescanalterthevesselpathandspeedandamodelshouldbeabletocopewiththosechanges.Differentfromtypetwoisthatthisonedoesnotdescribetheaverage,generalbehaviourofacertainvesselclass.Incontrary,externalinfluencescansometimesleadtoverydi-vergentvesselpathandvesselspeed.Althoughonlyalimitednumberofvesseltrackswillbethatdifferent,itisimportantforamodeltobeabletodescribethem.

Thelasttypeconcernstheinteractionbetweenvessels.Thisisthemostcomplicatedissue,asthisimpliesadeviationfromthepredefinedvesselpathandvesselspeed.Vesselclassesand-toalesserextent-externalinfluencesareconstantduringtheexaminationofacertainvesseltrack.Interactionwithothervesselsiscompletelyincontrastwiththis,asitcanhappenatalmostanypointintimeandspace.Nexttothis,therearealotofdifferentmannersinwhichaninteractioninfluencesthepathandspeedofthevesselsinvolved.Thisdependsforexampleonthetypeofinteraction(e.g.head-on,overtaking),thetypeandsizeofvesselsinvolvedandthelocationonthewaterway.Tosimulatetheinteractionsufficiently,vesselsshouldhavealotoffreedomtomanoeuvreanddeviatefromtheirpathandspeed.

3.5.2 SAMSON

SAMSONisamodelfortheriskassesmentofnauticaltransportatsea.Itevaluatestheriskeffectsofchang-esinforexampleshippingroutesandoffshoreconstructions.Themodeldividesthevesselaccidentsthatareconsideredintodifferenttypes,forexamplecollisions,fireandstranded.SAMSONisaTypeImodel,inwhichthecausationfactor(whichiscalledthecasualtyrateinSAMSON)isbasedonhistoricaldata.Thismeansthatitdoesnotsimulatenauticaltraffic.Themodelfocussesonthecalculationofrisksatsea,butby

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adjustingthecasualtyratealsoportareascanbeexamined.(Bolt,2006)

SAMSONistestedtothe4typesmentionedintheprevioussection.Thecharacteristicsoftype1arepartlymetbythemodel.Thevesseldistributionoverthewaterwayisclearlyincluded.ThiscanbeseenfromFigure3.4,whichisanexampleofhowthistypeofmodelsdeterminesthecollisionrisk.Itisclearthatthedistributionoverthewaterwayistakenintoaccount.Alsothevesselspeedisincluded;withasmalladjust-mentthedistributionofthevesselspeedoveracrosssectioninthewaterwayisimplementedaswell.

Theinfluenceofthevesselcharacteristicsisalsopresentinthemodel,asdifferentvesselclassesaredis-tinguished.Thedistributionoverthewaterwayisalsodifferentfortheseveralvesselclasses.Theexternalinfluencesarealsotakenintoaccount.Itishoweverdifficulttoincludetheinfluenceofsomesituationswithextremeexternalcircumstances,asSAMSONisnotmeantfortheinvestigationofindividualvesselbehav-iour.Asimilarproblemariseswhenlookingatthepossibilitytomodelinteraction.SAMSONisnotasimula-tionprogramandthereforeitisnotpossibletoincludeadetaileddescriptionoftheinteractionbetweenvessels.

3.5.3 Harboursim

HarboursimisasimulationmodelusedbytheTUDelft,mainlytodeterminewaitingtimes.Themodelfocussesonportareasanddescribesthenauticalinfrastructurebyfixatedwaterways.Somecharacteristicsareassignedtothesenauticallanes,forexamplethenumberofvesselsthatcansailinonelaneatthesamemoment.Themodelalsoincludestheservicetimeofvessels,whichmakesitpossibletoderivecapacityandwaitingtimes.

InHarbourSim,thevesselssailinacertainlaneanddonotdeviatefromthis.Insidethelanetherearealsonodifferentpathsavesselcantake.Thereisalsono‘naturaldeviation’invesselspeed.Theissuefromtype1arethereforenotdealtwithatthemoment.Itmighthoweverbepossibletoincludethisinthemodel,bycalculatingvesselpathsforeveryvesselthatiscreated.Thesepathscanthenbemadedependendonthevesseldistributionoverthewaterway.Thesamecanbedoneforthevesselspeed.Thisishoweveramajormutationofthemodel.

Thesecondtypeispartlymet.Thereisacleardistinctioninvesselclassesinthemodel,butthisdistinc-tionismainlyusedforthedifferenceinservicetimeanddestination.Thisisverylogical,asthegoalofthisprogramistocalculatewaitingtimes.If,followingfromissueone,individualvesselpathsareincludedinthemodel,itshouldnotbetoocomplicatedtoincludetheinfluencesofvesselclassdifferencesaswell.Thesameistrueforissuethree,whichcanpotentiallybeimplemented.

Theinteractionwithothervesselsishandledinthecurrentmodel,butinaverylimitedway.Itconsistsofbehaviouralruleswhetheravesselcanenteracertainwaterwaysegment.Thisdependsonthepresenceofothervesselsinthissegmentandthemaximalpermissiblenumberofvesselsinthatspecificsegment.Itdoesnotincludeanydeviationsfromthevesselpath.Toincludethis,averylargemutationofthemodelshouldbemade.

3.5.4 MARTRAM

MARTRAM(MarineTrafficRiskAssessmentModel)isdevelopedandusedbyRoyalHaskoningforaswellriskassesmentsascapacitystudies.Itcansimulatenauticaltrafficindifferentareas,inwhichforeverynewareathenauticalinfrastructureshouldbeimplementedinthemodel.Theconstructionoftheinfrastructure

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inthemodelcanbedonebyaddingnodesandconnectingsegments.Duringasimulationrunthenumberofencountersiscounted,whichisameasureforthenauticalsafety.

MARTRAMdoesincludeadistributionoverthewaterway.Everyvesselsmaintainsafixeddistancefromthecenterlineofthenavigationchannel.Thisdistanceisrandomlypickedfromanassumeddistributionofthevesselsoverthewaterway.Alsothevesselspeedhassomevariation,asthemodelkeeps10%variationaroundaninsertedvalue.Themodeldoesthereforecertainlykeepupwiththerequirementsoftype1.

Thecharacteristicsofissue2areclearlymetaswell,asdifferentvesseltypesaredistinguishedinMAR-TRAM.Forthesevessels,thecharacteristicdimensions,speedandvesselsafetydomaincanbeset.So,acleardistinctioninvesselclassesismade.Itishoweverunsureifthisclassesalsohavedifferentdistributionsoverthewaterway,whichshouldbeapossibilityinthemodel.Type3,theinfluenceofexternalcircum-stancesisnotincludedinthemodel.Becausethereisalreadyadistributionoverthewaterwayandadevia-tioninthevesselspeed,itshouldnotbealargesteptoincludethisinthemodel.

TheinteractionwithothervesselsistosomeextentpresentintheMARTRAMmodel.Ifavesselsdetectsan-othervesselinhis‘observationdomain’(whichis5-10%largerthanthesafetydomain),itmakesacollisionavoidancemanoeuvre.Thisconsistsofaspeedreduction,whileitmaintainsitscourse(Pimontel,2007).Thisisnotenoughtogiveadetailedinsightinrealvesselbehaviourduringaninteraction.Itishoweveragoodstartingpoint;mostimportantadditionisthepossibilitytodeviatefromthepredefinedpath.

3.5.5 Dymitri

Dymitri,ownedbyBritishMaritimeTechnologylimited,simulatesthenauticaltrafficwiththemaingoaltoindentifycollisionandgroudingrisk.Themodelisbasedonanautonomousagentsimulationofthemarimetraffic.Alsothehumanelementismodelled,byusing(Fuzzy)technologythatsimulatesthehumanbrain.Thevesselshavealargefreedomtomanoeuvre.Theincidentriskisbasedonthenumberandnatureofavoidanceactionsthathavebeenundertakenduringthesimulationrun.

Themodelcomplieswithtypeone,asthereisalotoffreedomtomanoeuvreforvesselsinthemodel.Dymitriishowevernotbasedonspecificvesseldistributionsoverthewaterway,butontheindividualbe-haviourofvessels.Thisbehaviourisbasedonthesimulateddecisionsmadebythevessel’sfirstmate.Thisisadifferentapproachthanthestatisticalwhichisusedinthisthesis.Thereishowevernodoubtthatthevesselsdohavesomedistributionoverthewaterway.

InDymitriitispossibletosetdifferentshiptypesandsizeclasses.Alsoexternalinfluencescanbeincluded.Boththevesselsclassesandtheexternalcircumstancesinfluencethewayinwhichthevessels(theautono-mousagents)sail.Types2and3arethereforeclearlymetbythemodel.TheinteractionbetweenvesselsisalsosimulatedbyDymitri.Thedistanceatwhichtheinteractionstartsisfoundfrommarinerreviewsanddigitalradarassessment.TheinteractionitselfisdrivenbytheFuzzylogicthatdeterminesthemarinersdecisions(Bolt,2006).

3.5.6 ConclusionMaritimemodellingprogramscanbedividedintwogroups:Geometricmodelsandthemaritimetrafficsimulationprograms.Thegeometricmodelisananalyticalcalculation,whichusesgeometricdistributionsoverthewaterwaystoderivenauticalsafety.MTSPssimulatetheindividualvesselsandtheirbehaviour,todifferentextents.Insomesimulationprogramsvesselsfollowpredefinedtracksandarebarelyallowedtochangespeedorcourseinordertopreventcollisions.

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Maritimemodelling

Othersimulationprogramstrytosimulatethevesselbehaviourmoreindetail.Itishoweververydifficulttodoso,becausethisbehaviourdependsgreatlyonthedecisionshumansmake,thehumanfactor.Thereareseveralpossibilitiespresenttodealwiththis.Somesolutionsaimtosimulatethehumanbrain.Thisismain-lydonebyfuzzytechnologyand-toalesserextent-byBayesiannetworks.Othersolutionstrytobypasstheproblemofsimulatingthehumanfactor,byderivingsimpleruleswhere,inpractice,mostvesselsobeyto.

InbothtypesofmaritimemodelsAISisused,butinaverylimitedway.IfAISisused,themainpurposeisthederivationoftrafficinputortoincreasetheunderstandingoflargertrafficpatterns.Atthemoment,someattemptsaremadetouseAISfortheanalysisofindividualvesselbehaviour,butnoclearresultsofthisareyetfound.

Casestudysetup

Chapter4

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4 Case study set up

Thischapterexplainsthesetupofthecasestudydoneinthismasterthesis.Theaimofthisstudyistoob-tainmoreinsightintothevesselpathandvesselspeedandhowthisisinfluencedbydifferentfactors.Intheend,theresultsaregeneralised:genericrulesareformulatedtodescribevesselbehaviourinaportarea.Inthischapter,itisexplainedhowthechoiceforthisspecificlocationwasmadeandwhatthelocalcharacter-isticsare.

4.1 Approach case study

Thegoalofthecasestudyistodescribetheexactpathvesselstakeandtheircorrespondingspeed.Theresultsshouldbeformulatedinsuchaway,thattheyaregeneralapplicableandcanbeusedasinputforamaritimemodel.Thereforethecasestudyaimstoderivegeneralrulesregardingvesselpathandves-selspeed.Itisimportantthattheobtainedsetofrulesissufficienttoreliablydescribeavessel’spathandspeedinamaritimemodel.Todoso,thedifferentrulesshouldcomplywiththefollowingissues:

1. Describethespatialdistributionofvesselsinacertaincrosssection;2. Describethelateralvesselspeeddistributionofvesselsinacertaincrosssection;3. Describethevesselspeeddistributiononacertainlocation;4. Takeintoaccountthatthe3distributionsmentionedabovedependon:

a. Vesseltype;b. Vesselsize;c. Vesselheading/destination;d. Typeofwaterwaysegment(straight/bend)e. Widthofthe(forthatspecificvesseltypeandsize)navigablewaterway;f. Windspeedandwinddirection;g. Currentspeedandcurrentdirection;h. Visibility;i. otherexternalinfluences;j. Interactionwithothervessels.

5. Describethemutualdependencebetweentwospatialsuccessivedistributions(toconnectthedifferentcrosssections,inordertoassembleanindividualvesselpathandcorrectspeeddevelopment)

Itcanbeseenfromthelistthattherulesdonottrytodescribedecisionsmadebypeoplethataresteeringtheindividualvessels.Byapplyingstatisticallyderiveddistributionsthisisbypassed;onlytheresults of this behaviourareformulated.Inthiscasestudynotthecompletelistofissuesmentionedaboveishandledfully.First,onlycontainervesselsareinvestigatedasavesseltype.Thisisbecauseonlythistypeofvesselsvisitsthelocationchoseninthecasestudy(see4.2).Second,nootherexternalinfluences(e.g.waves,rain)areinvestigated.Thisisbecause-inaportarea-thoseinfluencesareassumedtohaveasmallinfluenceonthevesselpathandspeedcomparedtotheotherexternalinfluences(wind,currentandvisibility).Third,theinteractionbetweenvesselsisnothandledinthisthesis.Theresultsfromthecasestudycanhoweverbeusedtoinvestigatetheinteraction.Anillustrativeexampleofthisisgiveninsection9.

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4.2 Location

Inthecasestudy,itistriedtoderivethegeneralrulesasdescribedintheprevioussection.Thereforethelocationshouldcomplywithsomeconditionsfollowingfromtheissueslistedbefore.Atfirst,enoughdatamustbeavailabletoderivethecrosssectionsmentioned(issues1-3).ThismeansthatthelargemajorityofthenauticaltrafficthatvisitsthechosenportlocationshouldbeequippedwithAIS.Nexttothis,thetrafficimageshouldnotbetoomuchdisturbedbyvesselsthatdonotcarryAIS(e.g.inlandvessels).Anotherpointofinterestistherequiredvarietyinvesselsize,tohandleis-sue4.b.Differenttypesofwaterwaysegmentsshouldbepresentinthepathtowardstheterminalaswell(issue4.d).Itisalsopreferablethatalotofinteractionbetweenvesselsistobeexpectedonthispath(issue4.j).

Afterdeliberatingtheseconditions,theAmazonehavenischosenasthecaselocation.Figure4.1andFigure4.2showthelocationoftheAmazonehavenintheportofRotterdam,atthe'MaasvlakteI'.ThevesselpathsthatwillbeinvestigatedarethetracksfromNorthSeatotheAmazonehavenandtheotherwayaround.Below,thisiselaboratedmoreintodetail,togetherwithamoreintodepthexplanationwhythislocationsuitsthepredefinedconditions.

WhenvesselscomingfromtheNorthSeavisittheAmazonehaven,theycrossseveralinterestinglocationswhereinterestingvesselbehaviourmightbeexpected.ShortlybeforeenteringtheportofRotterdamintheMaasmond,apilotembarksmostvessels(1).AfterthisthevesselscometosailbetweenthenorthernbreakwaterandtheMaasvlakteI(2).Theseofferprotectionfromcurrentsandwavesandvesselswillhavetoadjusttheirbehaviourtothechangedexternalinfluences.

Figure 4.1 Overview of the port of Rotterdam, the Maasvlakte I is indicated by the red circle; source: Google Earth

Figure 4.2 Overview of Maasvlakte I, the Amazonehaven is indicated by a red ellipse;

source: Google Earth

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Every(seagoing)vesselthatvisitstheportofRotterdameventuallyhastosailthroughtheMaasmond(3).Thereforethisisabusywaterwayinwhichitislikelythatvesselshavequitesomeinteractionwitheachother.Thisisalsotheplacewheretugsfastentomost(bigger)containervessels,aprocessthatcaninflu-encevesselcourseandspeed.AftertheMaasmond,thevesselsheadingfortheAmazonehaventakeaturnintotheBeerkanaal(4).Inthisbendquitesomeinteractionscanoccur,becausethereisalotof(sometimes

Figure 4.3 Plot of the vessel tracks at the entrance of the Beerkanaal on 14 July 2009, between 10:00 and 16:00 hours.

Figure 4.4 Plot of the vessel tracks at the entrance of the Amazonehaven (indicated by the red ellipse) on 14 July 2009, between 10:00

and 16:00 hours.

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crossing)nauticaltrafficpresent.SeeFigure4.3foratrafficimageatthislocation.

IntheBeerkanaal(5)andattheentranceoftheAmazonehaven(6)thenauticaltrafficintensityislowerthanintheareasmentionedbefore.TherearehoweverstillalotofvesselsthatvisitoneoftheterminalsatMaasvlakteI,orareaimingforthe‘Hartelkanaal’.Interactionwillthereforealsooccurhere,forexampleduringaturningmanoeuvreofalargevessel-tugscombinationinfrontoftheAmazonehaven.Figure4.4showsanimageofthenauticaltrafficatthislocation.

Asdescribedabove,thereareseveralreasonswhythevesseltrajectoriestowardsandawayfromtheAma-zonehavenareinterestingintheanalysisofvesselbehaviour.Nexttothepathvesselstake,alsothevarietyinsizeofthevesselsthatvisitthiscontainerterminalisagoodreason.Alotoflargecontainervesselsvisitthisterminal,becauseitiseasytoreachandtheAmazonehavenoffersenoughdepthfordeepdraughtves-sels.Firstofall,thisisinterestingbecauseinthiswaythebehaviourofthelargestcontainervesselscanbeinvestigated.Itisverylikelytheyreactdifferentone.g.highwindorcurrentsthansmallervessels.

Nexttothis,theselargevesselsonlyvisittheterminalintheAmazonehaven,afterwhichtheycontinuetheirjourneyontheNorthSea.Theseareexactlythetracksthatareinvestigatedinthiscasestudy.SmallercontainervesselsmostlyvisitalsoothercontainerterminalsintheportofRotterdam,tracksthatareonlyconfusingandnotexaminedinthisstudy.

AnotheradvantageoftheAmazonehavenisthatitislocatedatthemostWesternpartoftheport,awayfromthecitycentreandthesmallerterminals.Thisisadvantageousbecausethesmallerterminalsareoftenvisitedbyinlandvessels.Asmentionedbefore(chapter2)mostofthesevesselsdonottransmitAISmessag-esnowadays.ThereforethesevesselscannotbeseenwhenlookingpurelyatAISdata.Sowhensuchaves-selinteractswithanAISequippedvessel,thismakesitdifficulttoexplainthebehaviouroftheAISequippedvessel.Thisproblemcouldtheoreticallybeovercomebyusingradarimages,butitismuchmorepracticaltochooseanareawerelessinteractionwithinlandvesselsistobeexpected.

MostoftheadvantagesmentionedbeforedoalsoapplyforthedrybulkterminalthatispresentintheMis-sissippihaven(7).VesselsvisitingthisterminaldofollowlargelythesamerouteasthevesselsthatvisittheAmazonehaven.Thesedrybulkvesselsarealsoingeneralverylarge.Thisterminalishowevernotchosen,becausethenumberofvesselsthatvisititismuchlowerthanforthecontainerterminal.Thismakesitmoredifficulttomakestatisticalsignificantcalculations.Besides,drybulkvessels(especiallyverylargeones)arelesspresentinportsallovertheworldthancontainervessels.Itisthereforemorebeneficialtoformulategenericrulesforcontainervesselsthanfordrybulkvessels.

TheconsiderationsmentionedabovehaveledtothechoicetolookatthecontainerterminalintheAma-zonehaven.Thismakesitpossibletoderiveinsightinthebehaviourofcontainervesselsofdifferentsizeclasses.Duetothelargerangeinsizeclassesalsothedifferentinfluencesofwind,currentsandvisibilitycanbegivenacloserlook.

4.3 Case study outline

Theselectedtracks(fromvesselsthatvisittheAmazonehaven)arefurtheranalysedandinformationregard-ingvesselbehaviourisobtainedfromthisanalysis.First,thevesselsaremappedintodifferentvesselsizeclasses.Foreachoftheseclassestheaveragepathisdetermined,foraswellincomingasoutgoingvessels(section5.3).Theaveragevesselspeedisobtainedforeverysizeclassaswell.Alsothespatialdistributionofvesselsoverthewaterwayiscalculatedforseveralcrosssectionsovertheinvestigatedwaterway.Attention

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Casestudysetup

ispaidtothevesselspeedaswell,byderivingthespeeddistributionsoncertainlocationsontheaveragepath(Section5.4).

Withtheaveragepathandcorrespondingspatialandspeeddistributionsknown,attentionispaidtothefactorsthatinfluencetheseresults.Severalfactorsareinvestigated:wind,currents,visibilityandtheinter-actionwithothervessels.First,theinfluenceoftheinteractionwithothervesselsisleftoutofconsidera-tion.Severaltracksofvesselsthatweresailingduringhighwinds,currentsorlowvisibilityarecomparedtotheaveragepathofvesselsfromthesamesizeclass(Chapter6).Tomaptheinfluenceofvessel-vesselinteractionanexampleofasituationinwhichinteractionoccurredisexamined(chapter7).

Blue: < 8 AIS messagesYellow: 8-13Red: 14-30Black: >30

Average vesselpathandspeed

Chapter5

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Averagevesselpathandspeed

5 Average vessel path and speed

Inthischaptertheaveragevesselbehaviourisdetermined.First,thedatasetsusedforthisaredescribed(section5.1)andtheirqualityischecked(section5.2).Insection5.3theinfluenceofthevesselsizeontheaveragepathandvesselspeedisinvestigated.Insection5.4thespatialdistributionofvesselsindifferentcrosssectionsiselaborated.Thissectionalsotreatsthevesselspeeddistributioninthesecrosssections.

5.1 Data sets

WiththeuseoftheprogramShowRoute9aselectionofAISmessagesismade.TheselectionissetupbythemessagesofcontainervesselsthatvisitedthecontainerterminalintheAmazonehaveninFebruary,March,April,July,August,October,NovemberorDecember2009.Thesemonthsarechosentogetinformationfromdifferentseasons.Finally,atotalof4,105,821uniqueAISmessagesisderived.Thesearehoweverrawdata;differentimprovementshavetobemadebeforethedatacanbeanalysed.

ThemostimportantoperationistheremovaloftracksotherthanbetweenNorthSeaandAmazonehaven.Especiallysmallercontainervesselscausethesedisturbingtracks,becausetheyvisitdifferentterminalsintheportofRotterdam.Nexttotheremovaloftracks,twootheradjustmentsaremade.Thefirstonecon-cernsthetransformationofgeographicalcoordinatestoRijksdriehoeksgridcoordinates.TheRijksdriehoeks-grid(RD)isthenationalgridoftheNetherlands.Itisusedasabasisforgeographicalindicationsandfiles,likeGeographicInformationSystems.AlsotheportofRotterdamsinfrastructureisexpressedinRDcoordi-nates.So,toevaluateavesselspositioncomparedtotheportsinfrastructureitisneededtorecalculatethegeographicalcoordinatestoRDcoordinates.

Thesecondadjustmentisarecalculationofthevesselsposition,bytakingintoaccounttheexactantennapositiononthevessel.ThepositionofthevesselthatisshownintheAISmessagereflectsthepositionofthetransmittingantenna.Thisantennamostlyisnotpositionedinthemiddleofthevessel;thereforearecalculationisneededtoretrievethecorrectpositioncoordinatesofthevessel.Thepositioncoordinatesthatarefinallyderivedreflectthemiddleofthevessel.TheoperationsareexecutedbyaMatlabmodel,whichisexplainedindetailinAppendixD.

AftertheadjustmentstotherawAISdata,805differentincomingtracks(NorthSeatoAmazonehaven)and663outgoingtracks(AmazonehaventoNorthSea)areleft.Toinvestigatetheinfluenceofthevesselsize,thevesselsarecategorisedintofivesizeclasses:

1.Smallerthan10,000Deadweighttonnage(dwt).10

2.10,000–40,000dwt. 3.40,000–70,000dwt. 4.70,000–100,000dwt. 5.Largerthan100,000dwt.

9 ShowRouteisasoftwareprogram,ownedbyMarin,whichcanbeusedtomakeselectionsofAISdata.Itcan

alsoplotselectedAISmessages,whichmakesitpossibletoreplaysituations.Thisishelpfulinthejudgement

ofinteractionbetweenvesselsinchapter9.Itisalsopossibletocalculateothercharacteristics,likethe

ClosestPointofApproach(usedintheCPAanalysisinchapter9).

10 Deadweighttonnageisameasurehowmuchavesselcan(safely)carry.Itisthesumofthecargo,fuel,water,

provisions,passengersandcrew.

Page-33-


Thesizeclassesarechoseninsuchawaythatineverydatasetapproximatelythesameamountoftracksisavailable.Theonlyexceptiontothisisthesmallestsizeclass,inwhich2-3timesasmuchtracksarepresent.Thisisdoneonpurpose,becausethesmallestvesselshavealargerfreedomtomanoeuvre.Itisthereforeexpectedthatmoredataisneededbeforereliableandaccuratecalculationscanbemade.

Thenumberoftracksavailableineachofthe10differentdatasetsisshowninTable5.1

Table 5.1 Number of tracks in each dataset

SizeClass(dwt) Incoming Outgoing

<10,000 307 250

10,000-40,000 173 109

40,000-70,000 89 98

70,000-100,000 124 132

>100,000 112 119

5.2 Accuracy of the data sets

Thequestionarisesifthereareenoughdataineachdatasettocalculateareliableaveragevesselpathandspeed.Toanswerthisquestion,theaveragevesselpathandspeedarefirstcalculatedbyusingonly50%oftheavailabledata(thetracksusedforthisarechosenatrandom).Afterthis,thesamecalculationisdone,nowusing100%oftheavailabletracks.So,theamountofdatathatisusedisdoubled.Thetwoderivedav-eragesarecomparedwitheachother.Ifthereisnosignificantdifferencebetweenthem,apparentlyagoodapproximationoftheaveragevesselpathandspeedwasalreadygivenbyusingonly50%oftheavailabledata.Inthatcasetheconclusionisdrawnthatenoughdataareavailabletoobtainareliableresult.

5.2.1 Accuracy average track calculation

Theabovedescribedprocedureisperformedforeverydataset.ForthecalculationoftheaveragepaththesameMatlabmodelisusedasmentionedbefore(AppendixD).Inthismodelagridisapplied,withadistancebetweenthegridpoints(gridsize)of50meters.Thismeansthatevery50meterstheaveragelocationinacrosssectionoverthewaterwayofavesselwithinacertainsizeclassisdescribed.ThepathtowardstheAmazonehavenisinthiswaydescribedby234datapoints.Whencomparingtwoaveragepathswitheachother,thedifferenceateachgridpointisdetermined(Figure5.1).Itshouldhoweverberemarkedthatthesedifferencesarenotindependentfromeachother.Forexample,ahighvalueforΔnmakesitverylikelyalsoΔn-1andΔn+1havehighvalues,becausetheyarealllinkedtooneaveragepath.

Page-34-


Δyi-2

Path 1

Path 2

Δyi-1 Δyi Δyi+1Δyi+2

Δyi+3

Δyi+4

Figure 5.1 Calculation differences between average vessel paths.

Fromthe234differencesthatareobtained,themeanandstandarddeviationarecalculated,seeequation(5.1).Themeanvalueandstandarddeviationofthetotalofthesedifferencesareanindicationhowwellthetwovesselpathsmatch.Table5.2showsforthedifferentdatasetsthevaluesofthemeanandstandarddeviation.Anegativevalueforthemeanindicatesthatthepathbasedon50%ofthedatapointslies,onaverage,onthestarboardsideofthepaththatisbasedon100%ofthedatapoints.

(5.1)

n

ii 1

n 2ii 1

where n numberof tracks

1Mean y

n

1St.Dev. ( y ) ,

n

µ

µ

=

=

=

= = ∆

= ∆ −

∑

∑

Table 5.2 Comparison of the average tracks, calculated by respectively 50% and 100% of the data.


Mean(m) StDev(m) Mean(m) StDev(m)

<10,000 0.5 5.2 -5.2 4.8

10,000-40,000 0.6 9.6 1.1 8.7

40,000-70,000 2.8 5.7 8.4 7.8

70,000-100,000 3.0 6.2 -1.9 5.8

>100,000 -1.8 10.3 -3.2 4.8

Table5.2showsthatthemaximummeandifferencebetweenthecomparedaveragetracksis8.4meters.Themaximumstandarddeviationis10.3meters.Thesenumbersalonearehowevernotenoughtodrawclearconclusionsregardingtheaccuracyofthedatasets.Forthisacloserlookattheouterlimitsofthedif-ferencesisneeded.Bycalculatingconfidenceintervals11(cdf’s)thiscanbeachieved.

11 Aconfidenceintervalisthelikelihoodaparameterisincludedinacertainintervalinsideaprobabilitydistribu

tion.Theconfidencelimitsaretheendpointsoftheconfidenceinterval.Aconfidenceintervalisalwayspre

cededbyapercentage,theconfidencelevel,whichreflectsthelikelihood.

Page-35-


Todoso,itisneededtosetupcumulativedistributionfunctionsofthedifferences,foreverydataset.AnexampleofsuchafunctionisgiveninFigure5.2.

−20 −15 −10 −5 0 5 10 15 200

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Mean

X = Differences between two datasets (m)

P (X

)

95% lower limit 95% upper limit

Figure 5.2 The cumulative distribution function of the differences between two average tracks,

Vessel size class <10,000; outgoing.

Withthiscdf,itispossibletocalculatethe95%confidenceinterval.Thismeansthatthereisa95%likeli-hoodthatarandomchosendifferencebetweenthetwoaveragepathsiswithinthoselimits.Inthisthesis95%iskeptasathresholdvalueforthedeterminationoftheaccuracy12.TheresultsareshowninTable5.3.Fromthistableitcanbeconcludedthat-foreverysizeclass-itisfor95%certainthatthedifferencebe-tweentwoaveragetracksisintheinterval[-26;27].Thus,theaccuracythatcanbederivedbyusingonly50%oftheavailabledatais±30metersatleast.Inthecasestudy,alldataisusedanditisthereforeverylikelythattheaccuracyisevenhigher.

Table 5.3 The 95% confidence intervals in meters for the distance between two average tracks of one vessel size class.


<10,000 [-11;10] [-17;4]

10,000-40,000 [-26;12] [-16;18]

40,000-70,000 [-11;13] [-7;24]

70,000-100,000 [-6;18] [-14;7]

>100,000 [-15;27] [-15;5]

12 Whatconfidencelevelistakenasarepresentativevalueissubjectiveanddependsonthenatureofthestudy.

Mostcommonishowevertousea95%confidencelevel.

Page-36-


5.2.2 Accuracy average vessel speed calculation

Anotherimportantoutcomeofthecalculationoftheaveragetrackistheaveragespeed.Theaveragespeeddevelopsalongthevesselpath.Valuesforthisspeedarethereforecalculatedateverygridpoint(onceevery50meters).Thedifferencesarecomputedinthesamewayasdescribedabove.Table5.4showsthemeanandstandarddeviationofthedifferencesfortheseveralsizeclasses(incomingandoutgoing).Thedifferencesinvesselspeedaregiveninpercentages,tocopewiththefactthatthevesselspeedrangesfromalmostzerointheAmazonehaventoaround15knots13justoutsidethenorthernbreakwater.

Table 5.4 Comparison of the speed of the average tracks, calculated by respectively 50% and 100% of the data. The speed differences are reflected in percentages .

SizeClass(*1,000dwt)

Incoming Outgoing

Mean(%) Stand.Dev.(%) Mean(%) Stand.Dev.(%)

<10 -2.2 1.2 0.0 1.0

10-40 1.5 2.2 -1.0 1.8

40-70 1.7 2.1 -2.6 1.8

70-100 -2.6 1.7 0.0 2.1

>100 1.4 3.2 -0.7 1.0

Togetanindicationoftheaccuracythatcanbeobtainedinaveragespeedcalculations,the95%confidencelevelsarecalculated.Table5.5showstheresultsforthedifferentsizeclasses.Atthe95%confidencelevelthespeeddifferencesforalldatasetsareinthe[-6.2;6.3]interval,so±6.5%.At15knots,whichisaproxi-matelythefastestthatvesselssailintheobservedcasearea,thisisequaltoanaccuracyof±1.0knots.

Table 5.5 The 95% confidence intervals in percentages for the speed differ-ence between two average tracks of one vessel size class.


Incoming Outgoing

<10 [-6.2;-0.2] [-1.1;2.5]

10-40 [-3.1;5.5] [-4.8;3.8]

40-70 [-4.7;4.9] [-5.6;1.2]

70-100 [-5.4;0.6] [-2.2;6.3]

>100 [-6.1;4.9] [-3.4;0.5]

5.2.3 Conclusions

Theaccuracyoftheaveragepaththatiscalculatedisatleast±30meters.Theaccuracyofthevesselspeedis±6.5%.Bothvaluesarelowenoughtoconcludethatenoughdataisavailabletomakeareliableanalysisofthevesselpathandvesselspeed.Thederivedaccuraciesshouldhoweverbekeptinmindwhenevaluat-ingthosetwocharacteristics.

13 1knot=1nauticalmileperhour=1.852kilometerperhour=0.514meterspersecond.

Page-37-


5.3 The influence of vessel size

Toinvestigatetheinfluenceofvesselsize,theaveragetracksofthedifferentsizeclassesarecomparedwitheachother.Aswelltheaveragepaththatvesselstakeastheaccompanyingspeedisinvestigated.Thiscom-parisonisagaindonebycalculatingthemeanandstandarddeviationofthedifferencesbetweenthetwoaveragevesselpathsandvesselspeedsatthedifferentgridpoints(seeFigure5.1).Thegoalistoseeiftherearesignificantdifferencesbetweenthesizeclassesand,iftherearenot,whichsizeclassescanbebroughttogether.

InFigure5.3theaveragepathforoutgoingvesselsfromthesmallest(<10,000dwt)andthelargest(>100,000dwt)sizeclassareplotted.Itcanbeobservedthatthedifferencesbetweenthetwotrajectoriesincreaserapidlywhenthevesselshavelefttheprotectedportarea(PartA).Outsidethe(northern)break-waterthewaterwayismuchwiderandthesmallervessels(withasmallerdepth)arelessrestrictedanddeviatetothenorth.Insidetheprotectedportareatherearealsodifferencesbetweenthetwotracks,butthesearesmallerandlesssuitableforavisualinspection.AnexampleisintheBeerkanaal,wherethesmall-estvesselssailmoretotheeast.Nexttothis,thesevesselstakeasharpercurveintotheBeerkanaal,whentheyareleavingtheAmazonehaven.

TheabovedescribeddifferencesmakeitclearthatforadetaileddescriptionofthedifferencesitisneededtosplitthetrajectorybetweentheNorthSeaandtheAmazonehaveninseveralparts.Itisespeciallyworth-whiletolookseparatelyatthepartsoutside(PartA)andinsidetheprotectionofthebreakwater.

5.9 6 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.84.4

4.41

4.42

4.43

4.44

4.45

4.46

4.47

4.48

4.49

4.5

Part A

Figure 5.3 Average path for outgoing vessels, size classes <10,000 dwt (green) and >100,000 dwt (blue)

Page-38-


5.3.1 Influence on the average path

Tobeabletodrawvalidconclusions,aquantativeanalysisofthedifferencesismade.Theresults,thedif-ferencesbetweenthesizeclassesforbothincomingandoutgoingvessels,aresummarisedinTable5.6andTable5.7

Table 5.6 Comparison of the average tracks from different vessel size classes, for incoming vessels. A positive value for the mean indicates that the size class on that row sails more to the starboard

side of the vessel class in the column.


10-40 40-70 70-100 >100

Mean(m)St Dev (m)

Mean(m)St Dev (m)

Mean(m)St Dev (m)

Mean(m)St Dev (m)

<10 16 11 75 47 84 66 93 77

10-40 59 39 68 59 77 70

40-70 9 27 18 39

70-100 9 14

Table 5.7 Comparison of the average tracks from different vessel size classes, for outgoing vessels. A positive value for the mean indicates that the size class on that row sails more to the starboard

side of the vessel class in the column.


10-40 40-70 70-100 >100

Mean(m)St Dev (m)

Mean(m)St Dev (m)

Mean(m)St Dev (m)

Mean(m)St Dev (m)

<10 39 41 62 56 83 92 103 114

10-40 23 19 44 53 65 75

40-70 21 37 41 61

70-100 20 26

Itcanbeseenthatallmeandifferenceshaveapositivevalue.Thismeansthatthesizeclassontherowsailstothestarboardsideofthecorrespondingclassinthecolumn(whichisthelargestofthetwocomparedclasses).Toseewhetherthesizeclassesdiffersignificantlyfromeachother,theaccuracydeterminedintheprevioussectionisused:±30meters.Tocomparethedifferenceswiththisaccuracy,the95%confidenceintervalsarecalculated(Table5.8).

Itcanbeseenthatallconfidenceintervalsareoutsidethe[-30;30]accuracyinterval.Onlythecombina-tionof<10,000dwtand10,000-40,000dwtandthecombinationof70,000-100,000dwtand>100,000dwt,bothforincomingvessels,comeclosetotheaccuracyinterval.Sowhenlookingatthewholetrajectory,itcanbeconcludedthatallsizeclassesdiffersignificantlyfromeachotherconcerningthepaththeychoose.

Page-39-


Table 5.8 95% confidence intervals in meters for the difference between the average trajectories of two ves-sel size classes

SizeClass(*1000dwt)

10-40 40-70 70-100 >100

In Out In Out In Out In Out

<10 [1;39] [-19;120] [4;153] [-8;164] [-5;251] [-26;251] [1;245] [-14;251]

10-40 [-1;121] [-19;55] [-8;219] [-42;150] [-5;251] [-31;244]

40-70 [-19;103] [-21;103] [-22;137] [-11;192]

70-100 [-10;44] [-5;92]

Assaidbefore,themajorityofthedifferencesisfoundinthepartofthetrajectoryoutsidetheprotectionoftheportsbreakwater(PartA).Itisthereforeworthwhiletoinvestigatethedifferencesthatoccurwithintheprotectedportarea.Thisisdonebyagaincalculating95%confidenceintervals,nowleavingoutthepartoutsidetheprotectionofthebreakwater(Table5.9).

Table 5.9 95% confidence intervals in meters for the difference between the average trajectories of two ves-sel size classes, for the trajectory within the port’s breakwater

SizeClass(*1000dwt)

10-40 40-70 70-100 >100


<10 [0;39] [-20;37] [2;116] [-14;74] [-7;104] [-34;89] [-4;97] [-24;88]

10-40 [-1;82] [-27;38] [-10;69] [-47;53] [-7;79] [-37;49]

40-70 [-21;9] [-22;17] [-23;15] [-11;16]

70-100 [-10;14] [-6;22]

Table5.9showsthatthecombinationsofthethreehighestvesselsizeclassesareinsidetheaccuracyinter-val.Thecombinationofthesizeclasses<10,000dwtand10,000-40,000dwtalsogivesasmallinterval,butthisisoutsidethedeterminedaccuracylimits.Thereforetheconclusionisdrawnthatthevesselsizeclasses40,000-70,000dwt,70,000-100,000dwtand>100,000dwtdonotdifferfromeachothersignificantly.So,whenevaluatingthepaththatvesselstake,theycanbebroughttogether.Itshouldhoweverbekeptinmindthatthisisonlyvalidfortheareainsidetheport’snorthernbreakwater.Outsidetheprotectionoftheport,everysizeclassshouldbeinvestigatedindividually.

5.3.2 Influence on the average speed along the path

Alsotheaveragespeedisinvestigatedforthecombinationsofdifferentsizeclasses.Thisisdoneinthesamemannerasforthetrajectoriesabove.Againthemeanandstandarddeviationofthedifferencesarecalculat-ed.Thedifferencesareagainreflectedinpercentages,toobtaintherelativedeviationofthevesselspeed.Table5.10andTable5.11showthemeanandstandarddeviationforrespectivelyincomingandoutgoingvessels.

Page-40-


Table 5.10 Comparison of the average speed from different vessel size classes, for incoming vessels. A positive value for the mean indicates that the size class on that row sails faster than the other

vessel class in the column.


10-40 40-70 70-100 >100

Mean(%)St Dev (%)

Mean(%)St Dev (%)

Mean(%)St Dev (%)

Mean(%)St Dev (%)

<10 3.3 6 25.6 10.6 29 8.9 26.9 10.6

10-40 23.3 7.6 26.7 5.8 24.7 7.2

40-70 4.2 3.9 1.6 3.5

70-100 -2.8 4.5

Table 5.11 Comparison of the average speed from different vessel size classes, for outgoing vessels. A positive value for the mean indicates that the size class on that row sails faster than the other

vessel class in the column


10-40 40-70 70-100 >100

Mean(%)St Dev (%)

Mean(%)St Dev (%)

Mean(%)St Dev (%)

Mean(%)St Dev (%)

<10 5.4 12.1 20.8 14.5 28.5 12.7 21.2 18.6

10-40 16.7 7.2 24.6 7.6 17.8 11.2

40-70 9.6 4.1 1.6 6.4

70-100 -9 8.8

Itcanbeseenthatforincomingvesselsthethreelargestsizeclasseshaveagoodresemblance(Mean<5%).Alsothetwosmallestsizeclassesdiffernottoomuch.Foroutgoingvesselstheequalityisless,butthemeansofthementionedsizeclasscomparisonsarestillwithin10%ofeachother.Thesedifferencesseemhowevertoolargetostatethatthereisnosignificantspeeddifference.Toproofthispoint,the95%confi-denceintervalsarederived.Table5.12clearlyindicatesthatnoconfidenceintervaliswithinthepredefinedaccuracyintervalof±6.5%.

Table 5.12 95% confidence intervals in percentages for the difference between the speeds of two vessel size classes.

SizeClass(*1000dwt)

10-40 40-70 70-100 >100


<10 [-4;11] [-5;32] [12;40] [5;48] [17;41] [14;54] [11;42] [0;54]

10-40 [11;35] [8;34] [15;36] [13;44] [14;36] [5;42]

40-70 [-3;14] [-5;16] [-5;12] [-6;15]

70-100 [-13;8] [-18;17]

Figure5.4showsanexampleofthespeeddevelopmentalongthetrajectoryfortwosizeclasses:70,000-100,000dwtand>100,000dwt,outgoingvessels.Fromthisfigureitbecomesclearthatthereindeedisasignificantspeeddifferencebetweenthesizeclasses.Itisobviousthatthedifferencesdonotlargelyoccuroutsidetheprotectedportarea,aswiththeaveragepath.Thereisacontinuous,significantspeeddiffer-

Page-41-


ence.Thisisalsofoundfortheothercombinationsofsizeclasses.Thereforeasplittingofthetrajectoryintodifferentparts(e.g.insideandoutsidetheport’sbreakwater)willnotleadtoahugelyimprovedresem-blence.

0 50 100 150 200 2502

4

6

8

10

12

14

16

Development along average path, 1 (grid)point = 50m

Spee

d ov

er g

roun

d (k

nots

)

port entrance

Entrance Beerkanaal

Entrance Amazonehaven

−20

−18

−16

−14

−12

−10

−8

−6

−4

−2

Diff

eren

ce (%

)

Figure 5.4 Speed development and the relative difference between the tracks (blue).

Size class 70,000-100,000 dwt (green) and size class >100,000 dwt (black)

Nexttothedifferences,Figure5.4showssomeinterestingagreementsinthespeeddevelopment.Altoughthespeedisdefinitelydifferent,theshapeofthetwolinesisverysimilar.Moststrikingisthespeeddipclosetotheportentrance.Thisdipispresentinthegraphsofallsizeclasses,butonlyforoutgoingvessels.Thisisbecauseatthislocationpilotsleavethevessel,byapilotboatthatcomesalongside.Forthisma-noeuvre,thevesselshavetoreducespeedduringashorttimeinterval.

AlsointerestingisthestrongreductioninspeedattheentranceoftheAmazonehaven.ThishastodowiththefactthatthesevesselshavetomakeaturntowardstheBeerkanaal,aftertheyhavelefttheAmazone-haven.Thisisespeciallytrueforlargervessels,thatcannotmakethisturnwhentheyaresailingtoofast.Therefore,thesmallervesselsizeclassesshowthisdiptoo,butforthemthespeedreductionismuchless.Incomingvesselsalsoshowthisspeedreduction,butlesssharpthantheoutgoingvesselsdo.

5.3.3 Conclusions

Thevesselsizedefinitelyhasaninfluenceonaswellthechosenpathasthevesselspeed.Concerningtheaveragepaththefollowingconclusionscanbedrawn.First,thesmallervesselssailtothestarboardsideofthelargervesselonaverage.Inpractice,thismeansthattheysailmoreclosetotheshore.Inabend,smallervesselstakeashorterpaththanthelargervessels,astheymakeasharpercurve(smallerradius).Thethreelargestsizeclassesshowaverygoodresemblence,whenlookingattheiraveragepathinsidethe

Page-42-


port’sbreakwater.Outsidethebreakwaterthereishoweverasignificantdifference.Theothersizeclassesbehavesignificantlydifferentinbothareas.

Thedifferencesbetweenthesizeclassesinvesselspeedarelargerthanthedifferencesfoundfortheaver-agepath.Nocombinationofsizeclasseshasaresemblencethatiswithintheaccuracyinterval.Althoughthethreelargestsizeclassesshowthesesignificantdifference,theyhavearelativelygoodagreementwitheachother,comparedtotheothersizeclasses.Ingeneralitcanbesaidthatvesselspeeddecreasedwhenthevesselsizeincreases.Anexceptiontothisissizeclass70,000-100,000dwt,whichhasaloweraver-agespeedthansizeclass>100,000dwt.Themostprobablereasonforthisisthatvesselsfromsizeclass>100,000dwtdousemoretugs,whichincreasestheirflexibilitytoalterforexampletheirspeed.Thismakesitpossibleforthemtonavigatewithalargerspeedinsidetheportarea14.

Althoughtheaveragepathsofsomevesselsizeclasseshaveaverygoodresemblence,nosizeclassesarebroughttogetherintoonegroup.Thisisbecausethevesselspeedsaresignificantlydifferentforallsizeclasses.Besidesthis,theaveragepathsoutsidetheprotectionoftheport’sbreakwaterarealsoverydiffer-entfromeachother.

5.4 Vessel and vessel speed distribution

Nexttotheaveragepathvesselstake,itisimportanttoderiveinsightintothedeviationfromthispath.InFigure5.5agridhasbeenlaidoverthedeterminedcasearea.Thedimensionsofagridcellare25X25meters(0.5Xgridsize).ThecolorsoftheplottedpointsindicatehowmanyvesselshassendanAISmessagewhentheywhereinsidethatspecificgridarea.Thedatausedinthisfigureisfromsizeclass70,000-100,000dwt,forincomingvessels.

Itcanalreadybeseenfromthispicturethatmostvesselschooseapproximatelythesamepath,butthatthereisalsoadeviationfromthispath.Thisdeviationissometimesverylarge,forexampleoutsidetheport.Onotherlocationthedistributionoverthewaterwayisrelativelynarrow,whichisforexamplethecaseintheMaasmond.IntheBeerkanaal,thereisclearly1pathmostvesselstake,butsomevesselschooseacompletelydifferent,morewestwards,route.Thisfiguremakesitclearthatitisneededtoinvestigatethedistributionoverthewaterwayindifferentcrosssections.Inthisway,amoredetailedinsightinthediffer-entvesselpathscanbeobtained.

14 ThispracticalexplanationoftheresultsfoundisderivedfromaninterviewwithBenvanScherpenzeel(Port

ofRotterdam).Otherpracticalinterpretationsofthetheoreticalresultsfoundinthisthesisareconcluded

fromthisinterviewaswell.

Page-43-


Blue: < 8 AIS messagesYellow: 8-13Red: 14-30Black: >30

Figure 5.5 Overview of all AIS messages sent from spe-cific areas.

Size class 70,000-100,000, ingoing vessels

Ateverygridpoint(each50meters)adistributionoverthecrosssectionoverthewaterwayiscalculatedfromtheavailabledatapoints.For4locationsontheincomingandoutgoingtrajectoriesthedistributionsareelaboratedfurther.ThelocationswherethisisdoneareindicatedinFigure5.6

Location1ischosen,becauseitgivesmoreinsightintothebehaviourofvesselsjustoutsidetheport.Influ-encesofforexampletheirdestination(e.g.Hamburg,Antwerp)mightbevisibleinthiscrosssection.Loca-tion2showshowthevesselsbehaveinarelativelywidewaterway(e.g.howdotheypreparebeforetakingthebendintotheBeerkanaal).Theotherlocationsarechosenbecausetheygiveinsightinhowvesselsbehaveinabend(location3)andmoreclosetotheirdestination(location4).

Nexttothepaththatvesselstake,alsothevarianceinthevesselspeedisimportant.Thereforethedistri-butionofthevesselspeedisalsoinvestigatedforthecrosssectionsindicatedinFigure5.6.Thisisdoneintwoparts.First,thedistributionofthevesselspeedinacertaincrosssectionisdetermined.Hereafter,this

Page-44-


islinkedtothespatialdistributionbycalculatingthedistributionoftheaveragevesselspeedover a cross section.

1

4

3

2

Figure 5.6 Cross sections on the vessel trajectories, which are used to obtain more insight into the

spatial vessel distribution and the distribution of the vessel speed. Source: Google Earth

5.4.1 Spatial vessel distribution on cross-sections

Figure5.7showsanexampleofaspatialdistribution,derivedfromtheempiricaldataatacertaincrosssec-tion.OntheX-axis,avalueofzerocorrespondentstothecalculatedvaluefortheaveragetrack.Thisfigureshowsthereforethedeviationfromtheaverage.ApositivevalueforXmeansthatthevesselsailsmoretothestarboardside.

Page-45-


−400 −300 −200 −100 0 100 200 300 4000

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

X = devia�on from average (m)

P (X

)

Figure 5.7 Spatial distribution on location 3 (see Figure 5.6),

Size class 10,000-40,000; In-coming.

Byvisualinspectingthedifferentdistributions,itseemsanormaldistributionfunctionwouldmakeagoodfit.Toobtain(besidesthevisualinspection)asecondindicationhowthedataisdistributed,theskewnessandkurtosisarecalculated.Theskewnessisameasureoftheasymmetryofthedistributionoftheempiricaldata.Anormaldistributionissymmetrical;thereforetheskewnessofthisdistributionis0.Valuesbetween-1and1indicatethatthedataareapproximatelynormaldistributed.Thekurtosisgivesanindicationofthepeakednessofadistributionfunction.Anormaldistributionhasakurtosisof3.Inthisthesisthekurtosisiscorrectedbysubtracting3,becauseinthiswayvaluesaround0aretobeexpectedforanormaldistribution.Thisisalsoknownastheexcesskurtosis.Equation(5.2)and(5.3)showtheformulasfortheskewnessandkurtosis(Groenveld,2001).

Theskewnessandexcesskurtosisarecalculatedforthedifferentdatasetsatalllocations.TheresultsaresummarizedinTable5.13andTable5.14respectively.

n3

i ii=1n

3 3/2i i

i=1

Skewness =

(x - ) *p(x )

(x - ) *p(x )[ ]

µ

µ

∑

∑(5.2)

n4

i ii 1n

2 2i i

i 1

Excess kurtosis

where n=numberofdatapoints

(x ) *p(x )3

(x ) *p(x )[ ]

µ

µ

=

=

=−

−−

∑

∑(5.3)

Page-46-


Table 5.13 Skewness for the different datasets at locations 1 to 4.

Location<10,000 10,000-40,000 40,000-70,000 70,000-100,000 >100,000

In Out In Out In Out In Out In Out

1 -0.16 -0.5 -0.64 -0.17 -0.24 -0.26 -0.21 -0.07 0.09 0.02

2 -0.1 -0.44 -0.36 -0.46 0.01 -0.78 -0.05 -0.07 -0.28 0.08

3 -1.24 -0.02 -0.63 0.52 0.09 0.04 -0.17 0.21 0.02 -0.14

4 -0.24 -0.73 -0.07 -0.49 1.06 -0.91 0.32 -0.58 0.94 -0.4

Table 5.14 Excess kurtosis for the different datasets at locations 1 to 4.

Location<10,000 10,000-40,000 40,000-70,000 70,000-100,000 >100,000


1 -0.43 0.12 -0.09 -0.48 -0.5 -0.62 -0.72 -0.79 -0.51 -0.68

2 -0.06 -0.17 0.05 -0.03 -0.4 1.81 -0.36 -0.86 -0.71 -0.98

3 3.07 -0.57 0.44 -0.13 -0.69 -0.4 -0.21 0.28 -0.62 -0.37

4 0.09 0.17 -0.54 -0.12 0.8 1.17 0.06 2.57 0.72 0.75

Itcanbeseenthattheskewnessis,exceptfor2values,alwaysinsidethe[-1;1]-interval.Thismeansthat,basedontheskewness,itcanbeconcludedthatthedistributionsareindeedapproximatelynormaldis-tributed.Itisremarkabletoseethattheskewnessformostdatasetshasanegativevalue.Thismeansthattheyhaveatailtotheleftsideofthedistribution.Inpractice,thistailistowardstheportsideofthevessels.Thismeansthatthereareoftensomevesselsthatdeviatemoretothemiddleofthechannel,whereasthedeviationtowardstheshoreismorestrictlybounded.Fromapracticalpointofviewthisseemsalogicalconclusion.

Theexcesskurtosisisformostdatasetsaround0.Therearehoweversomenoticeablelowandhighvalues.Mosteye-catchingisthevalueof3.07forsizeclass<10,000dwt;incomingatlocation3.Figure5.8(left)showsthegraphofthisdistribution.Thismakesitclearthatthishighvalueiscausedbyarelativesmallpeakattheleftsideofthedistribution.Duetotheverysmallstandarddeviationofthisdistribution,thispeakhasabiginfluenceontheexcesskurtosis.(whichisthecomparisonbetweenthe4thmomentrela-tivetothemeanandthe4thpowerofthestandarddeviation).Thisalsoexplainstheothervalueslargerthan1.Inpractice,thissmallpeakiscausedby1or2vesselsthatsailalongthispath.Thefactthatsuchasmallamountofvesselshaveaccidentallysailedatthislocationisnoreasontorejecttheassumednormaldistribution.

Valuesaroundandlowerthan-1arefoundaswell.Thesedatasetshaveanexcesskurtosisthatindicatestheyaremainlyuniformdistributed(theexcesskurtosisforauniformdistributionis-1.2).Mostclosetothisaretheoutgoingvesselsfromsizeclass>100,000atlocation2,withanexcesskurtosisof-0.98.Figure5.8(right)showsthisdistribution,whichmakesitclearthatindeedauniformdistributedmightbeabetterfitforthisdatasetatthisspecificlocation.Byfarmostdatasetsdohoweverindicatethatanormaldistribu-tionisexpectedtogiveagoodfit.Itisthereforetriedtodoso.

Page-47-


−400 −300 −200 −100 0 100 200 300 4000

0.05

0.1

0.15

0.2

0.25

X = devia�on from average (m)P

(X)

Skewness = 0.08Kurtosis = -0.98

−400 −300 −200 −100 0 100 200 300 4000

0.05

0.1

0.15

0.2

0.25


P (X

)

Skewness = -1.24Kurtosis = 3.07

Thenormaldistributionthatisusedtofittheobserveddistributionfunctionsisafreetruncatednormaldistribution.Itisdescribedbythreeparameters:themean(μ),thevariance(σ2)andascalingparameter(A).Thefactthatitistruncatedmeansthatthedistributionisboundedbelowandabove.Normally,anormaldistributionisnotboundedandvaluesontheX-axiscangoto(minus)infinity.Inpractice,vesselswillnotdeviatethatmuchfromtheirpath,becausethentheyaregrounded.Ofcoursethismight(veryrarely)hap-peninreality,butinsuchcasesothermechanismsthanastatisticaldeviationfromtheaveragepathwillbeleading.Thisisthereforenottakenintoaccountinthenormaldistributionsthatdescribethevesselstrajectories.

Figure5.9andshowsthefittingofanormaldistributiononthefourpredefinedlocations.Thedataset10,000-40,000;incomingischosenasanexample.Thevaluesintheupperrightcornerofthegraphsde-scribethefittednormaldistribution(reddottedline).TheR2valuesmentionedindicatethegoodnessoffitforthisdistribution.Thecalculationofthisparameteriselaboratedbelow.

−400 −300 −200 −100 0 100 200 300 4000

0.05

0.1

0.15

0.2

0.25

X = devia�on from average (m )

P (X

)

R 2=0.9443

µ = −2.9σ = 72.5A = 0.14

−400 −300 −200 −100 0 100 200 300 4000

0.05

0.1

0.15

0.2

0.25


P (X

)

R 2=0.8663

µ=0σ=86.2A=0.12

Figure 5.9 The spatial vessel distribution of the vessel size class 10,000-40,000, incoming based on observed values (blue) and the fitted normal distri-

bution (red dotted), on location 1 (left) and location 4 (right).

Figure 5.8 Spatial distribution for the vessel size class <10,000; incoming at location 3 (left) and >100,000; outgoing at location 2 (right)

Page-48-


Assaidbefore,thenormaldistributionsaredescribedbythreeparameters.Nexttothis,theyareboundedbyX-valuesonbothsides.Equation(5.4)showstheformulathatdescribesthenormaldistribution,derivedforlocation4(Figure5.9;right).

fit

2-(X- )

22*

X = deviationfromthemeaninmetersforX = [-250;250] 2.9

72.5A 0.14

P (X) A*e

µ

σ

µσ

→ = −==

=

(5.4)

Theskewnessandexcesskurtosisgaveanindicationthatnormaldistributionswouldgiveagoodfit.Nowtheyarederived,thedistributionscanbetested.TheirgoodnessoffitisfirstdeterminedbyperformingaChi-squaretest(χ2).Thistestdeterminesthedegreeofagreementbetweentheempiricaldistributionandthetheoretical(normal)distribution.Thehypothesisisthatthereisnosignificantdifferencebetweenthosedistributions.Theconfidencelevel(answeringthequestionwhatissignificant)isseton95%,thesameasusedpreviously.

Thedetailedelaborationofthedifferentχ2-testscanbefoundinAppendixE.Table5.15showswhetherthedifferentdatasetsandlocationspasstheχ2-test(OK)ornot(FAIL).

Table 5.15 Results of the χ2-tests for the fitting of the assumed normal distribution to the different data sets.

Location<10,000 10,000-40,000 40,000-70,000 70,000-100,000 >100,000


1 OK OK OK OK OK OK OK OK OK OK

2 OK OK OK OK OK OK OK OK OK OK

3 OK OK OK OK FAIL OK OK OK OK OK

4 OK OK OK OK OK OK OK FAIL FAIL OK

Clearly,mostdistributionshaveasufficientfit.Therearethreedatasetsthatdonotpasstheχ2-test.Thefailsforthedatasets70,000-100,000dwt;outgoingand>100,000dwt;incomingatlocation4arenotverysurprising.Thecalculatedskewness(-0.58and0.94)andkurtosis(2.57and0.72)forthesedatasetswerealreadynotcompletelyindicatinganormaldistribution.Thisiscausedbyrelativelysmallpeakstotheouterlimitsofthedistribution,asexplainedbefore.Thedataset40,000-70,000dwt;incomingalsofailstheχ2-test atlocation3.Figure5.10showsthereasonforthis:alargepeaktotherightsideofthedistribution.Suchapeakisveryunlikelytooccurwhenthevesseldistributionisnormaldistributed.ThesmallpeakattheouterleftsideofthegraphisanoutlierthatisnotfilteredoutbytheMatlabcode.Thisoutlierdoeshowevernotinfluencetheoutcomeoftheχ2-testverymuch.Asalmosteverydatasetpassestheχ2-test,itisconcludedthatthenormaldistributionisagoodapproximationofthevesseldistributionoveracrosssectioninthewaterway.

Page-49-


−400 −300 −200 −100 0 100 200 300 4000

0.05

0.1

0.15

0.2

0.25


P (X

)

R2=0.8292

µ=7.9σ=72A=0.14

Figure 5.10 The spatial vessel distribution of the vessel size class 40,000-70,000; incoming at location 3

Besidesthediscusseddatasets,itisprovenbytheχ2-test-testthateverydatasetiscorrectlyapproximatedbyitsspecificnormaldistribution.Thereforethesedistributionsareusedinthefollowing.Itishoweverstillinterestingtoinvestigatehowwellthenormaldistributionsfittheempiricaldata.Theχ2-test-tests have providedanindicationforthis,butmoreinsightisobtainedbycalculatingthecoefficientofdetermination,R2.Thiscoefficientdependsontherelationbetweenthesumofthesquaredresiduals(SSR)andthesumofthesquarederrors(SSE).Equation(5.5)showsthecalculationofR2,SSRandSSE.

2

n2

X 1

n2

fitX 1

SSRR

SSE SSR

SSR

SSE

(P (X) P( ))

(P (X) P(X))

µ=

=

=+

=

=

−

−

∑

∑

(5.5)

ValuesofR2rangefrom0to1;inwhichvaluescloseto1indicateastrongcorrelationbetweenthetwodistributioncurves.Thegoodnessoffitisthereforedependentonthisvalue.Table5.16showsR2foralldatasets.

Table 5.16 Coefficients of determination (R2) for the spatial vessel distribution

Location<10,000 10,000-40,000 40,000-70,000 70,000-100,000 >100,000


1 0.88 0.85 0.87 0.77 0.83 0.76 0.95 0.76 0.85 0.79

2 0.94 0.85 0.96 0.88 0.97 0.87 0.99 0.91 0.94 0.95

3 0.97 0.82 0.96 0.88 0.83 0.91 0.91 0.86 0.96 0.86

4 0.95 0.96 0.94 0.93 0.94 0.98 0.94 0.97 0.88 0.97

Page-50-


Mostdatasetshaveanaveragevaluehigherthan0.8.Forthedatasetsthatdidnotpasstheχ2-test values above0.8arefoundaswell.Therearehoweversomeinterestingpatternsthatcanbeobservedfromthetable.Moststrikingarethelowervaluesthatoccurforoutgoingvesselsatlocation1and-toalesserextent-atlocation2and3.Figure5.11showsthedistributionforthesizeclass70,000-100,000dwt;outgoing,atlocations1(left)and3(right).Atlocation1,thedistributionisverywide(σ=123.9m).Becauseofthis,onlyasmallamountofdatapoints(afewvessels)canalreadycauseasmallpeak.Nexttothis,clearlytwopeakscanbedistinguished,both±100awayfromX=0.Thismightgiveanindicationthatvesselsarealreadyadaptingtheirpositionatthewaterwaytotheirdestination,towardstheSouth(e.g.Antwerp)ortowardstheNorth(e.g.Hamburg).

Atlocation3,thebendattheentranceoftheBeerkanaal,thedistributionismuchmorenarrowthanatlocation1.Anotherremarkablefindingisthefactthatthedistributionclearlyhastwopeaks.ThiscanbeexplainedbythefactthatthosevesselshavebeenhinderedbyvesselscomingfromtheCalandkanaal.Be-causeofthistraffic,theyhadtochoosea(lesspreferable)pathmoretotheinnerbend.

−400 −300 −200 −100 0 100 200 300 4000

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2


P (X

)

R 2=0.8571

µ=−5.4

σ=74.9

A=0.13

−400 −300 −200 −100 0 100 200 300 4000

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2


P (X

)

R 2=0.7592

µ=10.5

σ=123.9

A=0.08

Figure 5.11 The spatial vessel distribution of the vessel size class 70,000-100,000; outgoing at location 1 (left) and 3 (right)

Ingeneral,theincomingvesselshaveahigherR2valuethanoutgoingvessels.Thisismainlybecausetheoutgoingvesselshaveawiderdistributionoverthewaterway.Inpractice,they‘spreadout’moreoverthewaterwaydependingonforexampletheirdestination.Thereishoweveroneexceptiontothisobservation.Forthethreelargestsizeclasses,atlocation4theoutgoingvesselsaremorenormallydistributed(higherR2 value)thantheincomingvessels.

Page-51-


−400 −300 −200 −100 0 100 200 300 4000

0.05

0.1

0.15

0.2

0.25


P (X

)

R 2=0.971

µ=2.1σ=35A=0.27

−400 −300 −200 −100 0 100 200 300 4000

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2


P (X

)

R 2=0.8768

µ=−18.9

σ=55.3

A=0.17

Figure 5.12 The spatial distribution on location 4 for incoming (left) and outgoing (right) vessels from size class >100,000 dwt.

Figure5.12showsthedistributionsatthislocationforthesizeclass>100,000dwt,incoming(left)andout-going(right).Thedistributionfortheincomingvesselsclearlyshowsonepeak,butalsotwosmallerpeakstotherightsideofthedistribution.Apparently,apartofthevesselschoosestotakeanotherpathinsidetheBeerkanaal.ThiswasalreadyobservedfromFigure5.5onpage43.Thepresenceofthese‘preferencelanes’iscausedbythewaythevesselssailintotheAmazonehaven.Dependingonhowtheyareloaded,vesselshavetosailforwardsorbackwardsintotheAmazonehaven.Whentheysailinforwards,whatmostvesselsdo,theychoosethepathclosesttotheshore(thelargestpeakinFigure5.12).Thisisdonebecauseinthiswaythewidestbendcanbetaken,whichispreferred.Iftheysailinbackwards,thisistheotherwayaround,asthewidestbendisnowattheothersideofthewaterway(seeFigure5.13).

Figure 5.13 The difference in the vessel path when sailing forwards (red) or backwards (blue) into the Amazonehaven.

Page-52-


5.4.2 Vessel speed distribution

Nexttothespatialvesseldistribution,alsothedistributionofthevesselspeedoverthecrosssectiononthe4predefinedlocationshasbeeninvestigated.Theaccuracyofspeedcalculationsis±6.5%,whichisataspeedof15knotsequivalentto±1.0knot(seesection5.2).Thereasonforthisinaccuracyisthelargedeviationoftheindividualvesselspeedfromthecalculatedaveragespeed.Thislargedeviationwillbeinvestigatedmoreintodetailinthissection.Bycalculatingtheskewnessandexcesskurtosis,togetherwithperformingaχ2-testitisinvestigatedifthedatacanagainbeapproximatedbynormaldistributions(seeAp-pendixE).

Theskewnessandexcesskurtosisindicatethatanormaldistributionisagoodindicationforalmosteverydataset.Alsotheχ2-testsupportsthisconclusion.Toinvestigatehowwellanormaldistributionmatchesthedatasets,coefficientsofdeterminationarecalculated.TheseareshowninTable5.17.

Table 5.17 Coefficients of determination (R2) for the vessel speed distribution in locations 1 to 4

Location<10,000 10,000-40,000 40,000-70,000 70,000-100,000 >100,000


1 0.88 0.85 0.87 0.77 0.83 0.76 0.95 0.76 0.85 0.79

2 0.94 0.85 0.96 0.88 0.97 0.87 0.99 0.91 0.94 0.95

3 0.97 0.82 0.96 0.88 0.83 0.91 0.91 0.86 0.96 0.86

4 0.95 0.96 0.94 0.93 0.94 0.98 0.94 0.97 0.88 0.97

Itcanbeseenfromthetablethatallempiricaldistributionshavequiteagoodfitforanormaldistribution.Thesmallestvaluesarefoundatlocation1,wherevesselshavemorefreedomtomanoeuvreandtoaltertheirspeeds.ThehighestvaluesforR2arefoundforincomingvesselsfromthethreelargestsizeclasses,atlocations3and4.Attheselocationsthedifferentvesselsspeedshaveconvergedmoretowardseachother.ThisisalsoshownbyFigure5.14,whichshowthedistributionofthevesselspeedinthedifferentcrosssec-tions.Inthefigurealsothefittednormaldistributionisplotted(discontinuousredline).Thethreeparam-etersintherightuppersideofthefigures(μ,σandA)describethisdistribution.

Page-53-


0 2 4 6 8 10 12 14 16 18 200

0.05

0.1

0.15

0.2

0.25

X = Vessel speed (kn) −−>

P (X

)

R 2=0.8833µ=10.2

σ=1.9

A=0.1

0 2 4 6 8 10 12 14 16 18 200

0.05

0.1

0.15

0.2

0.25


P (X

)

R 2=0.8865µ=7.5

σ=1.4

A=0.14

0 2 4 6 8 10 12 14 16 18 200

0.05

0.1

0.15

0.2

0.25


P (X

)

R 2=0.9097µ=6.0

σ=0.8

A=0.23

0 2 4 6 8 10 12 14 16 18 200

0.05

0.1

0.15

0.2

0.25


P (X

)

R 2=0.9533µ=5.6

σ=0.7

A=0.27

Loca�on 1 Loca�on 2


Figure 5.14 Vessel speed distribution on locations 1 to 4, for sizeclass 70,000-100,000 dwt; incoming vessels.

Thegraphsmakeclearthatthevesselspeedhasawidedistribution.Thewidthofthespeedintervalisforthefirsttwolocationsaround10knots.ItcanbeseenthatthisintervaldecreaseswhenthevesselssailsfurthertowardstheAmazonehaven.Thisisalsoshownbytheσ(standarddeviation)thatdevelopsfrom1.9atlocation1tofinally0.7atlocation4.Itcanbeseenaswellthatthelargestreductioninspeedisobtainedbeforelocation3,sobeforethevesselsailsintothestraightpartoftheBeerkanaal.Theothersizeclassesshowthesamebehaviour,althoughitmustberemarkedthatforthesmallervesselsthedeviation(σ)isclearlylarger.

Nexttothedistributionofthevesselspeedinacrosssection,itisalsointerestingtoobtaininsightinthedistributionofthevesselspeedoveracrosssection.Todoso,graphsareproducedthatshowtheaveragespeedondifferentlocationsofacrosssection.Figure5.15givesanexampleofthis,forthecrosssectionsatlocation1to4,againforincomingvesselsfromsizeclass70,000-100,000dwt.

Page-54-


−200 −100 0 100 2000

5

10

15

X = devia�on from average (m)−200 −100 0 100 200

0

5

10

15


−200 −100 0 100 2000

5

10

15


Vess

el s

peed

(kn)

−200 −100 0 100 2000

5

10

15




MeanMean

Mean Mean

Vess

el s

peed

(kn)

Vess

el s

peed

(kn)

Vess

el s

peed

(kn)

Figure 5.15 Vessel speed distribution over the cross sections at locations 1 to 4, for incoming vessels from size class 70,000-100,000 dwt.

Thefigureshowsthatthevarianceofthevesselspeedoverthesecrosssectionsisnotverylarge.Especiallyatlocations3and4,thevesselspeedisclearlyindependentfromthelocationinthecrosssections.Forlocation2and-especially-location1thisimageissomewhatmorepeaky.Theirregularbehaviourattheouterlimitsoriginatesfromthefactthatthosepointsarecalculatedfromasmallamountofvessels.Thismakesthosepointslessaccurateandmostpeaksthatoccurattheouterlimitsarethereforenotsignificant.Thedistributionsoftheothersizeclassesareinvestigatedaswell.ThoseshowasimilarpatternasshowninFigure5.15.Foroutgoingvesselsandforsmallersizeclassesasomewhatmorepeakydistributionisfoundsometimes.Noproofishoweverfoundthatthelocationinthecrosssectionhasasignificantinfluenceonthevesselspeed.

ThevesseldistributionsandvesselspeeddistributionsthatarenotshowninthischaptercanbefoundinAppendixF.

5.5 Conclusions

Inthischaptertheaveragebehaviourofvessels,visitingtheAmazonehaven,isinvestigated.Theamountofdatausedmakesitpossibletodrawconclusionsregardingaveragevesselpathwithanaccuracyof±30m.Forvesselspeed,anaccuracyof±6.5%canbeachieved.Thesevaluesarebasedona95%significancelevel;thisiskeptasatresholdvaluethroughoutthisthesis.Theaccuraciesthatarefoundareacceptedas

Page-55-


sufficientinthisthesis.

Itisfoundthatthevesselsizeclearlyinfluencestheaveragepathandspeed.Aslongasthevesselsarewith-intheprotectionoftheport’sbreakwater,theaveragepathsofthethreelargestsizeclasseshaveagoodresemblence.Inthepartofthetrajctoryoutsidetheport’sprotection,thesedohowevertakeasignificantdifferentpath.Thevesselspeedisdifferentforall5sizeclasses.

Ingeneral,thefollowingcanberemarkedconcerningtheinfluenceofvesselsize.Largervesselssailmoreintothemiddleofthechannel.TheyalsotakealargerbendattheentranceoftheBeerkanaal.Onaverage,vesselsfromthelargestsizeclass(>100,000dwt)sailabout100metersmoretothemiddlethanvesselsfromthesmallestsizeclass(<10,000dwt).Thisistrueforbothincomingandoutgoingvessels.

Thevesselsizedoesalsoinfluencetheaveragevesselspeed.Ingeneralitistruethatlargervesselssailslow-erthansmallervessels.Thereisoneexceptiontothis:vesselsfromsizeclass70,000-100,000sailslowerthanallothervessels,includingthesizeclass>100,000dwt.Thespeeddifferencebetweenbothincomingandoutgoingvesselsfromthefastest(andsmallest)sizeclassandtheslowestsizeclass(70,000-100,000dwt)isalmost30%.

Thespatialdeviationoverthewaterwayisverywellapproximatedbyanormaldistribution.Thisissup-portedbycalculatingvaluesfortheskewnessandexcesskurtosisoftheempiricaldatasets.Aχ2-testshowedaswellthattheassumednormaldistributionsareagoodapproximation.Nexttothis,R2 values for the goodnessoffitarecalculatedon4differentcrosssections.Thesevaluesdemonstrateagainthatthenormaldistributionisagoodfitfortheempiricaldata.

Thedeviationfromtheaveragespeedisquitelarge.Inmostcrosssectionsthewidthofthespeeddistribu-tioncangoupto10knots,dependingonthelocationandvesselsize.Theskewness,excesskurtosis,χ2-test andR2valueshaveshownthatthevesselspeedinacrosssectionisbyagoodapproximationnormallydistributed.Alsothevesselspeeddistributionoverthecrosssectionsisexamined.Inthesedistributionsnosignificantproofisfoundthatthelocationinthecrosssectionhasinfluenceonthevesselspeed.Itisthere-foreconcludedthatthevesselspeedisuniformdistributedoveracrosssection.

Northern breakwater Start bend into Beerkanaal95

100

105

110

115

120

125

130

Development along average path -->

head

ing

(deg

rees

), 0

/ 36

0 =

Nor

th

Part 1 Part 2

Externalinfluences

Chapter6

Page-58-

Externalinfluences

6 External influences

Inthepreviouschaptertheaveragevesselbehaviourfordifferentsizeclassesisobtained.Thisaveragebe-haviourissplitintothevesselpathandtheaccompanyingvesselspeed(speedoverground).Itisverylikelythatexternalcircumstanceslikewindandcurrenthaveaninfluenceonthesecharacteristics.Ifthisisindeedthecaseandtowhatextent,isinvestigatedinthischapter.Thefactorsthatareexaminedare:wind,currentandvisibility.Thesearechosen,becausethelargestinfluenceonthevesselpathandspeedisexpectedforthesefactors.ThetrajectorybetweenNorthSeaandtheAmazonehavenis,whereneeded,splitintodiffer-entparts.Thismakesitpossibletodrawconclusionsregardingtheexternalinfluenceonthevesselbehav-iouroncertaintypesofwaterways.Theseconclusionsareusedinchapter8,fortheformulationofgenericrules.

6.1 Wind

6.1.1 Split up of the trajectory

Fortheinvestigationoftheinfluenceofwind,thetrajectorybetweentheNorthSeaandtheAmazonehavenissplitintotwoparts.Part1(‘Maasmond’)isbetweentheNorthSeaandtheentranceoftheBeerkanaal.Part2(‘Beerkanaal’)isbetweentheentranceoftheBeerkanaalandtheentranceoftheAmazonehaven.ThetrajectoryinsidetheAmazonehavenisnottakenintoaccount,asthemanoeuvrabilityisverylimitedatthispoint.ItisthereforeexpectedthatnosignificantresultsshallbefoundregardingthedeviationfromthevesselpathandvesselspeedinsidetheAmazonehaven.

TheMaasmondandBeerkanaalarelookedatseparately,becausethevesselheadingisclearlydifferentfortheseparts(Figure6.1).Thisisimportant,becauseitmeansthatthewindalsoworksfromdifferentdirec-tionsonthevessels.Forexample,anincomingvesselthatsailsintheMaasmondencountersastrongwindfrombehind.WhenthevesselenterstheBeerkanaalthissamewindnowcomesfromhisstarboardside,throughwhichthiswindislikelytohaveadifferentinfluence.

5.9 6 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.84.4

4.41

4.42

4.43

4.44

4.45

4.46

4.47

4.48

4.49

4.5

Part I - ‘Maasmond’

Part 2 - ‘Beerkanaal’

Figure 6.1 Part I and part 2

Page-59-


6.1.2 Wind data

ThewinddatathatisusedtomaptheinfluenceofthisexternalcircumstanceisobtainedfromtheKNMI15.ThisdatasetcontainstheinformationregardingthewindclimateatHoekvanHollandin2009.HoekvanHollandisseenasagoodapproximationofthewindclimateinthewholecasearea.Everyhourthehourlymeanwindspeedisknownwithanaccuracyof1m/s.Alsothemeanwinddirectionisgiveneveryhour,withanaccuracyof10degrees.BycouplingthepointsintimeoftheindividualAISmessagesandthewinddataset,thewindspeedanddirectionisknownforeveryAISmessage.

Theinfluenceofwindisexaminedfordifferentwinddirectionsandwindspeeds.Thedivisioninwinddirectionsismade,dependendonthevesselheading.Forthetwotrajectories(MaasmondandBeerkanaal)thewinddirectionissplitintofourgroups:windfrombehind,front,portsideandstarboardside.Forthecouplingofthesegroupstothewinddata(whichisgivenindegrees),theaverageheadinginthetwoportsiscalculated.Figure6.2showsthistranslationtoaspecificrangeofdegrees.Forincomingandoutgoingvesselsthesameaverageheadingsareused,buttherangeofdegreesisexactlytheoppositeofeachother(250o-340oiswindfrombehindforincomingvessels,butwindfromthefrontforoutgoingvessels).

Port side (in)Starboard side (out)

Starboard side (in)Port side (out)

Front (in)Behind (out)

Behind (in)Front (out)

0 / 360

Average heading: 115 (in) 295 (out)

Port side (in)Starboard side (out)

Starboard side (in)Port side (out)

Front (in)Behind (out)

Behind (in)Front (out)

0 / 360

Average heading: 195 (in) 15 (out)

Figure 6.2 Average heading in Maasmond and Beerkanaal

Thewindspeedisdividedintothreeclasses(Table6.1).Byusingthisdivision,everywindclasshasapproxi-matelythesameamountoftracks.Togetherwiththesplitupofthewinddirection,everyvesselsizeclassnowisdividedinto12differenttypesofwindinfluence.Itmustberemarkedthatnoteveryofthose12datasetshavethesameamountoftracks.Thisdependsverymuchonthewinddirection,asthereisforexamplelessfrequentwindfromtheeastthanfromthewest.

Table 6.1 Wind speed classes

Windspeedclass Beaufort Windspeed(m/s) Windspeed(kn)

I 0-3 0-5.4 0-10

II 4 5.5-7.9 11-15

III >5 >8.0 >15

15 RoyalNetherlandsMeteorologicalinstitute,thewinddataisobtainedfromtheirwebsite,www.knmi.nl,

at1April2010

5.9 6 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.84.4

4.41

4.42

4.43

4.44

4.45

4.46

4.47

4.48

4.49

4.5

Page-60-

Externalinfluences

6.1.3 Results

Foreverywindregimeandvesselsizeclass,aselectionoftracksisobtained.Theseselectionsarecomparedtotheaveragevesselpathandvesselspeedforthatspecificsizeclass.Thiscomparisonismadeforthechosenpathaswellasthedevelopmentofthevesselspeedalongthispath.Theresultsarepresentedinthesamewayaswasdoneinthepreviouschapter.Anaveragedeviationfromthevesselpathiscalculated.Inthis,apositivevaluemeansthattheobservedselectionsailsmoretothestarboardsideoftheaveragepathofthatspecificsizeclass.Thespeeddifferencesarecalculatedinpercentages.TheresultsarehandledseparatelyfortheMaasmondandBeerkanaalbelow.

Maasmond

Figure6.3showsthedeviationfromtheaveragepathforthedifferentsizeclasses,whentheyaresubjecttocrosswind.OntheX-axisthecrosswinddevelopsfromastrongwindfromportsidetoastrongwindfromstarboardside.Thefigureclearlyshowsthequiteextensiveamountofscatterthatispresentintheresults,mainlybecauseofthenaturaldistributionofvesselsoverthewaterway.Thedifferentsizeclassesarealsoindicatedinthefigure,toseeifsignificantconclusionsconcerningthespecificclassescanbedrawn.Afteradetailedinspectionofthefigureitisconcludedthatnosignificantdifferencesbetweenthesizeclassescanbefound.Thereforethesizeclassesarebroughttogether.Alsothewindspeedisbroughttogetherinthethreeclassesderivedintheprevioussection.

< 10,000 dwt

10,000 - 40,000 dwt

40,000 - 70,000 dwt

70,000 - 100,000 dwt

> 100,000 dwt

<-- Wind from port side Wind from starboard side -->

−15 −10 −5 0 5 10 15

−400

−300

−200

−100

0

100

200

300

400

500

Wind speed (m/s)

Dev

ia�o

n fr

om a

vera

ge tr

ack

(m)

Figure 6.3 Influence of cross wind on the chosen path of individual vessels at the ’Maasmond’ trajectory

Page-61-


Figure6.4showsaboxplotofthegroupedresults.Thehorizontalredlinereflectsthemeanvalue.Theblueboxindicatesthe25%and75%percentile.Therangeofresultsisindicatedbythehorizontalblackline.Theredplussesareoutliers.Everypointthatisfurtherawayfromthemeanthanapproximately2.7timesthestandarddeviationisseenasanoutlier.ThisisdeterminedbyMatlab.Itisobviousfromtheboxplotthattheinfluenceofcrosswindissmallcomparedtothenaturaldeviation,whichisintheorderofhundredsofmeters.

Figure 6.4 Boxplot of the influence of crosswinds in the Maas-mond

<-- Wind from port side Wind from starboard side -->

> 8 5.5−8 0−5.5 0−5.5 5.5−8 > 8 −600

−400

−200

0

200

400

600

Dev

ia�o

n fr

om a

vera

ge tr

ack

(m)

Wind speed (m/s)

Toobtainamoregenericresult,alinearfunctionisfittothemeanvaluesderivedbytheboxplot.Alinearfunctionischosen,becausethisisasimplefunctionanditisstatisticallydifficulttoderiveamorecomplexrelationshipduetotheamountofscatter.Avisualinspectionofthefiguresupportsthisconclusion,asalinearfunctionseemtogiveareasonablefit.Figure6.5showsthelinearfit.Inchapter8thisrelationshipisfurtherelaboratedandgeneralised.Intheremainderofthisthesistheboxplotandtheindividualvesseltracksarenotelaborated.Itisassumed,basedonthisexamplethatitiscorrecttodoso.

Page-62-

Externalinfluences

<-- Wind from port side (m/s).......wind from starboard side (m/s) −−>

> 8 5.5−8 0−5.5 0−5.5 5.5−8 > 8 −40

−20

0

20

40

60

devi

a�on

from

ave

rage

trac

k (m

)

Figure 6.5 Linear relationship regarding the influence of crosswinds in the Maasmond

Thevesselspeedisaffectedbycrosswindsaswell.Figure6.6showstheresultsforthedifferentsizeclasses(left)andtheirgroupedaverages(right).Thesamepatternwithareasonableamountofscatterispresent.However,thecalculatedmeanvaluesdonotshowalinearrelationshipthistime.Thevesselspeedisclearlysmalleratbothsidesofthegraph.Inpracticethismeansvesselsarelikelytosailslowerwhenthereisastrongcrosswind,regardlessifthewindcomesfromportsideorstarboardside.Therelationshipusedtodescribethecalculatedmeanvalues,isasecondorderpolynomial.

> 8 5.5−8 0−5.5 0−5.5 5.5−8 > 8 −15

−10

−5

0

5

10

15

<--Wind from port side (m/s)....wind from starboard side (m/s) -->

devi

a�on

from

ave

rage

spe

ed (%

)

> 8 5.5−8 0−5.5 0−5.5 5.5−8 > 8 −4

−3

−2

−1

0

1

2

o <-- Wind from port side (m/s).......wind from starboard side (m/s) −−>

devi

a�on

from

ave

rage

spe

ed (%

)

Figure 6.6 The influence of crosswinds on the vessel speed in the Maasmond The black lines in the left figure represent the results for the different size classes. The

red line in the left figure indicates the average, whereas the red lines in the right graph shows the fitted second order polynomial

Afterinvestigatingthevesselpathandvesselspeed,itcanbeconcludedthatcrosswindsdefinitelyhaveanoticeableinfluence.Forthevesselpaththisinfluenceishowevernotverylarge,especiallycomparedtothenaturaldeviationoverthecrosssection.Forlargewindspeedsthedeviationfromtheaveragepathisin

Page-63-


theorderof30meters.Themaximalvesselspeedreductionisapproximately4%.Anexplanationforbothresultscanbefoundwhenlookingattheaverageheadingofvessels.Figure6.7showsthedevelopmentoftheaverageheadingintheMaasmondforsizeclass>100,000dwt,forincomingvessels.Thebluelineistheaverageforthewholesizeclass.Thegreenlinereflectsthedevelopmentoftheheadingwhenthereisawind(windspeed>8m/s)blowingfromstarboardside.Itcanbeseenthatthevesselsobviouslyhaveadifferentheadingwhentheyareencounteringastrongcrosswind.

Northern breakwater

Fastening tugs Start bend into Beerkanaal100

105

110

115

120

125

130

Development along average path

head

ing

(deg

rees

), 0˚

/ 3

60˚

= N

orth

Figure 6.7 Development of the average vessel heading for the whole sizeclass >100,000 dwt and the part of the vessels that encounter strong crosswind from star-board side.

Thesevesselscorrecttheirheadinginordertostayoncourse.Iftheydonotcorrecttheircourse,thestrongcrosswindwouldblowthem‘away’.Itcanbeseenthattheheadingdifferenceislargestoutsidetheprotec-tionofthenorthernbreakwater.WhenthevesselsapproachthebendtowardstheBeerkanaal,theheadingdifferencebecomessmaller.Thisprincipleisalsofoundfortheothersizeclasses,butonlyforincomingves-sels.Outgoingvesselsdonot,ortoafarlesserextent,adapttheirheadingtothewindcircumstances.Inter-estingpeaksinheadingarefoundatlocationswheretugsfasten.ThefasteningoftugssometimesdisturbsthetransmittingofAISmessages,leadinginthiscasetosomepeaksinthevesselheading.

Thefactthatvesselsdoadapttheirheadingtokeeponcourseexplainswhythereisnotalotofdeviationfromtheaveragepath.Besidesthis,itdoesalsoexplainwhythevesselspeeddecreasesifthecrosswindspeedincreases.Becausethevesselscorrecttheirheading,theyareusingapartoftheirenginetocoun-terweightthewindforce.So,theyarenotusingtheirfullpowertosailahead;therebyreducingthevesselspeed.Anotherresultoftheadaptedheadingisthefactthatthepathwidthincreases.Thiscanalsohaveaninfluenceontheinteractionwithothervessels,asthevesselusesmorespace.Thisissueisnothandledinthisstudy,butitisworthwhiletoanalyseitinafuturestudy.

Alsotheinfluenceofwindcomingfrombehindorfromthefrontofthevessel(‘parallelwind’)isinvesti-gated.Thisisdoneinthesamewayasthecrosswindhandledabove.Figure6.8showsthefinalresults,inwhichalinearrelationshipisfoundandfitted.Thewindinfluenceishowevermuchlowerthanfoundforthecrosswinds.Thefactthatwindfrombehindleadstoahigherspeedfeelsverylogical.Thedeviationfromtheaveragepaththatisfoundishoweververylow(maximal11meters)andthelinearrelationshipdoesnotfitwell.Itisthereforedifficulttodrawsignificantconclusionsconcerningtheinfluenceofthiswindtypeonthevesselpath.

Page-64-

Externalinfluences

> 8 5.5−8 0−5.5 0−5.5 5.5−8 > 8 −10

−5

0

5

10

15

devi

a�on

from

ave

rage

trac

k (m

)

<-- Wind from behind (m/s).....wind from front (m/s) −−>> 8 5.5−8 0−5.5 0−5.5 5.5−8 > 8 −3

−2

−1

0

1

2

3

<-- Wind from behind (m/s).....wind from front (m/s) −−>

devi

a�on

from

ave

rage

spe

ed (%

)

Figure 6.8 The influence of parallel wind on the chosen path and vessel speed in the Maasmond.

Beerkanaal

IntheBeerkanaaltheinfluenceofwindisinvestigatedinthesamewayasfortheMaasmond.Figure6.9showstheinfluenceofcrosswindsatthislocation.ItcanbeseenthattheinfluenceonthevesselpathisthesameasfoundfortheMaasmond.Windcomingfromstarboardsideblowsthevesselsmoretowardsportsideandtheotherwayaround.Thedifferencesarehowevermuchlower(<10meters).Thelinearrelation-shipseemstofitbothgraphsinasufficientmanner.TheinfluenceonthevesselspeedisdifferentfromtheresultsfoundfortheMaasmond.Whenthewindblowsmorefromstarboardside,thevesselspeedseemstodecrease.Thelinearrelationshipdoesnotgiveagoodfitforthevesselspeedanditisalsoimpossibletofitothersimplerelationships.

> 8 5.5−8 0−5.5 0−5.5 5.5−8 > 8 −8

−6

−4

−2

0

2

4

6

8

o <-- Wind from port side (m/s).....wind from starboard side (m/s) -->

devi

a�on

from

ave

rage

trac

k (m

)

> 8 5.5−8 0−5.5 0−5.5 5.5−8 > 8 −4

−3

−2

−1

0

1

2

3

4

5

r <-- Wind from port side (m/s)......wind from starboard side (m/s) −−>

devi

a�on

from

ave

rage

spe

ed (%

)

Figure 6.9 The influence of crosswinds on the vessel path and vessel speed in the Beer-kanaal.

Page-65-


TheinfluenceofparallelwindisinvestigatedfortheBeerkanaalaswell(seeFigure6.10).AswasalsofoundintheMaasmond,thistypeofwinddoesnothavealotofinfluenceonchosenvesselpath.Itisaswellnotpossibletofindagoodandsimplerelationship.

> 8 5.5−8 0−5.5 0−5.5 5.5−8 > 8 −20

−15

−10

−5

0

5

o <-- Wind from behind (m/s).....wind from front (m/s) −−>

devi

a�on

from

ave

rage

trac

k (m

)

Figure 6.10 The influence of wind from behind and from the front of the vessel on the vessel path in the Beerkanaal.

Theinfluenceonthevesselspeedisanotherstory,asatthislocationthereisadifferencebetweenincom-ingandoutgoingvessels.Figure6.11showstheinfluenceoftheparallelwindontheincoming(left)andoutgoing(right)vessels.Clearlytheincomingvesselsfollowalinearrelationship,whereastrongwindfrombehindleadstoahighervesselspeedandastrongheadwindcausesalowervesselspeed.Foroutgoingvesselstherelationshipismorecomplex;inthefigureasecondorderpolynomialistriedtofit.Thisseemstogiveagoodapproximation.Thisisaninterestingresult,becauseitissimilartotheinfluencefoundattheMaasmond,butnowforparallelwindinsteadofcrosswind.

> 8 5.5−8 0−5.5 0−5.5 5.5−8 > 8 −6

−5

−4

−3

−2

−1

0

1

2

3

> 8 5.5−8 0−5.5 0−5.5 5.5−8 > 8 −4

−2

0

2

4

6

8

o

devi

a�on

from

ave

rage

spe

ed (%

)

<-- Wind from behind (m/s).....wind from front (m/s) −−> <-- Wind from behind (m/s).....wind from front (m/s) −−>

devi

a�on

from

ave

rage

spe

ed (%

)

Figure 6.11 The influence of parallel wind on the vessel speed in the Beerkanaal for incom-ing (left) and outgoing (right) vessels.

Page-66-

Externalinfluences

6.1.4 Conclusions

Thewindcircumstancesdefinitelyhaveaninfluenceonthevesselspeedandvesselpath.Thedeviationfromtheaveragevesselpathisnotverylarge,mainlybecausethevesselscorrecttheirheadingwhentheyareencounteringastrongcrosswind.Thisisconcludedbycomparingtheheadingofthosevesselswiththeaverageheading.Strongcrosswindsalsocauseadecreasedvesselspeed,asvesselsuseapartoftheirenginepowertocompensateforthewindforce.Moreinsidetheportarea,attheBeerkanaal,theinfluenceofcrosswindsisclearlylessthanattheMaasmond.

Windcomingfrombehindandfromthefrontofthevessel,parallelwind,hardlyinfluencesthevesselpath,butdoesinfluencethevesselspeed.Generally,headwindcausesadecreaseinvesselspeedandastrongerwindfrombehindthevesselleadstoahighervesselspeed.ExceptiontothisaretheoutgoingvesselsintheBeerkanaal.Thesevesselsshowadecreaseinvesselspeed,whenthewindisstronger,regardlessthedirec-tionoftheparallelwind.

6.2 Current

6.2.1 Currents in the case study area

Forthewindinfluence,itwasassumedthatthewindonlyvariesintime.Thisimpliedthatwithintheexaminedcasearea,thewindspeedandwinddirectionwereassumedtobeconstantoverthetotalarea,foracertainmomentintime.Forcurrentthisisnottrue,asthecurrentvariesintimeand inspace,bothhorizontallyandvertically.Thehorizontalvariationinspacedependsmainlyontheportsnauticalinfrastruc-ture.Theverticalvariationinspacedependsforalargepartontheinteractionbetweentheriver(NieuweWaterweg)andthetide.

Thesetwofactors(riverdischargeandtide)arethedrivingfactorsofthecurrentsthatoccurinthecasestudyarea,resultingindifferentdirectionsforthecurrentondifferentdepths.Thismightbeexplainedbythefollowing.Wherethesaltseawaterandthefreshriverwatermeeteachother,thefirstone‘dives’un-derthelayerofriverwater.Thisisbecausesaltwaterisheavierthanfreshwater.Becauseofthisprincipletherearemomentsintimewherethetoplayerofthewaterandthelayersbeneathhaveoppositecurrentdirections.Wheninalllayersthecurrentdirectionisapproximatelyequal,therecanstillbehugedifferencesincurrentvelocity.

6.2.2 Current data

FromthePortofRotterdam,dataisobtainedregardingtheexpectedcurentvelocitiesanddirectionsatthreedifferentsdepths.Thisinformationisknownfor10importantlocationsalongthecasetrajectory,fornormativetidalcyclesandriverdischarges(indicatedwithreddotsinFigure6.12.These10locationsaregrouped,bylookingatsimilaritiesintheircurrentregimes.Bydoingso,thehorizontalvariationinspaceistakenintoaccount.Finally,5differenttrajectoriesarepointedoutwhereasimilarregimeispresent(seeFigure6.12).Inpart5,theAmazonehaven,thecurrentinfluenceisnotfurtherinvestigated,asthecurrentvelocitiesareverylowatthislocation.

Page-67-


5.9 6 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.84.4

4.41

4.42

4.43

4.44

4.45

4.46

4.47

4.48

4.49

4.5

Part 1

Part 5

Part 2

Part 3

Part 4

Figure 6.12 Overview of the different current regimes in the case area.

The red dots indicate the points where current data is available

FromtheServicedeskData(Rijkswaterstaat)thewaterlevelsatthecaselocationareobtainedover2009.Bycouplingthesewaterlevelstothenormativecurrentinformation,thecurrentvelocityanddirectionisknownateverychosenlocation,forthethreedifferentdephts.Afterthis,selectionsaremadefromvesselsthathavesailedthroughthecaseareawhileencounteringdifferentcurrentvelocitiesanddirections.Whichlayers(depths)arechosentobetakenintoaccountforthisdependsonthevesselsize.

Thecurrentdirectionissplitupinto4categories,thesameasusedforthewindinfluence:currentfrombe-hind,front,portsideandstarboardside.Thecurrentvelocityissplitintothreeclasses(seeTable6.2).Theseclassesarechosen,becausenoweverysizeclasshasaboutthesameamountofvesseltracks.Theamountofvesseltracksinoneselectiondependsofcourseverymuchonthecurrentdirection.Hardlyanycrosscur-rentcanforexamplebefoundinpart2.

Table 6.2 Current velocity classes

ClassCurrentvelocity

(m/s)Currentvelocity

(kn)

I <0.3 <0.6

II 0.3-0.5 0.6-1.0

III >0.5 >1.0

6.2.3 Results

Theresultsaregiveninthesamewayasforthewindinfluence.Figure6.13showstheresultsfortheareaoutsidetheprotectionofthenorthernbreakwatertheinfluenceofcrosscurrentonthevesselpathandthevesselspeed.Theinfluenceonthevesselpathisveryclearandinlinewiththefindingsfortheinfluenceofcrosswind.Theinfluenceonthevesselspeedgivesamorescatteredimage.Thebestsimplefitisgivenbyasecondorderpolynomial,butitisobviousthatthisfitisfarfromperfect.

Page-68-

Externalinfluences

> 0.5 0.3−0.5 0−0.3 0−0.3 0.3−0.5 > 0.5−6

−5

−4

−3

−2

−1

0

1

2

3

devi

a�on

from

ave

rage

spe

ed (%

)> 0.5 0.3−0.5 0−0.3 0−0.3 0.3−0.5 > 0.5

−30

−25

−20

−15

−10

−5

0

5

10

15

<-- Current from port side (m/s)...current from starboard side (m/s) −−>

devi

a�on

from

ave

rage

trac

k (m

)


Figure 6.13 The influence of cross current on the vessel path (left) and speed (right) in part 1.

Althoughthedeviationfromtheaveragepathclearlyhasadowngoingtrend,theabsolutedeviationisnotverylarge,about25metersmaximal.Againthiscanbeexplainedbythefactthatvesseladapttheirhead-ingtostayoncourse.Thiswasalreadyfoundwheninvestigatingtheinfluenceofwind,butalsoduringhighcrosscurrentvelocitiesthevesselheadingissignificantlydifferentfromtheaverageheading.Figure6.14showsanexampleofthis,forthesizeclass40,000-70,000dwt.

Northern breakwater Start bend into Beerkanaal95

100

105

110

115

120

125

130

Development along average path -->

head

ing

(deg

rees

), 0

/ 36

0 =

Nor

th

Part 1 Part 2

Figure 6.14 Development of the vessel heading under influence of a strong cross cur-rent (green) compared to the average heading (blue), both for vessels of size class 40,000-70,000 dwt

TheinfluenceofthecurrentthatflowsparalleltothevesselisshowninFigure6.15.Bothgraphsdonothaveaperfectfitforalinearrelationship,butclearlyshowatrend.Thenegativevaluesforthedeviationfromtheaveragepath(leftfigure)indicatethatvesselssailmoretoportsidewhentheyexperienceastrongcurrentfrombehind.Inpracticethismeansthattheyaresailingmoretothemiddleofthewaterway.Thevesselspeeddecreaseswhenthecountercurrentincreases.

Page-69-


> 0.5 0.3−0.5 0−0.3 0−0.3 0.3−0.5 > 0.5−6

−5

−4

−3

−2

−1

0

1

2

3

<-- Current from behind (m/s).......current from front (m/s) −−>de

via�

on fr

om a

vera

ge s

peed

(%)

> 0.5 0.3−0.5 0−0.3 0−0.3 0.3−0.5 > 0.5−20

−10

0

10

20

30

40

devi

a�on

from

ave

rage

trac

k (m

)

<-- Current from behind (m/s).......current from front (m/s) −−>

Figure 6.15 The influence of parallel current on the vessel path (left) and speed (right) in part 1

Inpart2onlyparallelcurrentsarepresentduetothefactthatatthislocationthewaterwayisclosedatbothsides.Theinfluenceofthiscurrentonthevesselpathandvesselspeedissimilartotheinfluencefoundinpart1,butsmaller(seeFigure6.16).

> 0.5 0.3−0.5 0−0.3 0−0.3 0.3−0.5 > 0.5−6

−4

−2

0

2

4

6

devi

a�on

from

ave

rage

spe

ed (%

)

> 0.5 0.3−0.5 0−0.3 0−0.3 0.3−0.5 > 0.5−8

−6

−4

−2

0

2

4

6

8

10

12

devi

a�on

from

ave

rage

trac

k (m

)

<-- Current from behind (m/s).......current from front (m/s) --> <-- Current from behind (m/s).......current from front (m/s) -->

Figure 6.16 The influence of parallel current on the vessel path (left) and speed (right) in part 2

Inpart3,thebendattheentranceoftheBeerkanaal,andpart4(Beerkanaal)thecurrentvelocitiesaremuchlower.Alsotheinfluenceofthecurrentonthevesselpathandspeeddecreases.Forpart3,nosig-nificantinfluencesarefound.IntheBeerkanaal(part4)thereissomeinfluenceofparallelcurrent,mainlyregardingthevesselpath.Figure6.17showsthisresult,whichisquitesimilartothefindinginpart1and2.Thereisnosignificantinfluencefoundonthevesselspeedatthislocation.ThecrosscurrentsarehardlypresentintheBeerkanaal;thereforenoinfluenceofthesecurrentdirectionsisfound.

Page-70-

Externalinfluences

> 0.5 0.3−0.5 0−0.3 0−0.3 0.3−0.5 > 0.5−15

−10

−5

0

5

10

devi

a�on

from

ave

rage

trac

k (m

)

<-- Current from behind (m/s).......current from front (m/s) -->

Figure 6.17 The influence of parallel cur-rent on the vessel path in part 4 (Beerkanaal)

6.2.4 Conclusions

Itisverycomplextoanalysetheinfluenceofthecurrentonthevesselpathandvesselspeed.Thisisbe-causethecurrentishugelyaffectedbythelocalinfrastructure,especiallyinaportarea.Inthiscasealsotheinteractionbetweentheriverandtheseaisimportant:thisleadstoalargedeviationincurrentvelocityanddirectionoverthewaterdepth.Bysplittinguptheexaminedcaseareaandbyusingseveralsimplificationsitishoweverpossibletoobtainsomegoodresults.

Theinfluenceofcrosscurrentscouldonlybeobservedinpart1,outsidethenorhernbreakwater.Attheotherlocationscrosscurrentsarehardlypresent,duetothelocalinfrastructure.Inpart1theinfluenceofthecrosscurrentissimilartotheinfluenceofthewind.Thereisadeviationfromthevesselpathfound.Thisdeviationisnotverylarge,becausevesselsadapttheirheadinginordertostayoncourse.Theinfluenceofthecrosscurrentonthevesselspeedislessclear.

Currentcomingfrombehindorthefrontofavessel,parallelcurrent,hasaninfluenceaswell.Astrongcur-rentfrombehindmakesvesselssailmoretothemiddleofthewaterway.Astrongheadcurrentmakesthemsailmoretowardstheshore.Thevesselspeedisalsoaffected:astrongcurrentfrombehindincreasesthevesselspeedandtheotherwayaround.Thesefindingsaresupportedbytheresultsforpart1,part2andpart3.Inpart4,theBeerkanaal,onlytheconclusionsregardingthevesselpatharefound.

6.3 Visibility

6.3.1 Visibility data

Visibilitydatafor2009areobtainedfromtheKNMI.Theinvestigationoftheinfluenceofvisibilityismorestraightforwardthanforwindandcurrent.Visibilitydoesonlyvaryintimeandithasnodirectioninwhichitworks.ThevaluesforvisibilityaredefinedbytheKNMIasthe‘horizontalvisibilityatthetimeofobserva-tion’.Thisvisibilityisknownasthe‘meteorologicvisibility’andisdefinedasthelargestdistanceatwhichablackobjectcanbeseenandrecognised.Theintervalbetweentheobservationsisonehour.

Page-71-


Thevisibilityisnotsplitintodifferentclasses,asisdonewiththewindandcurrent.Thisisbecausebyfar,mostvesselsmeetclearvisibilityconditions.Onlywhenthevisibilitybecomesverylow,thereisanoticeableinfluence.Thisiswhythereareareonlytwoclassesmade:badvisibilityandsufficientvisibility.Badvisibilitymeansthatthemeteorologicvisibilityislowerthan2kilometers.Bycomparingthemomentsintime,theAISmessagesfromthevesselsandthevisibilitydataarecoupled.

6.3.2 Results

Forthedeterminationoftheinfluenceontheaveragepath,thecaseareaisagainsplitintotwoparts:the MaasmondandtheBeerkanaal.Forthecalculationofthedeviationfromtheaveragespeednosplitupofthecaseareaisused.Vesselsthatenterorleavetheportwithsufficientvisibilitydonotdeviatefromboththeaveragepathandaveragespeed.Forvesselsthatencounteradecreasedvisibilityaninfluenceispresent;itistriedtofindarelationshipbetweenthevesselsizeandthisinfluence.

IntheMaasmonditisnotpossibletofindaclearrelationshipbetweenthevesselsizeandtheinfluenceonthevesselpath.Thereishoweveracleardifferencebetweenincomingandoutgoingvessels.Incomingves-selsdonotsignificantlydeviatefromtheaveragepathduringtimesoflowvisibility.Contrarytothis,outgo-ingvesselsdohaveadeviationtostarboardside(theshore),intheorderof50meters.

IntheBeerkanaaltheinfluenceofthevesselsizeismoreobvious(seeFigure6.18).Thereisnodifferencebetweenincomingandoutgoingvessels.Thelineartrendlinefitsquitegoodandadowngoingtrendcanbeobserved.Inpractice,thismeansthatlargervesselssailmoretothemiddleofthechannelunderlowvis-ibilitycircumstancesthansmallervessels.

<10,000 10,000−40,000 40,000−70,000 70,000−100,000 >100,000−60

−50

−40

−30

−20

−10

0

10

20

Vessel size class (dwt) −−>

devi

a�on

from

ave

rage

trac

k (m

)

Figure 6.18 The influence of low visibility on the deviation from the average path in the Beerkanaal.

Fortheinfluenceoflowvisibilityonthevesselspeednosignificantdifferencesbetweenincomingandoutgoingvesselsarefound.Inthiscaseadivisioncanbemadeinsmallandlargevessels.Thesmallvessels,containingthesizeclasses<10,000dwt,10,000-40,000dwtand40,000-70,000dwtareclearlyhamperedbyalowvisibility.Thesevesselsdecreasetheirspeed,onaverage,with6%.Thelargervessels(sizeclasses70,000-100,000dwtand>100,000dwt)havenosignificantspeeddifference.

Page-72-

Externalinfluences

6.3.3 Conclusion

Itisdifficulttofindaveryclearrelationshipfortheinfluenceoflowvisibility.MostimportantfindingisthatvesselssailintheBeerkanaalmoretothemiddleofthewaterway,whenthevesselsizeincreasesincaselowvisibility.GoodrelationshipsforthedeviationsfromtheaveragepathintheMaasmondandfromtheaveragespeedarenotfound.Therearehoweveraveragevaluesobtainedthatgivesomeinsightinthisves-selbehaviour.

6.4 Conclusions

Forallthreeexternalcircumstancesinfluencesonthevesselpathandvesselspeedarefound.ThelargestdeviationsfromthevesselpatharefoundforcrosswindandcrosscurrentintheMaasmond,outsidetheprotectionoftheNorthernbreakwater.Thesedeviationsarelimited,becausevesselsadapttheirheadingtostayoncourse.Inthiswaytheypreventfrombeingblownor‘flowed’awaybythewindorcurrent.AsecondlargedeviationisfoundintheBeerkanaal,intimesoflowvisibility.Especiallylargervesselssailmoretothemiddleofthewaterwayinthesecircumstances.

Alsoforthedeviationfromtheaveragespeedtheinfluenceofwindandcurrentisquitesimilar.Highcross-windandcrosscurrentvelocitiesleadtoalowervesselspeed.Thisresultismostvisibleforwind,butalsothecurrentinfluenceshowsthispattern.Largewindandcurrentvelocitiesfrombehindleadtoahighervesselspeed,wherewindandcurrentfromthefrontcauseadecreasedspeed.

Exceptforthevisibility,nosignificantdifferencesbetweenthesizeclassesarefound.Thisismainlyduetoalackofdatawhensplittinguponesizeclassintoseveralselections.Insomeoftheseselections,therearenotalotofvesseltracksavailable.Thisiscausedbythelackofoccuranceofaexternalinfluence,forexamplewindfromtheeastorcrosscurrentintheBeerkanaal.Alsowhentheexaminedexternalinfluencedoesoccurfrequent,theamountofdataismostlytoosmalltodrawsignificantconclusionsforonlyonesizeclass.

6.3 6.35 6.4 6.45 6.5 6.55

4.425

4.43

4.435

4.44

4.445

4.45

4.455

X−posi�on in "Rijksdriehoeksgrid" [m]

Y−po

si�on

in "R

ijksd

rieho

eksg

rid" [

m]

x105

x104

Interaction

Chapter7

Page-74-

Interaction

7 Interaction

Oneoftheresearchquestionsistoinvestigatetheinfluenceofvessel-vesselinteractioninastatisticalway.Duetotimeconsiderationsthestatisticalanalysisofthisinteractionisnotperformed.Someresearchontheinfluenceofinteractionishoweverperformed,mainlytoshowhowindividualcasescanbefoundandanalysed.Forthisexaminationthesimilarcasestudyareaisused.

7.1 Interaction in the case study area

Vessel-vesselinteractiontakesplacewhenavesseldeviatesfromitsnormalpath,speedorheading,be-causeofthepresenceofanothervessel.Sometimesthevesselsreactoneachotherinanearlystage;thesesituationsaredifficulttotrackdown.Otherinteractionsituationsaremoreobviousandarealsomoreeasilyfound.InthetrackthatvesselssailbetweentheNorthSeaandtheAmazonehaven,thereareseveralplaceswhereinteractionislikelytooccur.ForexampleinthebendattheentranceoftheBeerkanaalorintheBeerkanaalitself.Amoredetaileddescriptionofthepathanditsinterestinglocations,togetherwithsometrafficimages,hasbeengiveninsection4.2.

Thefirststepistoidentifyinteractionsituations.Therearemainlytwowaystodoso,basedonthecalcula-tionprinciplesusedinthisthesis.Bothmethodsinvestigatedifferenttypesofvesselsthatareinvolvedintheinteraction.Thefirstway(MethodI)isbasedontheinteractionbetweentwocontainervesselsthatbothvisittheAmazonehaven.ThisanalysisusesCPA(ClosestPointofApproach)andTCPA(TimetoClosestPointofApproach)characteristics.Thesecondway(MethodII)investigatestheinteractionbetweenaves-selthatvisitstheAmazonehavenandavesselthatlikelydoesnot(thus,thissecondvesselisnotanalysedinthecasestudy).Thisanalysismakesuseofthecalculated‘outliers’,vesselsthatclearlydeviatefromtheaveragepathorspeed.

Inthecasestudyareaseveraltypesofinteractionarepresent.Theseareconnectedtothetypesofencoun-tersvesselscanexperience:head-on,crossingorovertaking.Allofthesetypesofinteractionwillbepresent,andshouldbelookedat,wheninvestigatingtheinfluenceofinteraction.

7.2 Method I

Ofallvesselsthatareanalysedinthecasestudy,alsodataareknownconcerningtheCPAandTCPA.TheCPAisthesmallestdistancethatvesselswillhavetoeachother,iftheykeeptheirheadingandspeedcon-stant.TheTCPAisthetimeuntilthismomentisreached(seeFigure7.1).Inpracticethesetwoparametersgiveanindicationaboutthepossibleclosestdistancetoothervesselsandthetimethatislefttoadaptcourseandspeed,ifthisdistanceistoosmall.

AsanoutputofShowRoute,theCPAandTCPAcanbeobtainedforeverycombinationoftwovesselsthatarerelativelyclosetoeachother.AverysmallCPAandTCPAindicatethattwovesselsareclosetoeachother;thereforevessel-vesselinteractionisexpected.Tofindsomeoftheseinteractionsituations,lowerlimitsaresetfortheCPAandTCPA.FortheCPAthislimitissetat0.05nauticalmile,roughly100meters.ThelimitfortheTCPAissetat5minutes.ItisalsoworthwhiletoreducetheCPAandTCPAevenmore.Inthiscase,onlyafewinteractionsituationwillbefound,buttheseareprobablyveryhelpfullintheanalysisofsituationswhereacollisionwasnarrowlyavoided(nearmisses).

Page-75-


Figure 7.1 Explanation CPA and TCPA

Closest Point of Approach, CPA (m)Distance

Vessel speed

TCPA = Distance / Vessel speed

Theselectionthatisobtainedbytheselimitsconsistsofseveralvesseltracks.Figure7.2showsthecombina-tionoftwooftheseinteractingtracksaroundtheentranceoftheBeerkanaal.Thebluelineshowstheindi-vidualtrackofanincomingvessel,fromthesizeclass70,000-100,000dwt.Theredlineindicatesthetrackofanoutgoingvessel,alsofromsizeclass70,000-100,000dwt.Thediscontinuouslinesshowtheaveragepathsforthissizeclass,incoming(blue)andoutgoing(red).Themarkersindicatesimilarmomentsintime,thetriangleindicatesthereforethepositionofthevesselswhentheyaretheclosesttoeachother.

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4.445

4.45

4.455


Y−po

si�on

in "R

ijksd

rieho

eksg

rid" [

m]

x105

x104

Figure 7.2 An example of interaction shortly before the entrance of the Beerkanaal

Afewthingscanbeconcludedfromthisexample.Firstofall,itisobviousthatthereisaninteractionbetweenthevessels,becausebothdeviateclearlyfromtheiroriginalpath.Thisisnotaverystrangecon-

Page-76-

Interaction

clusion,whenlookingatthedimensionsofthevessels.Botharelargecontainervesselsofthesizeclass70,000-100,000dwt.Theyhavetopasseachotherinarathernarrowwaterway.Thisconclusionisbasedonthedeviationfromtheaveragepath.Beforeitspathisdisturbedbytheoutgoingvessel,theincomingvesselsailsquiteclose(alittlebittothesouth)totheaveragepathofitssizeclass.Atacertainmomentitdeviatesquitestrongtotheshore;afterithastakenthebendintotheBeerkanaalitreturnsattheaveragetrack.Theoutgoingvesselundergoesaboutthesame.Atfirstinstance,italmostexactlyfollowstheaveragepath.Inthebenditdeviatesstronglytothestarboardsideoftheaveragepath.Contrarytotheincomingvessel,itdoesnotcomebackatthepathaftertheinteraction.Soinitscase,theinteractionhasastructuraleffect.

Theinteractionsituationhasnowbeendescribedqualitatively.Toobtainstatisticalequationsconcerningthevesselbehaviourduringaninteractionsituation,itisalsoimportanttodoquantitativeanalyses.Inthisanalysis,afewquestionsshouldbeanswered.First,atwhatdistanceinspaceand timedotheinteractionmanoeuvresstart.Whenthisisknown,itisimportanttoinvestigatewhatthebehaviourexactlyincludes.Thiscanbedescribedbyanadjustmentofthevesselspeed(knots/minute)andvesselheading(degreesperminute).Itshouldalsobederivedatwhatmoment(forexampleadistancebetweenthetwovesselsinvolved)theseadjustmentsareseenasbeingsufficient.Finally,thequestionshouldbeansweredhowves-selsbehaveaftertheinteractionsituationhaspassed.

Inthisexamplethefollowingresultsarefound.Theincomingvesselstartswithhisdivergentbehaviourwhenthedistancebetweenthetwovesselsisabout1000meters.Atthispointthetimetoclosestpointofapproachis1.5minute.Theoutgoingvesselalreadystartsdeviatingfromhispathwhenthedistancebetweenthevesselsisapproximately4kilometers.TheactionsthatareundertakenbytheincomingvesselcanbequantifiedbylookingatFigure7.3.OntheX-axisofthisfiguretheareainwhichtheinteractiontakesplaceisshown;thiscanbecomparedtotheX-axisofFigure7.2.Regardingthevesselspeedtwoconclusionscanbedrawn.First,thevesselsailsfasterthantheaverageofitssizeclass.Thisdeviation(±1knot)canhoweverbeexplainedbythenaturalspreadinvesselspeed.

6.38 6.4 6.42 6.44 6.46 6.48 6.5

114

115

116

117

118

119

120

Hea

ding

(deg

rees

)

6.38 6.4 6.42 6.44 6.46 6.48 6.56.5

7

7.5

8

8.5

9

9.5

Vess

el s

peed

(kno

ts)

X−posi�on in "Rijksdriehoeksgrid" [m] X−posi�on in "Rijksdriehoeksgrid" [m]

Figure 7.3 Development of the vessel speed (left) and vessel heading (right) compared to the average of the sizeclass 70,000-100,000 dwt (discontinuous line).

Page-77-


Thegraphontheright,theheading,givesagoodindicationhowthevesseldeviatesfromhispath.ClearlyaroundX=64,000mthevesselheadingquicklyincreasesandafterabout250meters,theheadinghasrisenwith4degreesfrom115degreesto119degrees.Thismeansthattheratiooftheheadingadjustmentisabout1degreeper60meters.Withavesselspeedof9knotsthisimpliesapproximately4degreesperminute.Inthefigureitcanbeseenthatafter600meters(X=65,000m.)theheadingisagainalmostthesameastheaverageheading.Atthatmoment,thedistancebetweenthevesselsis300meters.

Afterthevesselshavepassedeachother,theinteractionisover.Theresultsoftheinteractionarehow-everstillpresent.About2kilometersafterthevesselshavepassedeachother,theincomingvesselisbackaroundtheaveragetrack.Theoutgoingvesseldoesnotconvergetowardstheaveragetrackanymore.

Anotherremarkcanbemade.Theincomingvessel,thattakestheinnerbendintotheBeerkanaaldevi-ateslessfromitsoriginalpaththantheoutgoingvessel.Bothvesselssailbeforetheinteractionalongtheaveragepathoftheirsizeclass,byapproximation.Themaximaldeviationfromthisaveragepathisfortheincomingvessel100meters,fortheoutgoingvessel200meters.Thishasverylikelytodowiththespacethatisavailableforthevessels.Theincomingvesselisintheinnerbendandsailsalreadyquiteclosetothesideofthewaterway,whereastheoutgoingvesselhassome‘reserve’spaceleftathisstarboardside.

7.3 Method II

Asexplainedinthefirstsectionofthischapter,themethodIIinteractionsituationsarederivedbycalculat-ingoutliers.Theseoutliershavebeenfoundduringthecalculationoftheaveragevesselbehaviourinchap-ter5.Duringthiscalculationsomevesselswerefoundthathadsuchadifferentvesselpathorvesselspeed,thatthesewerecalledoutliers.Theideaisthatthelargedeviationsofthesevesselsoriginatefromthefactthattheyhadtoaltercourseorspeedbecauseofavessel-vesselinteraction.

TheCPAandTCPAdataisonlyknownforthevesseltracksthatwereinvestigatedinthecasestudy.Iftheoutliersindeedhadinteraction,thiswillverylikelynotbewithanotherinvestigatedvessel.Thisisbecausethesevesselsareonlyaverysmallpartofthetotalamountofvesselsthatsailthroughthecasearea.So,infirstinstancethereisnoinformationconcerningthevesselsthatpossiblyhadinteractionwiththedeter-minedoutliers.Toobtainthisinformation,thetotaltrafficimagearoundanoutlierisplayedinShowRoute(seeFigure7.4).

Page-78-

Interaction

Figure 7.4 Example of the interaction of an outliers (purple triangle) with another vessel, after plotting the whole traffic image.

Thisgivestwooptions.Thefirstoptionistoseewhethertherehavebeenvesselspresentthatsailedclosetotheoutliers.Secondly,ifinteractionsituationsareindeedfound,theinformationofinteractingvesselscanbeobtained.ThesecanthenbeusedtoproducethesamenumbersandfiguresasinmethodI,fromwhichaquantativeanalysiscanbeperformed.

7.4 Conclusion

Theexampleshowsthatitispossibletodoaquantitativeanalysisconcerningvesselbehaviourinaninter-actionsituation.Thedataderivedherearehoweveronlyvalidforthisspecificsituation.Forthederivationofstatisticalequations,itisneededtoobserveandanalysemanymoreofthesesituations.Differenttypesofinteractionshouldbeinvestigatedaswell.Thiswouldalsomakeitpossibletoincludethevesselspeedintheanalysis.Duetothelargenaturalspreadinvesselspeeditisdifficulttodrawconclusionsbasedonasmallnumberofsituations.

0 200 400 600 800 1000 12000

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

Loca�on on the waterway (m)

P (X

)

Cross sec�on 1 - C< 10,000 dwt

> 100,000 dwt

North South

Incoming: µ = 1100 m σ = 90 mOutgoing: µ = 460m σ = 120 m


Genericrules

Chapter8

Page-80-

Genericrules

8 Generic rules

Inthischapterthevesselbehaviouranalysedinthecasestudyistransformedintogenerallyapplicablerules.Inthiswaythevesselbehaviourinotherwaterwaysandportscanbedescribed,basedonthefind-ingsofthecasestudy.Togeneralisetheresultofthecasestudy,thefirstissuetobehandledisthemappingofthenauticalinfrastructure.Theinfrastructureisdifferentateverylocation.Thetrackofthecasestudyissplitinseveralpartsinsection8.1.Afterdealingwiththeinfrastructure,theaveragevesselbehaviourisgeneralised(section8.2)andtheexternalinfluencesareincluded(section8.3).

8.1 Defining waterways

Thetrackinthecaseareaissplitinto5differentparts,whichwerealsousedfortheexaminationoftheinfluenceofcurrent(seeFigure8.1).Inthissectionthedifferentpartsaregeneralisedtospecifictypesofwaterways.Itistriedtofindouterboundariesforeverypart,therebyfindingthewidthofthecharacterisedwaterway.Inthiswayitispossibletodescribethevessel’spositioninrelationtoitspositiononthewater-way.

5.9 6 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.84.4

4.41

4.42

4.43

4.44

4.45

4.46

4.47

4.48

4.49

4.5

Part 1

Part 5

Part 2

Part 3

Part 4

Figure 8.1 Overview of the different current re-gimes in the case area.

8.1.1 Part 1 - Outside the northern breakwater

Inthispartthewidthofthewaterwayisnotreallydefinedbyanacceptabledepth.ThefactthatvesselswanttoenterorleavetheportofRotterdam,andthereforeconvergetowardstheentranceoftheport,isnormative.Thereforethewidthofthewaterwayisdefinedbytakingacertainanglefromtheentranceoftheport.Thisanglehasbeendeterminedbylookingatthe98%contoursfromtheincomingandoutgo-ingvessels.Inportareaswherethesecontourlinesarenotavailable,thisangleshouldbedeterminedbyinvestigatingthedepthprofiles,navigationalaidspresent(e.g.buoys),theorigin,destination,expectedtypeandsizeofthevesselsthatvisitthatport.Whentherearesimilaritiesfoundwiththiscasestudyarea,thancontourlinesofthiscasestudycanbeusedtogiveafirstinsightintheangleoftheline.Sizeclass<10,000dwtischosenforthis,asthesevesselsusethewidestspaceandthereforehavethenormativecontourlines.Figure8.2showsthesecontours(red)andtheaveragepath(greendotted,incomingandoutgoing).Thebluelineshowsthedefinitionofthewidthofthewaterway.

Page-81-


5.9 6 6.1 6.2 6.34.45

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Y−po

si�o

n in

"Ri

jksd

rieh

oeks

grid

" [m

]

Figure 8.2 Overview of the simplified waterway (blue) in part 1.

Also indicated are the average path (green dash dotted), the 98% contours (red) and the buoys (red).

Byusingthe98%contours,itisinevitablethatsomevesselswillsailoutsidethedeterminedlimits.Othervesselswillsailveryclosetotheselimits.Theseouterlimitsshouldthereforenotseenasastrictborder.Vesseldonotrunagroundiftheygooutside.Thelimitsrepresentthemostlikelyareatocontainvesseltracks,whiletherearenonauticalinfrastructurerestrictions.

8.1.2 Part 2 - ‘Maasmond’

Thewaterwayinpart2isclearlyindicatedbybuoys.Bydrawingstraightlinesbetweenthosebuoys,itispossibletoobtainthewidthofthewaterway.Thiswidthisdecreasing,asallvesselsconvergetowardstheentranceoftheBeerkanaal.Figure8.3showsanoverviewofthebuoys(reddots)andthedeterminedwa-terway.Atsomelocations,the98%contourlinesarenotstraight,butquite‘peaky’.ThisisprobablybecauseoferrorsindisturbedAISmessages,causedbythefactthattugsfastentothecargovesselsatthatlocation.

6.2 6.25 6.3 6.35 6.4 6.45 6.5 6.554.435

4.44

4.445

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4.455

4.46

4.465

4.47


Y−po

si�o

n in

"Ri

jksd

rieh

oeks

grid

" [m

]

Figure 8.3 Overview of the simplified waterway in part 2.

Page-82-

Genericrules

8.1.3 Part 3 - Bend at entrance Beerkanaal

Alsothispartisdistinguishedasseparatepart,asthisiscompletelydifferentfromtherelativelystraightwa-terwaysintheMaasmondandBeerkanaal.Intheinnerbendaswellastheouterbend,buoysarepresentthatshowtheouterlimitsofthewaterway(seeFigure8.4).Thelimitsintheouterbendare‘cutof’,theselimitsdonotexistinreality,becausethisistheentrancetoanotherwaterway,theCalandkanaal.Inthiscaseuseismadeofabuoytopredictthelimitsofthewaterwayintheouterbend.Inotherportareas,thesenavigationalaidscouldbeusedaswell.Whenthesearenotpresent,the98%contourlinesgiveagoodindi-cation.Anotheroptionistoinvestigateandsettheouterbendtoacertaindistancefromtheinnerbend.

6.48 6.5 6.52 6.54 6.56 6.58 6.6 6.62

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4.438

4.44

4.442

4.444


Y−po

si�o

n in

"Ri

jksd

rieh

oeks

grid

" [m

]

Figure 8.4 Overview of the simplified wa-terway in part 3.

8.1.4 Part 4 - the Beerkanaal

TheschematisationofthewaterwayintheBeerkanaalisshowninFigure8.5.Thewidthisapproximatelyconstantforthewholesegment.OnlyattheentranceoftheAmazonehaven,thewidthdecreases.Useismadeofexistingbuoys,shorecontourlinesand98%vesselpathcontourstodeterminetheouterlimitsofthewaterway.Thispartisquitesimilartopart2,themaindifferenceisthefactthatthevesselnowap-proachtheirgoal,theAmazonehaven,whichinfluencestheirbehaviour(e.g.sailinginbackwards).

6.44 6.46 6.48 6.5 6.52 6.54 6.56 6.58 6.6 6.62 6.64

4.41

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4.42

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4.43


Y−po

si�o

n in

"Ri

jksd

rieh

oeks

grid

" [m

]

x10⁵

x10⁴

Figure 8.5 Overview of the simplified wa-terway in part 4.

Page-83-


8.2 Average behaviour

Withthetotaltrajectoryschematisedintodifferentparts,itispossibletoobtainthevessellocationwithrespecttothewaterway.Thedistributionofvesselsoveracrosssectioninthewaterwayishandled,aswellasthedistributionoveracrosssectionofthevesselspeed.Toobtainasufficientinsight,thesegeneraliseddistributionsarederivedforseveralcrosssectionsineverypart.Theshapeandsizeofmostofthesedistri-butionswasalreadyfoundinchapter5,butheretheyarecoupledtothesimplifiednauticalinfrastructure.

8.2.1 Part 1 - Outside the northern breakwater

Inthissectionanexamplewillbegivenhowthedistributionsofbothlocationandvesselspeedarederived.Fortheothercrosssectionsinthisandintheotherparts,thisapproachremainsthesame.Inpart1,4dif-ferentcrosssectionsareinvestigated(seeFigure8.6).AsanexampleCrosssection1-Ciselaboratedbelow.

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" [m

]

1 - A

1 - B

1 - D

1 - C

Figure 8.6 The cross sections that are investigated in part 1.

Atcrosssection1-C,thedeviationoverthewaterwayisinvestigated,forbothincomingandoutgoingves-selsfromsizeclasses<10,000dwtand>100,000dwt.Thenormaldistributionsarebasedontherealvesseltracks,asexplainedinchapter5.Figure8.7showsthesedistributions.Severalcharacteristicsareimportantinthederivationofgenericrules.First,thewidthofthewaterway.ThiscanbeseenontheX-axis(0isontheportsideoftheincomingvessels)andisatthislocationequalto1300m.Next,themeanandstandarddeviationofthedistributions.Itcanimmediatelybeseenthatthelargestsizeclasssailmoretothemiddleofthechannel.Thisresultsinasubstantialoverlapbetweentheincomingandoutgoingvesseldistributionforthissizeclass.Thesmallestsizeclasssailsmoretotheouterlimitsandhasalmostnooverlap.

Page-84-

Genericrules

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Loca�on on the waterway (m)

P (X

)

Cross sec�on 1 - C< 10,000 dwt

> 100,000 dwt

North South



Figure 8.7 Distribution over the waterway at cross section 1-C

Fromtheresultsshowninthefigure,itispossibletoformulaterulesregardingtheprobablepositionofavesselonthewaterwayinthiscrosssection,dependingonitssizeclass.Nexttothevesseldistributionoverthecrosssection,alsothevesselspeeddistributionshouldbeexamined.Thisisalsobasedontheresultsfromchapter5.Figure8.8showsthenormalisedspeeddistributionsincrosssection1-Cforthesmallestandlargestsizeclass,forincomingvessels.Thedistributionsaretruncatedinsuchawaythattheirtotalwidthisabout14knots.Moststrikingisthefactthatthesmallestvesselssailabout2knotsfasterthanthelargestvessels.Forthevesselspeedthemeanandstandarddeviationgiveenoughinformationtoformulategeneralisedrules.

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0.12

Vessel speed X (knots)

P (X

)

< 10,000 dwt

> 100,000 dwt

µ = 13.9 knσ = 2.1 kn

µ = 11.0 knσ = 2.4 kn

Figure 8.8 The speed distribution for incoming vessels at cross section 1-C

Theexampleshowsthatnowenoughinformationisavailabletocalculatetheprobabilitythatavessel,fromacertainsize,sailsataspecificlocationinthecrosssection,withaspecificspeed.Figure8.7andFigure8.8alsoofferinformationconcerningforexampletheoverlapbetweenincomingandoutgoingvessels.Allcrosssectionswillbehandledinthesamewayastheexampleabove.Theresultsarepresentedintables,inwhichthemostimportantcharacterics(mean,standarddeviation,widthofthewaterway)canbefound.

Page-85-


ThesetablescanbefoundinAppendixG;anexampleisgivenbelowforcrosssection1-C,Table8.1.

Table 8.1 Characteristics of the different size classes in cross section 1-C

Widthofthewaterway(B):1300meters

Sizeclass(dwt)

Incoming Outgoing

Spatialdistr.(m) Speeddistr.(kn) Spatialdistr.(m) Speeddistr.(kn)

Mean(μ) StDev(σ) Mean St Dev Mean St Dev Mean St Dev

<10,000 1100 90 13.9 2.1 460 120 14.7 2.1

10,000-40,000 1080 100 14.6 2.4 520 130 15.0 2.1

40,0000-70,000 1000 90 11.1 1.5 560 120 13.6 2.3

70,000-100,000 980 90 10.6 1.8 600 140 12.0 2.4

>100,000 970 90 11.0 2.4 630 160 14.3 2.0

μ/B σ/B μ/μV0 σ/σV0 μ/B σ/B μ/μV0 σ/σV0

<10,000 0.85 0.07 0.96 1.11 0.35 0.09 1.06 0.95

10,000-40,000 0.83 0.08 0.97 1.14 0.40 0.10 1.02 0.84

40,0000-70,000 0.77 0.07 0.93 0.65 0.43 0.09 1.03 0.92

70,000-100,000 0.75 0.07 0.92 0.82 0.46 0.11 1.04 1.26

>100,000 0.75 0.07 0.87 0.89 0.48 0.12 1.05 0.87

InthesecondpartofTable8.1ageneralisationismadetorespectivelythewidthofthewaterwayandthe‘starting’vesselspeedcharacteristics.Thewidthofthewaterwaythatisusedisindicatedatthetopofthetable.The‘starting’vesselspeedcharacteristicsused,arethemean(μV0)andstandarddeviation(σV0)ofthevesselspeedincrosssection1-A(seeTable8.2).Bydividingthemeanandstandarddeviationofthevesselspeedwiththeoriginalmeanandstandarddeviation,insightintothedevelopmentofthevesselspeedisobtained.

Table 8.2 Vessel speed characteristics of the different size classes in cross section 1-AWidthofthewaterway:3000meters

Sizeclass(dwt)

Incoming Outgoing

Speeddistr.(kn) Speeddistr.(kn)

μV0 σV0 μV0 σV0

<10,000 14.5 1.9 13.9 2.2

10,000-40,000 15.1 2.1 14.7 2.5

40,0000-70,000 11.9 2.3 13.2 2.5

70,000-100,000 11.5 2.2 11.5 1.9

>100,000 12.6 2.7 13.6 2.3

8.3 External influences

Theexternalcircumstancesdonotchangetheshapeofthenormaldistributionsthatarefoundforthespa-tialandspeeddistributions.Thisisbecausetheinvestigationoftheexternalinfluencesinchapter6didnotincludethe individualdeviationfromtheaveragepathandspeed.Thiswasnotpossible,becausetherewas

Page-86-

Genericrules

notenoughdatainmostselectionstoobtainsignificantresults.Inmostcases,nodifferencesbetweensizeclassesarefound.Thereisoneexceptiontothis,theinfluenceofvisibilityonthevesselspeed.

Theabovementionedmeansthattheexternalcircumstancesmainlycauseashiftofthenormaldistribu-tions.Thesizeoftheshiftdependsontheexternalinfluenceitself.Inchapter6already,mostlylinear,relationshipswerefound.Theyhavetobetransformedtoobtainamoregeneralinsightintheexternalinfluence.Figure8.9showswhatismeantbythistransformation.Theleftfigureistheoriginalinfluence,asfoundinchapter6.Therightfigureshowsthegeneralisedinfluence,inwhichtheX-axisisnolongerdividedin6sizeclasses.ThevaluesontheY-axisseemlarger,butthisisbecausetheresultsareextrapolated.Withthisrelationshipitispossibletoadaptthespatialvesseldistributiontothecurrentthatispresentatacer-tainmomentintime.

<-- Current from port side (m/s).......current from starboard side (m/s) -->

Part 1 - Outside the northern breakwater

> 0.5 0.3−0.5 0−0.3 0−0.3 0.3−0.5 > 0.5−30

−25

−20

−15

−10

−5

0

5

10

15


devi

a�on

from

ave

rage

trac

k (m

)

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−40

−30

−20

−10

0

10

20

30

devi

a�on

from

ave

rage

trac

k (m

)

Figure 8.9 The influence of cross current on the vessel path at part 1.

Theinfluenceofthecrosscurrentatpart1isanexampleofhowtheinfluencesaregeneralised.Theotherinfluencesandlocationsareelaboratedinthesameway.ThesegraphscanbefoundinAppendixG.

8.4 Implementation in maritime models

InSection3.5,thecharacteristicsoffourmaritimemodelswerediscussed,concerningthepossibilitytoim-plementtheresultsofthisthesis.Forthedescriptionofthemodels,thefollowingissueswerementioned:

Type1-Nauticalinfrastructure Describelateralvesseldistributionoveracrosssectionoverthewaterway. Describethevesselspeeddistributionoverandinacrosssectionoverthewaterway. Type2-Vesselrelatedcharacteristics Distinguishbetweenstaticcharactericsasvesselsizeandvesseltype. Distinguishbetweendynamiccharacteristics,forexamplevesseldestination. Type3-Externalcircumstances Takeexternalinfluenceslikewind,currentandvisibilityintoaccount. Type4-Interactionwithothervessels Abilitytoincludedeviationfromthepredefinedpathandspeedbecauseofinteractionwithother vessels.

Nowtheresultsofthecasestudyareknown,thesetypescanbeelaboratedabitfurther.Type1,thenauti-

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calinfrastructure,isdescribedindetailinthecasestudy.Resultshavebeenobtainedconcerningthevesselandvesselspeeddistributionoverthewaterway,dependentonthetypeandwidthofthespecificwater-way.Type2,thevesselcharacteristicsaretreatedpartly,asonlytheinfluenceofvesselsizeanddestination(tosomeextent)aretreated.Resultsforthedestinationareobtainedtosomeextent,asthesailingdirec-tionofvessels(incomingoroutgoing)hasbeentakenintoaccount.

Externalcircumstancesdonotchangethesizeandshapeofthevesseldistributions,butshiftthemtoport-sideorstarboardside.Thevessel-vesselinteraction,type4,isnotelaboratedstatistically.Althoughexam-plesaregivenhowtofindandanalysethesesituations,nostatisticalresultsareavailable.

Thefirstmaritimemodelhandledinchapter3wasSAMSON.Thismodelisabletoincludetheresultsfromthecasestudyconcerningthetype1,type2andtype3characteristics.ThemaindisadvantageofSAMSONistheinabilitytosimulatethenauticaltraffic.Thischaracteristicishowevermainlyneededforthemodel-lingofinteraction.Becausenointeractionresultsarefound,thisisnotalargedrawbackfortheimplemen-tationoftheavailablecaseresults.However,ifafuturestudywouldobtainmoreinsightintheprocessofvessel-vesselinteraction,simulatingnauticaltrafficispreferable.

ForHarbourSim,themostseriousdrawbackswerethe(speed)distributionoverthewaterway.Becauseseveralresultsarefoundforthisdistributionoverthewaterway,themodelshouldbeadjustedlargelytobeabletoimplementthis.AlsotheinteractionisverylimitedinHarbourSim,butsinceinteractionresultshavenotbeendetermined,thisisnoproblematthemoment.Again,futurestudiesmightchangethis.

MARTRAMwasfoundtomeetmostofthecriteriamentioned.Themodelsimulatesthenauticaltrafficandthereisadistributionoverthewaterway,alsoforvesselspeed.Thedistributionsusedshouldbeadaptedtotheresultsfoundinthecasestudy.Ifthisisdone,itcanalsohandletheinfluenceoftheexternalcircum-stances.MARTRAMalsosimulatesinteraction,butonlyinverylimitedway(vesselscanonlyreducespeed).Iflateroninteractionresultsarefound,MARTRAMshouldbeextendedtocopewiththis,butatthemo-mentthemodelkeepsupwiththecriteria.

Thefourthmodelthatwasinvestigated,Dymitri,simulatesnauticaltrafficinmostdetail.Itrunsonbehav-iouralrules,thatarebasedonthesimulationofthehumanbrain.Thismakesitdifficulttoimplementtheresultsthatarefoundinthecasestudy.Theresultsthatarefound(mainlydistributionsandfactorsthatinfluencethesedistributions)arenotlinkedtobehaviouralrules.Inotherwords,Dymitriisnotbasedoncertaindistributionsoverthewaterway,butonthedecisionsofindividualvessels.Contrarytothis,resultsoffutureinteractionresearchcanbeimplementedmoreeasilyinthemodel.Thisisbecausetheseresultswillbemorelikebehaviouralrules,astheyareclosertothe(casespecific)natureoftheinteractionprocess.

8.5 Conclusions

Theresultsofthecasestudyhavebeenusedtoderivegenericrulesregardingthevesselpathandves-selspeedinsideaportarea.Forthis,thetotaltrajectorybetweenNorthSeaandAmazonehavenissplitintodifferentcharacteristicwaterways.Itisnotalwayspossibletoassignreal,physicalouterlimits.Thisisbecausesometimesthephysicalrestrictions,likedepth,arenotnormative.Thisisforexamplethecaseoutsidethebreakwater,whenvesselsconvergetowardstheportentrance.

Thevesselpathandspeedaredescribedbynormaldistributions,obtainedinchapter5.Visualrepresenta-tionsofthesedistributionsquicklygiveinsightintodifferencesbetweensizeclassesandbetweenincomingandoutgoingvesselsfromonesizeclass.Theexternalinfluencesaregeneralisedand,inmostcases,causea

Page-88-

Genericrules

horizontalshiftofthespatialandspeeddistributionforeverysizeclass.

Thegenericrules,thatarederivedfromthecasestudy,canbeimplementedmosteasilyinamodellikeMARTRAM.AmodellikeSAMSONdoesnotsimulatenauticaltraffic,becausethisisnotthepurposeofthemodel.Thisisespeciallydifficultinthelightofapossiblyincreasedfutureinsightintheinteractionprocess,whereasnowadaysSAMSONwouldbesufficientlyabletoimplementtheresultsofthecasestudy.Harbour-Simdoesnotallowdeviationfromtheaveragepath,animportantresultofthecasestudy.Dymitrisimu-latesthenauticaltrafficingreatdetail,buttheapproachofthemodelisdifferentthanwhatfollowsfromtheresultsfromthecasestudy.

Chapter 9

Conclusions&recommendations

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Conclusions&recommendations

9 Conclusions & recommendations

9.1 Conclusions

AfterperformingtheAISanalysisandformulatinggenericresults,finalconclusionscanbedrawn.Theyaresplitupinsuchawaythattheseparateresearchquestionsareansweredand,finally,theproblemdefinitionoftheresearchishandled.

AIS and maritime models

ThisresearchquestionwasdividedintothepossibilitiesandlimitationsofAIS,characteristicsofmaritimemodelsandtheuseofAISinmaritimemodelling.NexttothemainfunctionsofAIS,beingcollisionavoid-anceandnavigationalaid,thesystemisalsousedinmaritimemodelling.Untilnow,AISdataaremainlyusedtodeterminethenauticaltrafficinput(e.g.interarrivaltime)andthebehaviourofnauticaltrafficatalargerscale(e.g.insightintothetrafficnetwork).Notmuchuseismadeofthepossibilitytoobtaininsightintoindividualvesselbehaviour,somethingwhatisdoneinthisthesis.Indoingso,itispossibletodealwiththehumanfactorinmaritimemodels.ProblemsthatexistwhenusingAISdatainthesemaritimemodelsarecausedbythefactthatsomeAISdatacontainerrorsandthereforearenotcompletelyreliable.

AIS data analysis

Thisresearchquestionwasdividedintotheinfluencesofvesselsize,externalinfluencesandinteractiononthevesselpathandvesselspeed.ThisstudyhasshownthepossibilitiestodescribetheindividualvesselbehaviourintheportofRotterdamareastatistically,byusingananalysisofAISdata.Inthisthesisthebe-haviourinaspecificcaseareaisinvestigated,butitisalsopossibletodosofortheotherareasintheportofRotterdam.Theinvestigatedfactorsvesselsize,wind,currentandvisibilityallhaveasignificantinfluenceonthevesselpathandspeed.Noconclusionsregardingtheinteractioncanbemade,asnostatisticalanalysisofthevessel-vesselinteractionhasbeenperformed.

Generic rules

Thisreserachquestionwasdividedintothetransferfromspecifictogenericrulesandthepossibilitytoimplementtheminmaritimemodels.Withtheapproachusedinthisthesis,itispossibletoobtaingenericrulesthatdescribethevesselpathandvesselspeedinaportarea.Todoso,thecasestudyareaissplitintoseveralcharacteristicwaterwaysegmentsandthelocationspecificresultsaregeneralisedtotheirspecificsegments.Currentlyexistingmaritimemodelsarenotabletodirectlyimplementthegenericrulesfound,butwithasmallnumberofadjustmentsitispossibleforsomeofthemtodoso.

Finally,itcanbeconcludedthatbyusingananalysisofAISdata,clearlymoreinsightisobtainedinthede-tailedindividualvesselbehaviour.Thisunderstandingofthebehaviourcanbeformulatedingenericrules.Theserulescanbeimplementedinmaritimemodels,whichimprovesthesimulationoftheindividualvesselpathandvesselspeed.

9.2 Recommendations

ThisthesishasshownthatitispossibletoobtaininsightinvesselbehaviourbyusingAISdata.Oneofthemainfinalgoalsofthethesisistousethisinsighttoobtaingenericrules,whichcanbeimplementedinamaritimemodel.Somerulesarederivedinthisthesis,butthereareseveralissueswherefurtherresearchisneeded.

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Firstofall,onlycontainervesselsareinvestigatedinthecasestudy.Othertypesofvesselswillhavediffer-entbehaviour,astheyhaveotherdimensions.Forexampledrybulkvessels,thathavealargerdepthandasmallerheight.Thismakesthem,theoretically,moresensitivetotheinfluenceofcurrentsandlesssensitivetowind.Thissamedepthcouldalsorestrictthemmoretothemiddleofthewaterway,wherealargerwaterdepthcouldbeexpected.

Rulesconcerningtheinfluencesofexternalcircumstancesareobtainedinthisthesis.Additionalresearchwouldhoweverbeverybeneficialfortheinsightintotheseandotherexternalinfluences.First,onlywind,currentandvisibilityareexamined,asthesewereexpectedtobethemostimportantinthecasestudy.Thevisibilitydatainthecasestudydependedmainlyonthepresenceofweatherinfluenceslikefogandrain.Thequestionifavesselsailedbydaylightornot,isnottakenintoaccount.Thisisaninterestingissue,asvesselsmightbehavedifferentlyiftheysailbynight(despitegoodlightingintheportarea).Theinfluenceofwavesisalsoapossiblesubjectoffutureresearch,butitisofminorimportancewhenlookingataportarea;thereforethisisnotafirstnecessity.

Fortheexternalinfluences,thereisnorelationshipfoundbetweenthedifferentsizeclasses(exceptforvisibility).Itmightbethecasethatthereisnoclearrelationship,butitismorelikelythat-tosomeextent-arelationshipexist.Thereishoweveralotofdataneededbeforethiscanbeshownstatistically,astheinflu-enceoftheexternalcircumstancesonthevesselpathandspeedissmallcomparedtothenaturaldeviationfromtheaverage.Anothercharacteristicthatshouldbelookedatmorecloselyisthepathwidth,ascrosscurrentsandcrosswindscausealargerpathwidth.Moreresearchisthereforeworthwhile.Thisresearchshouldnothaveacaseareabetweentheseaandaterminal,butshouldfocusonaspecificwaterwayseg-ment.Everyvesselthatsailsthroughthissegmentshouldbeanalysed;inthiswayenoughdatacouldbeobtained.

Thegenericrulesthatareobtainedinthisthesisdescribethevesselpathandvesselspeedbyusingdistribu-tionsoverdifferentcrosssections.Amaritimemodelshouldbeabletousethesedistributionstosimulatenauticaltraffic.Atthemoment,noresearchisdoneontherelationofthevessel’spositionbetweentwosuccessivecrosssections.Amaritimemodelneedsthisinformationbeforeitcansimulateindividualvessels.

Nostatisticalresultsofvessel-vesselinteractionareobtainedinthecasestudy.Thisisthenextstepinobtaininginsightinthevesselbehaviourinportareas.Anexamplehasalreadyshownthatitispossibletotrackdowninteractionsituationsandhowtheycanbeanalysed.Toobtainstatisticalvalidresultshowevermanymoresituationsshouldbeelaborated.

References

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References

References

Bailey,N.J.,N.Ellis,N.andSampson,H.(2008):TrainingandTechnologyOnboardShip:HowseafarerslearnedtousetheshipboardAutomaticIdentificationSystem(AIS),Cardiff,Lloyd’sRegisterEduca-tionalTrustResearchUnit,SeafarersInternationalResearchCentre(SIRC)andCardiffUniversity.

Barauskis,G.andFriis-Hansen,P.(2007):Baysiannetworksforshipsmanoeuvringcontrol,SafetyatSeaproject,Coastal,MaritimeandStructuralEngineering/MEK,TechnicalUniversityofDenmark.

Bolt,E.(2006):Modeldescriptions,Safetyatseaproject.strand1,reportNo1.08.http://www.safetyatsea.se/index.php?section=results

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Friis-Hansen,P.andSimonsen,B.C.(2001):GRACAT:softwareforgroundingandcollisionriskanalysis, MarineStructures15:383-403.

Fujii,Y.,Yamanouchi,H.andMizuki,N.(1974):SomeFactorsAffectingtheFrequencyofAccidentsinMarineTraffic.II–TheProbabilityofStrandingandIII–TheEffectofDarknessontheProbabilityofCollisionandStranding,JournalofNavigation27(2):239-247.

Harati-Mokhtari,A.,Wall,A.,Brooks,P.,Wang,J.(2007):AutomaticIdentificationSystem(AIS):DataReli-abilityandHumanErrorImplications,JournalofNavigation60:373-389.

Groenveld,R.(2001).ServiceSystemsinPortsandInlandWaterways.Delft,TUDelft,FacultyCiTG.

IALAandAISM(2004):IALAguidelineNo.1028onTheAutomaticIdentificationSystem(AIS),Volume1,PartI:Operationalissues,Ed.1.France.

Iperen,W.H.van,Koldenhof,Y.,Saladas,J.,Tak,C.vander(2008):NetwerkevaluatieNoordzee2008.Wage-ningen,Marin.

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Kujala,P.,Hänninen,M.,Arola,T.,Ylitalo,J.(2009):AnalysisofthemarinetrafficsafetyintheGulfofFin-land,ReliabilityEngineeringandSystemSafety94:1349-1359.

Macduff,T.(1974):Theprobabilityofvesselcollisions,OceanIndustry1974:144-148.

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Pedersen,P.T.andZhang,S.(1999):CollisionAnalysisforMSDEXTRA.MSDEXTRA.Lyngby,DepartmentofNavalArchitectureandOffshoreEngineering,TechnicalUniversityofDenmark.

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Pimontel,L.(2007):Astudyintomaritimecollisionprobability,CEG,Delft,DelftUniversityofTechnology,MScthesis.

Seignette,R.W.P.(2005):Comprehensivetrafficmodelling,InternationalConferenceonPort-MaritimedevelopmentandInnovation,WTC,Rotterdam

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Tak,C.Vander(2009):Safetyassessmentstudyforoffshorewindfarmducalvados.Wageningen,Marin:12-19.

Ylitalo,J.(2009):Ship-ShipcollisionprobabilityofthecrossingareabetweenHelsinkiandTallin.Helsinki,HelsinkiUniversityofTechnology.

Appendices

Page-A2-

Appendices

Appendix A Safetyatsea................................................................................................... A7

Appendix B DatainanAISmessage................................................................................ A11

Appendix C ApplicationsandpossibilitiesofAIS............................................................ A15

Appendix D MatlabmodelfortheAISanalysis............................................................... A19

Appendix E χ2tests,skewnessandexcesskurtosis......................................................... A29

Appendix F Vesselandvesselspeeddistributions.......................................................... A35

Appendix G Genericrules................................................................................................ A53

Table of contents

Page-A3-


FigureC.1 Theprincipleofaradardirectionfinder(left)andRadarwavesblockedbyan-othervessel(right)........................................................................................................ A19

FigureC.2 AISSART,asdevelopedbyJotronAS................................................................... A19FigureD.1 GUItomakeavesseltrackselection.................................................................... A24FigureF.1 Vesseldistributionovercrosssections1-4forincomingvesselsfromsizeclass

<10,000dwt.................................................................................................................. A38FigureF.2 Vesseldistributionovercrosssections1-4foroutgoingvesselsfromsizeclass

<10,000dwt.................................................................................................................. A39FigureF.3 Vesseldistributionovercrosssections1-4forincomingvesselsfrom

sizeclass10,000-40,000dwt......................................................................................... A39FigureF.4 Vesseldistributionovercrosssections1-4foroutgoingvesselsfrom

sizeclass10,000,40,000-dwt........................................................................................ A40FigureF.5 Vesseldistributionovercrosssections1-4forincomingvesselsfrom

sizeclass40,000-70,000dwt......................................................................................... A40FigureF.6 Vesseldistributionovercrosssections1-4foroutgoingvesselsfrom

sizeclass40,000-70,000dwt......................................................................................... A41FigureF.7 Vesseldistributionovercrosssections1-4forincomingvesselsfrom

sizeclass70,000-100,000dwt....................................................................................... A41FigureF.8 Vesseldistributionovercrosssections1-4foroutgoingvesselsfrom

sizeclass70,000-100,000dwt....................................................................................... A42FigureF.9 Vesseldistributionovercrosssections1-4forincomingvesselsfromsizeclass

>100,000dwt................................................................................................................ A42FigureF.10 Vesseldistributionovercrosssections1-4foroutgoingvesselsfromsizeclass

>100,000dwt................................................................................................................ A43FigureF.11 Vesselspeeddistributiononlocation1-4,forincomingvesselsfromsizeclass

<10,000dwt.................................................................................................................. A44FigureF.12 Vesselspeeddistributiononlocation1-4,foroutgoingvesselsfromsizeclass

<10,000dwt.................................................................................................................. A44FigureF.13 Vesselspeeddistributiononlocation1-4,forincomingvesselsfrom

sizeclass10,000-40,000dwt........................................................................................ A45FigureF.14 Vesselspeeddistributiononlocation1-4,foroutgoingvesselsfrom

sizeclass10,000-40,000dwt........................................................................................ A45FigureF.15 Vesselspeeddistributiononlocation1-4,forincomingvessels

fromsizeclass40,000-70,000dwt................................................................................ A46FigureF.16 Vesselspeeddistributiononlocation1-4,foroutgoingvessels

fromsizeclass40,000-70,000dwt................................................................................ A46FigureF.17 Vesselspeeddistributiononlocation1-4,forincomingvessels

fromsizeclass70,000-100,000dwt.............................................................................. A47FigureF.18 Vesselspeeddistributiononlocation1-4,foroutgoingvessels

fromsizeclass70,000-100,000dwt.............................................................................. A47

List of figures

Page-A4-

Appendices

FigureF.19 Vesselspeeddistributiononlocation1-4,forincomingvesselsfromsizeclass>100,000dwt................................................................................................................ A48

FigureF.20 Vesselspeeddistributiononlocation1-4,foroutgoingvesselsfromsizeclass>100,000dwt................................................................................................................ A48

FigureF.21 Vesselspeeddistributionovercrosssections1-4,forincomingvessels fromsizeclass<10,000dwt.......................................................................................... A49

FigureF.22 Vesselspeeddistributionovercrosssections1-4,foroutgoingvessels fromsizeclass<10,000dwt.......................................................................................... A49

FigureF.23 Vesselspeeddistributionovercrosssections1-4,forincomingvessels fromsizeclass10,000-40,000dwt................................................................................ A50

FigureF.24 Vesselspeeddistributionovercrosssections1-4,foroutgoingvessels fromsizeclass10,000-40,000dwt................................................................................ A50

FigureF.25 Vesselspeeddistributionovercrosssections1-4,forincomingvessels fromsizeclass40,000-70,000dwt................................................................................ A51

FigureF.26 Vesselspeeddistributionovercrosssections1-4,foroutgoingvessels fromsizeclass40,000-70,000dwt................................................................................ A51

FigureF.27 Vesselspeeddistributionovercrosssections1-4,forincomingvessels fromsizeclass70,000-100,000dwt.............................................................................. A52

FigureF.28 Vesselspeeddistributionovercrosssections1-4,foroutgoingvessels fromsizeclass70,000-100,000dwt.............................................................................. A52

FigureF.29 Vesselspeeddistributionovercrosssections1-4,forincomingvessels fromsizeclass>100,000dwt........................................................................................ A53

FigureF.30 Vesselspeeddistributionovercrosssections1-4,foroutgoingvessels fromsizeclass>100,000dwt........................................................................................ A53

FigureG.1 Thecrosssectionsthatareinvestigatedinpart1................................................ A56FigureG.2 Thecrosssectionsthatareinvestigatedinpart2................................................ A58FigureG.3 Thecrosssectionsthatareinvestigatedinpart3................................................ A60FigureG.4 Thecrosssectionsthatareinvestigatedinpart4............................................... A62FigureG.5 InfluenceofcrosswindsintheMaasmondontheaveragepath.Theleftfigure

showsthesplitupindifferentwindspeedclasses...................................................... A64FigureG.6 InfluenceofcrosswindsintheMaasmondontheaveragespeed.Theleftfigure

showsthesplitupindifferentwindspeedclasses...................................................... A64FigureG.7 InfluenceofparallelwindsintheMaasmondontheaveragepath.Theleftfig-

ureshowsthesplitupindifferentwindspeedclasses................................................ A65FigureG.8 InfluenceofparallelwindsintheMaasmondontheaveragespeed.Theleft

figureshowsthesplitupindifferentwindspeedclasses............................................ A65FigureG.9 InfluenceofcrosswindsintheBeerkanaalontheaveragepath(left)andspeed

(right)............................................................................................................................ A66FigureG.10 InfluenceofparallelwindsintheBeerkanaalontheaveragepath................... A66FigureG.11 InfluenceofparallelwindsintheBeerkanaalontheaveragespeed,forincom-

ing(left)andoutgoing(right)vessels.......................................................................... A67FigureG.12 Influenceofcrosscurrentinpart1onthevesselpath(left)andvesselspeed

(right)............................................................................................................................ A67

Page-A5-


FigureG.13 Influenceofparallelcurrentinpart1onthevesselpath(left)andvesselspeed(right).................................................................................................................. A68

FigureG.14 Influenceofparallelcurrentinpart2onthevesselpath(left)andvesselspeed(right).................................................................................................................. A68

FigureG.15 Influenceofparallelcurrentinpart4onthevesselpath................................. A69

Page-A6-

Appendices

TableB.1 DatainanAISmessage.......................................................................................... A12TableE.1 ExampleofapartoftheChi-squaredistributiontable.......................................... A31TableE.2 χ2testsperformedforthevesseldistributionsoverthecrosssectionsonlocation

1-4,Sizeclass<10,000dwt.......................................................................................... A31TableE.3 χ2testsperformedforthevesseldistributionsoverthecrosssectionsonlocation

1-4,Sizeclass10,000-40,000dwt................................................................................ A31TableE.4 χ2testsperformedforthevesseldistributionsoverthecrosssectionsonlocation

1-4,Sizeclass40,000-70,000dwt................................................................................ A32TableE.5 χ2testsperformedforthevesseldistributionsoverthecrosssectionsonlocation

1-4,Sizeclass70,000-100,000dwt.............................................................................. A32TableE.6 χ2testsperformedforthevesseldistributionsoverthecrosssectionsonlocation

1-4,Sizeclass>100,000dwt........................................................................................ A32TableE.7 χ2testsperformedforthevesselspeeddistributionsoverthecrosssectionson

location1-4,Sizeclass<10,000dwt............................................................................. A32TableE.8 χ2testsperformedforthevesselspeeddistributionsoverthecrosssectionson

location1-4,Sizeclass10,000-40,000dwt.................................................................. A33TableE.9 χ2testsperformedforthevesselspeeddistributionsoverthecrosssectionson

location1-4,Sizeclass40,000-70,000dwt.................................................................. A33TableE.10 χ2testsperformedforthevesselspeeddistributionsoverthecrosssectionson

location1-4,Sizeclass70,000-100,000dwt................................................................ A33TableE.11 χ2testsperformedforthevesselspeeddistributionsoverthecrosssectionson

location1-4,Sizeclass>100,000dwt........................................................................... A33TableE.12 Skewnessforthevesselspeeddistributionsoverthecrosssectionsatlocations

1to4,,forthedifferentdatasetsatlocations1to4.................................................... A34TableE.13 Excesskurtosisforthevesselspeeddistributionsoverthecrosssectionsat

locations1to4,forthedifferentdatasetsatlocations1to4...................................... A34TableG.1 Characteristicsofthedifferentsizeclassesincrosssection1-A........................... A54TableG.2 Characteristicsofthedifferentsizeclassesincrosssection1-B............................ A55TableG.3 Characteristicsofthedifferentsizeclassesincrosssection1-C............................ A55TableG.4 Characteristicsofthedifferentsizeclassesincrosssection1-D........................... A55TableG.5 Characteristicsofthedifferentsizeclassesincrosssection2-A........................... A56TableG.6 Characteristicsofthedifferentsizeclassesincrosssection2-B............................ A56TableG.7 Characteristicsofthedifferentsizeclassesincrosssection2-C............................ A57TableG.8 Characteristicsofthedifferentsizeclassesincrosssection3-A........................... A57TableG.9 Characteristicsofthedifferentsizeclassesincrosssection3-B............................ A58TableG.10 Characteristicsofthedifferentsizeclassesincrosssection4-A......................... A58TableG.11 Characteristicsofthedifferentsizeclassesincrosssection4-B.......................... A59TableG.12 Characteristicsofthedifferentsizeclassesincrosssection4-C.......................... A59

List of tables

AppendixA

Safetyatsea

Page-A8-

Safetyatsea

Appendix A Safety at sea

A.1 History of maritime transport1 2

Alreadythousandsofyearsagoseatransportwasimportantintrade.Intheseancienttimesthistradewasmainlyonaregionalornationalscale.Peoplewerenotabletosailacrossbigwaters,liketheAtlanticOcean.Lackofknowledgeoftheseaandallitsexternalfactorsmadesailingonopenseaaverydangerousactivity.Somewhatlater,inRomantimes,vesselsstayedmostofthetimequiteclosetothecoast,butthiswasnotaguaranteeforsafenavigation.Inbadweatherwindandcurrentscouldstilldestroyashipandalsopiracywasextensivelypresent.

FromtheMiddleAgesuntilthe18thcenturytheshippingindustrydeveloped,butsafetyatseastayedlow.Inthe19thcenturythelossofcargoandlifebyshipwreckwasstillenormous.Onlyduringthewinterof1820over2,000shipswerelostintheNorthSea,causingthedeathof20,000people.Theproblemswereinternationallyrecognisedandin1840thefirstnavigationrules,dealingwiththelightingofships,wereapplied.InthenextdecadesmainlyEnglandandFranceformulatedmoreguidelinesandrulestoaidnaviga-tionalsafety.

Theinternationalisationoftheshippingindustryperseveredinthe20thcentury.Itbecameclearthattheshippingbusinessneededgeneralagreements,toimprovesafetyandensurefaircompetition.TheBerlinconventionofNovember1906gaverisetothefirstrulesonwirelesstelegraphy.In1910conventionsoncol-lisionandlifesavingandassistanceweresigned.However,adisasterwasneededtoacceleratethedevelop-mentsonthefieldofstandardssetting.

A.2 SOLAS3 4

On14April1912theRMSTitanicsanknearNewfoundland.Noonehadexpectedtheworld’snewestandlargestpassengervesseltosink.Nexttothefactthatsomany–sometimesrichandfamous-peopledied,thisledtothequestionwhetherindividualcountriescouldsettheirownsafetystandards.AconferencewasheldinLondonwhichledtothefirstInternationalConventionfortheSafetyofLifeatSea(SOLAS).Thiswasoneofthefirsttreatiesthatfocussedontheprotectionofhumanlifeinsteadofproperty.

TreatieslikeSOLASwereimportant,butalsoverydependentonthededicationandenthusiasmofthedif-ferentgovernments.Inthefirstpartofthe20thcenturythesegovernmentsweremainlyoccupiedbythetwoworldwars.Howeverbetweenthesewars,in1929,anewerversionoftheSOLASwasaccepted.AftertheSecondWorldWartheinternationalisationoftheshippingbusinessincreasedrapidly.KeydevelopmentwasthefoundingoftheInter-GovernmentalMaritimeConsultativeOrganization(IMCO).

1 TheUNAtlasoftheOceans,www.oceansatlas.org,accessed:27/10/2009

2 Thehistoryofsafetyatsea,PhilippeBoisson,theUNAtlasoftheOceans,http://www.oceansatlas.com/unat

las/issues/safety/transport_telecomm/history_safety/history_safety.htm,accessed:27/10/2009

3 IMO’s50thanniversary:shippingandtheoceans,Overviewofshippingandnavigationhistory,World

MaritimeDay1998,InternationalMaritimeOrganization,http://www.imo.org/About/contents.asp?topic_

id=320&doc_id=886&header=false,accessed:27/10/2009

4 Internationalconventionforthesafetyoflifeatsea(SOLAS),1974,InternationalMaritimeOrganization,Inter

nationalMaritimeOrganization,http://www.imo.org/Conventions/contents.asp?topic_id=257&doc_id=647,

accessed:27/10/2009

Page -A9-


TheIMCOwasestablishedinGenevain1948.Thefirstofficialmeetingoftheneworganisationwasheldin1959.In1982thenamewaschangedinhowweknowitnowadays:theInternationalMaritimeOrganiza-tion,IMO.TheIMOisaspecialisedagencyoftheUnitedNations;herheadquarterislocatedinLondon.ThemaingoalforIMOis‘todevelopandmaintainacomprehensiveregulatoryframeworkforshippinganditsremittodayincludessafety,environmentalconcerns,legalmatters,technicalco-operation,maritimesecu-rityandtheefficiencyofshipping’.5

Toreachtheabovedescribedmainpurpose,internationalconventionshavebeensetup.ItisIMOhistasktomaintainandupdatetheseconventionsaswellassetupnewonesifneeded.Threetypesoftreatiesaredistinguished.Firstthereareconventionswhichaimtopreventaccidents.Second,treatiesprescribewhattodoifanaccidenthappens.Third,thereareconventionsthatestablishcompensationandliabilityregimes.TheSOLASconventionisaconventionofthefirsttype:topreventaccidents.OtherkeytreatiesofthistypeareMARPOL(InternationalConventionforthePreventionofPollutionfromShips)andSTCW(InternationalConventiononStandardsofTraining,CertificationandWatchkeepingforSeafarers)6.

TheSOLASconventionwasoneofthefirsttasksofIMO.Itcameintoforcein1965.Theideawastokeeptheconventionuptodatebyadjustingandexpandingitwithamendments.Theprocedurestodosoappearedtobeveryslow;thereforeafifthconventionwassetupin1974,inwhichtheamendmentprocesswasmadequicker.

TheSOLASconventioncurrentlyconsistsof12chapters.InDecember2000anumberofamendmentswasadopted.OneoftherevisedchaptersoftheconventionwaschapterV:‘SafetyofNavigation’.Thisbroughtinnewmandatoryrequirementsconcerningtheuseofvoyagedatarecorders(VDR’s)andautomaticidenti-ficationsystems(AIS).Atimeschemewasintroducedtoclarifywhichvesselsshouldbeequippedwiththeseitemsatwhattime.

AccordingtothenewchapterVinSOLAStheAISis“designedtobecapableofprovidinginformationabouttheshiptoothershipsandtocoastalauthoritiesautomatically”.IntheDecember2000amendmentthesevesselswererequiredtoinstalltheAISdependingontheirsizebetweenbetweenJuly2005andJuly2007.TheimplementationoftheAISwasfurtheracceleratedbyanewamendmentadoptedinDecember2002.Inthisamendment,allvesselsbetween300and50,000grosstonnagewereobligedtobefittedwithAISon31December2004atthelatest.

5 InternationalMaritimeOrganization,IntroductiontoIMO,http://www.imo.org/About/mainframe.asp?topic_

id=3,accessed:31/1/2010

6 InternationalMaritimeOrganization,Conventions,http://www.imo.org/Conventions/mainframe.asp?topic_

id=148,accessed:27/10/2009

AppendixB

DatainanAISmessage

Page-A12-

DatainanAISmessage

Appendix B Data in an AIS message

Table B.1 Data in an AIS message

Static information Sent every 6 minutes and on request of a competent authority

MMSI MaritimeMobileserviceIdentity.Setduringinstallation.

Callsign Setduringinstallation

Name Ship’sname

IMOnumber InternationalMaritimeOrganizationnumber

Lengthandbeam Setduringinstallationorifchanged

Locationofpositionfixingantenna

Setduringinstallationormaybechangedforbi-directionalvesselsorthosefittedwithmultiplepositionfixantennae.

Dynamic information Sent every 3-10 seconds, dependent on speed and course alteration

Ship’spositionwithaccu-racyindicationandintegritystatus

AutomaticallyupdatedfromthepositionsensorconnectedtotheAIS.

PositionTimestampinUTCAutomaticallyupdatedfromship’smainpositionsensorconnectedtoAIS.(e.g.GPS)

Courseoverground(COG)

Automaticallyupdatedfromship’smainpositionsensorconnectedtotheAIS,providedthatsensorcalculatesCOG.(Thisinformationmightnotbeavailable)

Speedoverground(SOG)AutomaticallyupdatedfromthepositionsensorconnectedtotheAIS,pro-videdthatthesensorcalculatesSOG(Thisinformationmightnotbeavail-able).

Heading Automaticallyupdatedfromtheship’sheadingsensorconnectedtotheAIS.

Navigationalstatus

Navigationalstatusinformationhastobemanuallyenteredbytheofficeronwatch(OOW)andchanged,asnecessary,forexample:

underwaybyengines,restrictedinabilitytomanoeuvre(RIATM),aground,atanchor,moored,engagedinfishing,notundercommand(NUC),con-strainedbydraughtandunderwaybysail.

Inpractice,sincealltheserelatetotheCOLREGS,anychangethatisneed-edcouldbeundertakenatthesametimethatthelightsorshapeswerechanged.

Rateofturn(ROT)Automaticallyupdatedfromtheship’sROTsensororderivedfromthegyro-compass.(Thisinformationmightnotbeavailable).

Page-A13-


Voyage related information Sent Every 6 minutes, when data is amended or on request

Ship’sdraughtTobemanuallyenteredatthestartofthevoyageusingthemaximumdraftforthevoyageandamendedasrequired;e.g.afterde-ballastingpriortoportentry.

Hazardouscargo(type)

Asrequiredbycompetentauthority.Tobemanuallyenteredatthestartofthevoyageconfirmingwhetherornothazardouscargoisbeingcarried,namely:

- DangerousGoods(DG) - HarmfulSubstances(HS) - MarinePollutants(MP) - Indicationsofquantitiesarenotrequired.

DestinationandETAAtMaster’sdiscretion.Tobemanuallyenteredatthestartofthevoyageandkeptuptodateasnecessary.

AppendixC

Applicationsand possibilitiesofAIS

Page-A16-

ApplicationsandpossibilitiesofAIS

Appendix C Applications and possibilities of AIS

ThisappendixshortlydescribeshowAISisorcanbeusedbycoastalauthoritiesandVTSsorinsearchandrescueoperations.

C.1 Aiding coastal authorities

AISoffersagoodopportunityforcoastalauthoritiestomonitorthevesselssailingthroughthecoastalwa-tersofanation.Alargerrangeandmoreinformation(e.g.typeofcargoanddestination)canbeobtainedthanwithradar;thisleadstoagoodoverviewofmaritimeactivity.Inthiswaytheycankeepcontrolofforexamplehazardouscargo.AdisadvantageofAISisthefactthatAISmessagesaresentbythevesselsthem-selves(comparedtoradar,wherethesignalisreflectedbythevessels).Althoughmostvesselsarenotlikelytodoso,itispossibletotransmitincorrectmessagesonpurpose.

ShoresideestablishedAISstationscansimplymonitor,butalsoactivelyrequestdatafrompassingvessels(ship-shore).Thesestationscanalsotransmitinformationtovessels(shore-ship),forexampletidesandweatherforecasts.

C.2 Vessel Traffic Services

InmostbusyportsandwaterwaysaVTSexiststokeepcontrolofthenauticaltraffic.Theseservicesuseradartomapthetraffic.Identificationisdonebyradioandradarinformation.VTSuseAISmessagesforadditionalinformationandasbackupwhenradarisnotworkingsufficient.AISdataisusedincreasingly,butradarstillisthemainsourceofinformationforVTSoperators1.Therearemainlytworeasonsforthis.First,thetechnicalreliabilityofthesignalisnotalwaysveryhigh.Thisisforexamplethecaseundercontainercranesandwhentugsarefasteningtothevessel.ThesecondreasonthatAISisnotfullyreliedonbyVTSoperatorsisduetoerrorsandinaccuraciesintheAISmessages.

Mostoftheseerrorsoccurinthestaticdataofamessage.Theoretically,itispossibletoidentifyvesselsquicklyandcorrectlywithAIS,whichcanbeveryuseful,especiallyincrowdedwaterways.ThevesselnameinAISmessagesdoessometimesnotexactlymatchwiththenameintheportitsdatabase.ThismakesitdifficulttousetheAISdataforidentifyingvessels.Thereforenowadaysidentificationis,atleastfortheportofRotterdam,stilldonemanually,withhelpfromradarandradio.Thisisdonebydeterminingtheloca-tionfromwherearadiosignalistransmitted(radardirectionfinder,seeFigureC.1(left).Whenthetargetisidentifiedontheradar,avesselnamecanbeplacedmanually.

1 InformationderivedfromavisittotheVTSHoekvanHolland,portofRotterdam,Netherlands

Page-A17-


VTSPort area

Radar Direc�on Finder

Radar Direc�on Finder

Radar Sta�on

Shadow area

Figure C.1 The principle of a radar direction finder (left) and Radar waves blocked by another vessel (right)

VTSscanalsouseAISdatatomapthetrafficsituationinsideandaroundtheportarea.AdvantageofAISoverradaristhatthepositionofthevesselsismuchmoreprecise.Nexttothis,AISdetectionisnotlimitedbyobstacleslikeothervesselsorlandmass(e.g.aroundcorners),seeFigureC.1(right).DisadvantageofAISistheoccurrenceofalotoferrorsinthedata,whichmakesitdifficulttorelyon.Furthermore,notallvesselssailinginorthroughtheportareequippedwithAIS(e.g.fishing,recreationalandinlandshippingvessels).

C.3 Search and rescue

Duringamarinesearchandrescueoperationitisimportanttoknowthepositionandnavigationalstatusofallshipsinvicinityoftheshiporpersonindistress.WithAIS,thisinformationisavailableforthevessels.AlsoSearchandRescue(SAR)aircraftcantransmittheirpositionbyAIS.Latelyanewtoolisdevelopedtolo-catepersonsindistress:theAIS-SART(FigureC.2).ThisdevicetransmitsAISmessagescontainingtheactualpositionoftheperson2.

Figure C.2 AIS SART, as de-veloped by Jotron AS.

2 InternationalMaritimeOrganization,IMO,

http://www.imo.org/includes/blastDataOnly.asp/data_id%3D20463/246%2883%29.pdf,

accessed:24/12/2009

AppendixD

MatlabmodelfortheAISanalysis

Page-A20-


Appendix D Matlab model for the AIS analysis

ThematlabmodelusedfortheanalysisofAISdatatransformsinseveralstepstheavailableroughAISmes-sagesintodataconcerningthevesselbehaviourofaspecifiedselectionofvessels.Inthisappendix,firsttheconvertingfromroughAISmessagestowardsanumberofreadytousevesseltracksishandled.Hereafteritisshownhowdifferentselectionscanbemadefromthesevesseltracks.Finally,theselectedvesseltracksareanalysed.

D.1 Transformation rough AIS data

SomeadjustmentshavetobemadebeforetheAISmessagesthatareobtainedasoutputfromShowRoutecanbeusedintheAISanalysis.Thevessel’spositionisgiveninlongitudeandlatitudecoordinates.Disad-vantageofthesecoordinates,isthattheyaremeasuredindegrees,minutesandseconds.Thereisalsothedifficultythatonedegreeinlateraldirectionisadifferentdistancethanonedegreeinlongitudinaldirec-tion.Thismakesitverydifficulttocomparethemandbecausetheresultsconcerningthevesselbehaviourshouldbeobtainedinmeters,itisdecidedtorecalculatethecoordinates.Theyaretransformedtocoordi-natesinthe‘Rijksdriehoeksstelsel’(RD).Thisnationalgridisusedasabasisforgeographicalindicationsandfiles,likeGeographicInformationSystems.AlsotheportofRotterdamsinfrastructureisexpressedinRDco-ordinates.So,toevaluateavesselspositioncomparedtotheportsinfrastructureitisneededtorecalculatethegeographicalcoordinatestoRDcoordinates.TheMatlabcodethatisusedtodosoispresentedbelow:

function [A0] = transform_to_RD(A0)

disp(‘Transform to RD...’)

Latitude = A0(:,1);

Longitude = A0(:,2);

dF = 0.36 * (Latitude - 52.15517440);

dL = 0.36 * (Longitude - 5.38720621);

for i=1:size(A0)

A0(i,2)= 155000+(190094.945 * dL(i)) + (-11832.228 * dF(i) * dL(i)) + (-144.221 * dF(i)^2 * dL(i)) + (-32.391 * dL(i)^3) +

(-0.705 * dF(i)) + (-2.340 * dF(i)^3 * dL(i)) + (-0.608 * dF(i) * dL(i)^3) + (-0.008 * dL(i)^2) + (0.148 * dF(i)^2 * dL(i)^3);

A0(i,1) = 463000+(309056.544 * dF(i)) + (3638.893 * dL(i)^2) + (73.077 * dF(i)^2 ) + (-157.984 * dF(i) * dL(i)^2) +

(59.788 * dF(i)^3 ) + (0.433 * dL(i)) + (-6.439 * dF(i)^2 * dL(i)^2) + (-0.032 * dF(i) * dL(i)) + (0.092 * dL(i)^4) + (-0.054 *

dF(i) * dL(i)^4);

end

AfterthetransformationtowardstheRDcoordinates,thelocationoftheantennethattransmitsthemes-sagesonthevesselshouldbetakenintoaccount.Thisantennaismostlynotsituatedexactlyinthemiddleofthevessel;itcanbeatadifferentplaceateveryvessel.Thiscausesinaccurieswhencomparingvesselpositionswitheachother.Theseinaccurariescanbenegligibleatopensea,butinaportarea,theyaredefi-nitelynot.Itisthereforeneededtoadjustthevessel’scoordinatesbytakingintoaccountthepositionoftheantennainthevessel.ThisexactpositionisfortunatelyincludeintheAISmessage,whichmakesitpossibletodoso.TheMatlabcodebelowshowshowthiscalculationisdone.

Page-A21-


function [A2] = AntennaLocation(A1)

disp(‘Antenna Location...’)

pf = 0.8;

sf=1 ;

for i=1:size(A1)

bow(1) = A1(i,1) + A1(i,8)*cos(A1(i,7)*pi()/180)*sf;

bow(2) = A1(i,2) + A1(i,8)*sin(A1(i,7)*pi()/180)*sf;

starfor(1) = A1(i,1) + A1(i,8)*cos(A1(i,7)*pi()/180)*pf*sf - A1(i,10)*sin(A1(i,7).*pi./180)*sf;

starfor(2) = A1(i,2) + A1(i,8)*sin(A1(i,7)*pi./180).*pf.*sf + A1(i,10)*cos(A1(i,7)*pi./180).*sf;

staraft(1) = A1(i,1) - A1(i,9)*cos(A1(i,7)*pi()/180)*s - A1(i,10)*sin(A1(i,7)*pi./180).*sf;

staraft(2) = A1(i,2) - A1(i,9)*sin(A1(i,7)*pi./180).*sf + A1(i,10)*cos(A1(i,7)*pi./180).*sf;

portaft(1) = A1(i,1) - A1(i,9)*cos(A1(i,7)*pi./180).*sf + A1(i,11)*sin(A1(i,7)*pi./180).*sf;

portaft(2) = A1(i,2) - A1(i,9)*sin(A1(i,7)*pi./180).*sf - A1(i,11)*cos(A1(i,7)*pi./180).*sf;

portfor(1) = A1(i,1) + A1(i,8)*cos(A1(i,7)*pi./180).*pf.*sf + A1(i,11)*sin(A1(i,7)*pi./180).*sf;

portfor(2) = A1(i,2) + A1(i,8)*sin(A1(i,7)*pi./180).*pf.*sf - A1(i,11)*cos(A1(i,7)*pi./180).*sf;

A1(i,1)=(starfor(1)+staraft(1)+portaft(1)+portfor(1))/4;

A1(i,2)=(starfor(2)+staraft(2)+portaft(2)+portfor(2))/4;

end

D.2 Track selection

Aftertheoperationsmentionedabove,anumberoftracksisleftwithwhichtheanalysiscanbeperformed.Beforeanycalculationsregardingforexampletheaveragevesselpathcanbemade,aselectionoftracksmustbedetermined.Thisselectioncandependonthevesselsizeandthedirectionofthevessel(incomingoroutgoing).Itishoweveralsopossibletoincludetheexternalcircumstancesintheselectionprocess.ByusingaGraphicalUserInterace(GUI)theselectioncriteriaarefilledin,seeFigureD.1.

Page-A22-


Figure D.1 GUI to make a vessel track selection

AfterfillingintheGUI,thefollowingMatlabcodeisrun.

function [A4,f,h,tracks_data,GeenInfo] = route_toewijzing(A2,a,ondergrens,bovengrens,r,LowLim_wind,UpLim_

wind,LowLim_dir,UpLim_dir,LowLim_visibility,UpLim_visibility,Current_track,Current_dir,Current_size_max,Current_

size_min,Cur)

disp(‘Chosing tracks...’)

tf=strcmp(a,’ingaand’);

if tf==1

s=200;

t=100;

end

if tf==0

s=100;

t=200;

end

n=1;

k=1;

for i=1:size(A2)-1

if abs(A2(i+1,3)-A2(i,3))<600

A2(i,6)=n;

else

A2(i,6)=n;

n=n+1;

if (and(A2(i,2)<62000,A2(i,1)>444300))

A2(i,13)=200;

else

Page-A23-


A2(i,13)=300;

end

if and((A2(i,1)<441500),and(A2(i,1)>440000,and(A2(i,2)<66000,A2(i,2)>62200)))

A2(i,13)=100;

end

if (and(A2(i+1,2)<62000,A2(i+1,1)>444300))

A2(i+1,13)=200;

else

A2(i+1,13)=300;

end

if and((A2(i+1,1)<441500),and(A2(i+1,1)>440000,and(A2(i+1,2)<66000,A2(i+1,2)>62200)))

A2(i+1,13)=100;

end

b{1,n}=A2(k+1:i,:);

k=i;

end

end

load Input/Grootte

b{1,1}=0;nnn=0;GeenInfo=0;

for i=2:n

c=size(b{1,i});

d=b{1,i};

for x=1:size(Grootte)

if d(1,5)==Grootte(x,1)

d(:,12)=Grootte(x,2);

end

end

b{1,i}=d;

if or(d(1,12)<ondergrens,or(d(1,12)>bovengrens,c(1,1)<10))

b{1,i}=0;

end

if d(1,12)==0;b{1,i}=0;nnn=nnn+1;GeenInfo(nnn)=d(1,5);end

if or(d(1,14)<LowLim_wind,d(1,14)>UpLim_wind)

b{1,i}=0;

end

if UpLim_dir-LowLim_dir>0

if or(d(1,15)<LowLim_dir,d(1,15)>UpLim_dir)

b{1,i}=0;

end

else

if and(d(1,15)<LowLim_dir,d(1,15)>UpLim_dir)

b{1,i}=0;

end

end

if or(d(1,16)<LowLim_visibility,d(1,16)>UpLim_visibility)

Page-A24-


b{1,i}=0;

end

if or(b{1,i}==0,Cur~=1);else

[Check] = Current_check(d,Current_track,Current_dir,Current_size_max,Current_size_min);

if Check(1,1)==0;

b{1,i}=0;

end

end

end

j=1;b{1,1}=0;tracks_data(1,1)=0;

for i=1:n

c=size(b{1,i});

d=b{1,i};

if size(b{1,i})<100;b{1,i}=0;end

if b{1,i}==0;

else

if or(d(1,13)~=s,d(c(1,1),13)~=t)

b{1,i}=0;

else

tracks_data(j,1)=i-1;

tracks_data(j,2)=d(1,5);

j=j+1;

end

end

end

y=0;f{1,1}(1,1)=0;

for i=1:n

if b{1,i}==0

else

y=y+1;

f{y,1}=b{1,i};

end

end

if f{1,1}(1,1)~=0

g=randperm(round(numel(f)));

h=f(g(1:numel(f)*r));

A4=cell2mat(h);

else

h{1,1}=0;A4(1,1)=0;

end

Page-A25-


D.3 Analysis selected tracks

Theanalysisoftheselectedtrackscontainsseveralaspects.Firsttargetistodeterminetheaveragevesselpathandtheaccompanyingaveragevesselspeed.Togetherwiththis,alsothedeviationofthevesselsoverthedifferentcrosssectionsinthewaterwayisdetermined.Thesameisdoneforthevesselspeed.TheMat-labcodeinwhichthisisdone,ispresentedbelow.

function [Tracks,B1] = bepaling_gem_positie_snelheid_final_v4(a,gridsize,gridsize_verdeling,h)

disp(‘Calculate average track (1)’)

tf=strcmp(a,’ingaand’);

if tf==1

route=180;

else route=0;

end

load Input/RefLine

Xstart=59000;

Xeind=68000;

Ystart=440000;

Yeind=450000;

Xtotal=Xeind-Xstart;

Ytotal=Yeind-Ystart;

Xkruis=65500;

Ykruis=4.441*10^5;

Deviation=cell(numel(RefLine(:,1)),3);

n=0;

for xxx=1:numel(RefLine(:,1))

disp(xxx)

x=RefLine(xxx,1);

n=n+1;

v=0;

vv=0;

bb=0;pp=0;bbb=0;

for iii=1:size(h)

if xxx==1;Tracks{iii,2}=h{iii,1}(1,6);end

clear a

a(:,1)=h{iii,1}(:,1);

a(:,2)=h{iii,1}(:,2);

a(:,3)=h{iii,1}(:,4);

a(:,4)=h{iii,1}(:,7);

a(:,5)=h{iii,1}(:,6);

b=a;

v=0;

Page-A26-


bb=0;

for i=1:size(a)

Bpar=a(i,1)-a(i,2)*tan((RefLine(xxx,3)-90)*pi/180);

CrossX=(Bpar-RefLine(xxx,4))/(tan((RefLine(xxx,3))*pi/180)-tan((RefLine(xxx,3)-90)*pi/180));

CrossY=tan((RefLine(xxx,3)-90)*pi/180)*CrossX+Bpar;

Dist=sqrt((CrossY-a(i,1))^2+(CrossX-a(i,2))^2);

if or(Dist>gridsize/2,or(abs(RefLine(xxx,1)-a(i,2))>2000,abs(RefLine(xxx,2)-a(i,1))>2000))

b(i,:)=0;

else

v=v+1;

bb(v,1:5)=a(i,:);

bb(v,7)=CrossX;bb(v,8)=CrossY;

end

end

vv=vv+1;

if numel(bb(:,1))~=1;bbb(vv,1:8)=mean(bb(:,1:8));bbb(vv,6)=v;Tracks{iii,1}(xxx,1)=mean(bb(:,8));Tracks{iii,1}(xxx,2)=m

ean(bb(:,7));Tracks{iii,1}(xxx,3)=mean(bb(:,3));

else

if bb(1,1)~=0;bbb(vv,1:8)=bb(:,1:8);bbb(vv,6)=v;Tracks{iii,1}(xxx,1)=bb(:,8);Tracks{iii,1}(xxx,2)=bb(:,7);Tracks{iii,1}

(xxx,3)=bb(:,3);

else

bb=0;

for i=1:size(a)

Bpar=a(i,1)-a(i,2)*tan((RefLine(xxx,3)-90)*pi/180);

CrossX=(Bpar-RefLine(xxx,4))/(tan((RefLine(xxx,3))*pi/180)-tan((RefLine(xxx,3)-90)*pi/180));

CrossY=tan((RefLine(xxx,3)-90)*pi/180)*CrossX+Bpar;

Dist=sqrt((CrossY-a(i,1))^2+(CrossX-a(i,2))^2);

if or(Dist>gridsize,or(abs(RefLine(xxx,1)-a(i,2))>2000,abs(RefLine(xxx,2)-a(i,1))>2000))

b(i,:)=0;

else

v=v+1;

bb(v,1:5)=a(i,:);

bb(v,7)=CrossX;bb(v,8)=CrossY;

end

end

if numel(bb(:,1))~=1;bbb(vv,1:8)=mean(bb(:,1:8));bbb(vv,6)=v;Tracks{iii,1}(xxx,1)=mean(bb(:,8));Tracks{iii,1}(xxx,

2)=mean(bb(:,7));Tracks{iii,1}(xxx,3)=mean(bb(:,3));

else if bb(1,1)~=0;bbb(vv,1:8)=bb(:,1:8);bbb(vv,6)=v;Tracks{iii,1}(xxx,1)=bb(:,8);Tracks{iii,1}

(xxx,2)=bb(:,7);Tracks{iii,1}(xxx,3)=bb(:,3);else vv=vv-1;end

end

end

end

end

e=bbb;

if numel(e)~=1;

Page-A27-


eX=mean(e(:,7));

eY=mean(e(:,8));

Deviation{n,2}=eX;Deviation{n,3}=eY;

Deviation{n,1}(1,:)=-400:gridsize_verdeling:400;

Deviation{n,1}(2,:)=0;Deviation{n,1}(3,:)=0;

for eee=1:numel(e(:,1))

if or(and(e(eee,4)>45,and(e(eee,4)<=135,e(eee,8)<eY)),or(and(e(eee,4)>135,and(e(eee,4)<=225,e(eee,7)<eX)),or(a

nd(e(eee,4)>225,and(e(eee,4)<=315,e(eee,8)>eY)),and(or(e(eee,4)>315,e(eee,4)<=45),e(eee,7)>eX))))

e(eee,9)=sqrt((e(eee,7)-eX)^2+(e(eee,8)-eY)^2);

else e(eee,9)=-sqrt((e(eee,7)-eX)^2+(e(eee,8)-eY)^2);

end

nnn=0;

for nnn=1:numel(Deviation{n,1}(1,:))

if abs(e(eee,9)-Deviation{n,1}(1,nnn))<gridsize_verdeling/2

Deviation{n,1}(2,nnn)=Deviation{n,1}(2,nnn)+1;

Deviation{n,1}(3,nnn)=Deviation{n,1}(3,nnn)+e(eee,3);

end

end

end

Afw2=prctile(e(:,9),2);Afw98=prctile(e(:,9),98);

f(n,12)=Afw2;f(n,13)=Afw98;

if route==180;

Prct2X=eX-Afw2*cos(RefLine(xxx,3)*pi/180);Prct2Y=eY-Afw2*sin(RefLine(xxx,3)*pi/180);

Prct98X=eX-Afw98*cos(RefLine(xxx,3)*pi/180);Prct98Y=eY-Afw98*sin(RefLine(xxx,3)*pi/180);

else Prct2X=eX+Afw2*cos(RefLine(xxx,3)*pi/180);Prct2Y=eY+Afw2*sin(RefLine(xxx,3)*pi/180);

Prct98X=eX+Afw98*cos(RefLine(xxx,3)*pi/180);Prct98Y=eY+Afw98*sin(RefLine(xxx,3)*pi/180);

end

f(n,1)=mean(e(:,7));

f(n,2)=mean(e(:,8)); %average path

f(n,3)=Prct2X;

f(n,4)=Prct2Y;

f(n,5)=Prct98X;

f(n,6)=Prct98Y;

f(n,7)=mean(e(:,3)); %average speed

f(n,8)=prctile(e(:,3),2);

f(n,9)=prctile(e(:,3),98);

f(n,10)=vv;

f(n,11)=mean(e(:,4));

u{n,1}(:,1)=e(:,3);

end

end

g=find(f==0);

f(g)=NaN;

B1=f;

AppendixE

χ2tests,skewnessandexcesskurtosis

Page-A30-


Appendix E χ2 tests, skewness and excess kurtosis

Thisappendixgivesthemoredetailedelaborationoftheχ2teststhatareperformedinthecasestudy.Nexttothis,alsotheresultsfromthecalculationoftheskewnessandexcesskurtosisthatarenotshowninthemainreport,areshownhere.

E.1 χ2 tests

χ2testsareperformedforaswellthevesseldistributionasthevesselspeeddistributionoverthewaterway(seesection5.4).Thistestexaminesthedegreeofagreementbetweentheempiricaldistributionandaspe-cifictheoreticaldistribution.Equation(E.1)showshowthevalueforχ2iscalculated.

(E.1) 2k2 o e

1 e

(f f )

fχ

−=∑

where

fo=observedfrequencyofeachclassorinterval; fe=expectedfrequencyforeachclassorintervalpredictedbyatheoretical distribution; k=totalclassesorintervals.

Ifthevalueforχ2isequaltozero,thentheempiricalentheoreticaldistributionhaveaperfectmatch.Ifthisisnotthecase,thesizeofχ2determinesthedegreeofagreement.Thehypothesisthatismadewhenperformingaχ2test,isthatnosignificantdifferenceexistsbetweenthecompareddistributions.Ifthecalcu-latedvalueforχ2istoolarge,thishypothesisisrejected.Beforeitcanbeseenifthisisthecase,twoques-tionsshouldbeanswered.First,thedegreeoffreedomofthedistributionsshouldbeobtained.Thedegreesoffreedomreflectthenumberofclassesinwhichthetwodistributionsarecomparedtoeachotherandthenumberofparametersthatisneededtodescribethetheoreticaldistribution,equation(E.2)).

(E.2) k 1 mθ = − − where

θ=degreesoffreedom; k=numberofclassesorintervals; m=numberofparametersneededtocalculatetheexpected frequencies.

Afterthedegreesoffreedomaredetermined,thesignificancelevelhastobeset.Thisreflectsthecon-fidencelevelthatisusedtorejectoracceptthehypothesis.Thislevelcanbesetbyatdifferentvalues,dependingonforexamplethenatureofthestudie.Throughoutthisthesisalevelof95%isused;thisisalsodonefortheχ2tests.

Whenthevalueforχ2,thedegreesoffreedomandthesignificancelevelareknown,thehypothesiscanbetested.Thisisdonebycomparingthevaluefoundforχ2toavalueobtainedfromaChi-squaredistribu-tion.ThisisvaluefromtheChi-squaredistributionismostlyderivedfromatable,inwhichalsothedegreesoffreedomandthesignificancelevelareincluded.TableE.1showsanexampleofhowapartofthistable

Page-A31-


lookslike.Itcanbeseenthattheasignificancelevelof95%combinedwith5degreesoffreedom,leadstoavalueof11.1.

Table E.1 Example of a part of the Chi-square distribution table

Degrees of free-dom

Significancelevel

99.5% 99% 95% 90%

1 7.88 6.63 3.84 2.71

2 10.6 9.21 5.99 4.61

3 12.84 11.34 7.81 6.25

4 14.96 13.28 9.49 7.78

5 16.7 15.1 11.1 9.2

6 18.5 16.8 12.6 10.6

Thisvaluecanhereafterbecomparedtothevaluefoundforχ2.Ifthevalueforχ2islargerthanthevaluefoundinthetable,theirisasignificancedifferencebetweenthetwodistributions.Thehypothesisofnodif-ferenceisinsuchacaserejected.

Inthethesis,theabovedescribedχ2testisperformedseveraltimes.Aswelthevesseldistributions,asthevesselspeeddistributionsoverdifferentcrosssectionsaretested.TableE.2toTableE.11showtheresultsforthesetests.Thecolumn‘χ2’showsthevaluethatwasfoundforχ2and‘Freedom’reflectsthedegreesoffreedom.Thecolumn‘χ2table’showsthevaluethatwasreadfromtheChi-squaredistribuiontable.Thecolumn‘Check’reflectstheresultofthecomparisonbetweenthefirsttwo:thehypothesisisaccepted(OK)orrejected(FAIL).

Table E.2 χ2 tests performed for the vessel distributions over the cross sections on location 1-4Size class < 10,000 dwt.

LocationIncoming Outgoing

χ2 Freedom χ2table Check χ2 Freedom χ2table Check

1 12.9 19 30.1 OK 16.2 24 36.4 OK

2 8.8 11 19.7 OK 16.3 22 33.9 OK

3 16.6 15 25 OK 14.8 25 37.7 OK

4 7.9 16 26.3 OK 11.6 12 21 OK

Table E.3 χ2 tests performed for the vessel distributions over the cross sections on location 1-4Size class 10,000-40,000 dwt.



1 18.2 17 27.6 OK 34.2 29 42.6 OK

2 9.7 8 15.5 OK 17.0 16 26.3 OK

3 11.8 12 21 OK 12.4 23 35.2 OK

4 6.2 15 25 OK 15.4 9 16.9 OK

Page-A32-





1 17.4 17 27.6 OK 25.3 20 31.4 OK

2 7.2 6 12.6 OK 20.2 14 23.7 OK

3 28.9 15 25 FAIL 9.7 16 26.3 OK

4 17.2 10 18.3 OK 10.8 8 15.5 OK




1 7.8 17 27.6 OK 29.7 26 38.9 OK

2 2.5 6 12.6 OK 13.8 15 25 OK

3 12.0 12 21 OK 19.5 15 25 OK

4 16.0 12 21 OK 13.6 6 12.6 FAIL

Table E.6 χ2 tests performed for the vessel distributions over the cross sections on location 1-4Size class >100,000 dwt.



1 16.5 17 27.6 OK 16.3 27 40.1 OK

2 9.9 9 16.9 OK 16.3 15 25 OK

3 9.9 13 22.4 OK 21.8 15 25 OK

4 23.1 11 19.7 FAIL 8.2 6 12.6 OK

Table E.7 χ2 tests performed for the vessel speed distributions over the cross sections on location 1-4Size class <10,000 dwt.



1 18.4 17 27.6 OK 7.9 15 25 OK

2 17.7 20 31.4 OK 10.9 12 21 OK

3 10.3 16 26.3 OK 14.5 16 26.3 OK

4 3.8 17 27.6 OK 6.5 13 22.4 OK

Page-A33-


Table E.8 χ2 tests performed for the vessel speed distributions over the cross sections on location 1-4Size class 10,000-40,000 dwt.



1 30.7 20 31.4 OK 22.5 15 25 OK

2 22.2 26 38.9 OK 9.2 13 22.4 OK

3 11.9 19 30.1 OK 18.9 16 26.3 OK

4 7.3 18 28.9 OK 9.7 13 22.4 OK




1 29.7 13 22.4 FAIL 23.8 18 28.9 OK

2 7.7 8 15.5 OK 11.2 15 25 OK

3 8.3 7 14.1 OK 15.5 11 19.7 OK

4 13.7 4 9.49 FAIL 13.1 9 16.9 OK




1 17.4 14 23.7 OK 31.0 18 28.9 FAIL

2 17.8 10 18.3 OK 23.0 16 26.3 OK

3 13.4 6 12.6 FAIL 12.9 12 21 OK

4 2.5 4 9.49 OK 13.1 9 16.9 OK

Table E.11 χ2 tests performed for the vessel speed distributions over the cross sections on location 1-4Size class >100,000 dwt.



1 13.9 18 28.9 OK 18.4 14 23.7 OK

2 15.3 11 19.7 OK 12.7 11 19.7 OK

3 4.7 5 11.1 OK 6.6 11 19.7 OK

4 9.1 3 7.81 FAIL 8.2 8 15.5 OK

Page-A34-


E.2 Skewness and kurtosis

Forthevesseldistributionsoverthecrosssectionsatthedifferentlocations,theskewnessandkurtosiswerealreadygiveninthemainreport.Forthevesselspeeddistributionthisishowevernotdone.Thereforethesetwoparametersareshownbelow(TableE.12andTableE.13).

Table E.12 Skewness for the vessel speed distributions over the cross sections at locations 1 to 4, for the different datasets at locations 1 to 4

Location<10,000 10,000-40,000 40,000-70,000 70,000-100,000 >100,000


1 -0.68 -0.05 -0.63 -0.1 0.2 0.02 0.22 0.33 0.12 -0.28

2 -0.59 -0.12 -0.17 -0.72 0.58 0.47 0.66 0.24 0.12 0.02

3 -0.38 -0.65 0.12 -0.54 -0.43 0.24 0.13 0.16 0.25 0.41

4 -0.36 -0.54 -0.11 -0.21 0.03 -0.17 -0.97 0.44 -0.21 0.22

Table E.13 Excess kurtosis for the vessel speed distributions over the cross sections at locations 1 to 4, for the different datasets at locations 1 to 4

Location<10,000 10,000-40,000 40,000-70,000 70,000-100,000 >100,000


1 0.33 -0.4 -0.28 -0.48 0.5 -0.79 0.34 -0.33 -0.41 -0.57

2 -0.25 -0.45 -0.65 2.31 0.66 0.69 0.95 -0.62 0.26 -0.63

3 -0.04 0.59 -0.39 0.36 0.9 -0.74 0.5 0.82 0.52 0.18

4 0.18 0.91 -0.35 -0.38 0.73 0.1 3.45 1.03 0.52 0.51

AppendixF

Vesselandvesselspeeddistributions

Page-A36-

Vesselandvesselspeeddistribution

Appendix F Vessel and vessel speed distributions

Thisappendixshowsalldistributionsthatareusedthroughoutthecasestudy,toobtaininsightintheaver-agevesselbehaviour.First,thevesseldistributionsoverthewaterwayatthefourpredefinedlocationsisgivenforeverysizeclass.Second,thevesselspeeddistributions,againatthefourspecifiedlocationsisshown.Forboth,aswellthetheempiricalasthefittednormaldistributionaregiven.Finallyalsothespeeddistributionoverthewaterwayispresented.

F.1 Vessel distribution over the waterway

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.8845µ=11.3σ=84.1A=0.12

Loca�on 1

−400 −200 0 200 4000

0.1

0.2


P (X

)R 2=0.939µ=0σ=39.1A=0.25

Loca�on 2

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9654µ=23σ=42.9A=0.21

Loca�on 3

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9526µ=7.7σ=72.9A=0.13

Loca�on 4

Figure F.1 Vessel distribution over cross sections 1-4 for incoming vessels from sizeclass <10,000 dwt

Page-A37-


−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.8464µ=21.9σ=111.9A=0.09

Loca�on 1

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.8546µ=0σ=95.1A=0.1

Loca�on 2

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.8159µ=−1.4σ=120.8A=0.08

Loca�on 3

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9631µ=9.5σ=58.7A=0.17

Loca�on 4

Figure F.2 Vessel distribution over cross sections 1-4 for outgoing vessels from sizeclass <10,000 dwt

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.8663µ=0σ=86.2A=0.12

Loca�on 1

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9644µ=6.8σ=36A=0.27

Loca�on 2

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9553µ=13.2σ=57.1A=0.17

Loca�on 3

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9443µ=−2.9σ=72.5A=0.14

Loca�on 4

Figure F.3 Vessel distribution over cross sections 1-4 for incoming vessels from sizeclass 10,000-40,000 dwt

Page-A38-


−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.7726µ=0σ=139.6A=0.07

Loca�on 1

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.8835µ=2.6σ=79A=0.12

Loca�on 2

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.8848µ=−5.8σ=112A=0.09

Loca�on 3

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9267µ=7.7σ=50.6A=0.19

Loca�on 4

Figure F.4 Vessel distribution over cross sections 1-4 for outgoing vessels from sizeclass 10,000,40,000- dwt

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.7592µ=10.5σ=123.9A=0.08

Loca�on 1

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9071µ=5.3σ=76.3A=0.13

Loca�on 2

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.8571µ=−5.4σ=74.9A=0.13

Loca�on 3

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9716µ=0σ=27.8A=0.32

Loca�on 4


Page-A39-


−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.7635µ=20.9σ=98.5A=0.1

Loca�on 1

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.8737µ=16.6σ=59.9A=0.16

Loca�on 2

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9094µ=6.4σ=82.2A=0.12

Loca�on 3

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9829µ=8.1σ=34.2A=0.27

Loca�on 4

Figure F.6 Vessel distribution over cross sections 1-4 for outgoing vessels from sizeclass 40,000-70,000 dwt

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.952µ=−1.3σ=82.7A=0.12

Loca�on 1

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9921µ=3.3σ=37A=0.27

Loca�on 2

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9109µ=4.9σ=58.7A=0.17

Loca�on 3

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.935µ=−15.5σ=51.9A=0.18

Loca�on 4


Page-A40-


−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.7592µ=10.5σ=123.9A=0.08

Loca�on 1

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9071µ=5.3σ=76.3A=0.13

Loca�on 2

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.8571µ=−5.4σ=74.9A=0.13

Loca�on 3

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9716µ=0σ=27.8A=0.32

Loca�on 4

Figure F.8 Vessel distribution over cross sections 1-4 for outgoing vessels from sizeclass 70,000-100,000 dwt

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.8535µ=−4.6σ=84.9A=0.12

Loca�on 1

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9444µ=2σ=49A=0.21

Loca�on 2

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9599µ=5.4σ=63.8A=0.16

Loca�on 3

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.8768µ=−18.9σ=55.3A=0.17

Loca�on 4

Figure F.9 Vessel distribution over cross sections 1-4 for incoming vessels from sizeclass >100,000 dwt

Page-A41-


−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.7885µ=1σ=131.5A=0.08

Loca�on 1

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.9451µ=−5.6σ=76.8A=0.14

Loca�on 2

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.8553µ=−4.6σ=68.6A=0.14

Loca�on 3

−400 −200 0 200 4000

0.1

0.2


P (X

)

R 2=0.971µ=2.1σ=35A=0.27

Loca�on 4

Figure F.10 Vessel distribution over cross sections 1-4 for outgoing vessels from sizeclass >100,000 dwt

Page-A42-


F.2 Vessel speed distribution on a location on the waterway

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.8593

µ=13.7

σ=2.1

A=0.09

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.8406

µ=12.7

σ=2.5

A=0.08

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.8997

µ=10.5

σ=2.2

A=0.09

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9269

µ=9.2

σ=2.3

A=0.09



Figure F.11 Vessel speed distribution on location 1-4, for incoming vessels from size class <10,000 dwt

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9553

µ=14.8

σ=2.1

A=0.1

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9348

µ=14.3

σ=1.7

A=0.12

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9324

µ=11.8

σ=1.9

A=0.1

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9018

µ=10.4

σ=1.7

A=0.12



Figure F.12 Vessel speed distribution on location 1-4, for outgoing vessels from size class <10,000 dwt

Page-A43-


0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.8541

µ=14.4

σ=2.5

A=0.07

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.8262

µ=11.5

σ=3.4

A=0.06

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9221

µ=9

σ=2.7

A=0.08

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.8577

µ=8.1

σ=2.5

A=0.08



Figure F.13 Vessel speed distribution on location 1-4, for incoming vessels from size class 10,000-40,000 dwt

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.8044

µ=15.3

σ=2.2

A=0.09

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.947

µ=14.5

σ=1.7

A=0.11

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9019

µ=11.1

σ=2.1

A=0.09

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.8647

µ=9.8

σ=2

A=0.1



Figure F.14 Vessel speed distribution on location 1-4, for outgoing vessels from size class 10,000-40,000 dwt

Page-A44-


0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.7607

µ=10.8

σ=1.8

A=0.11

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9149

µ=7.4

σ=1.3

A=0.16

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9545

µ=6.2

σ=1.1

A=0.19

0 5 10 15 200

0.1

0.2


P (X

)R 2=0.9592

µ=5.9

σ=0.6

A=0.28




0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.8221

µ=13.7

σ=2.4

A=0.09

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9022

µ=12.4

σ=2

A=0.1

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9398

µ=8.5

σ=1.7

A=0.12

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9114

µ=7

σ=1.4

A=0.14




Page-A45-


0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.8833

µ=10.2

σ=1.9

A=0.1

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.8865

µ=7.5

σ=1.4

A=0.14

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9097

µ=6

σ=0.8

A=0.23

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9533

µ=5.6

σ=0.7

A=0.27




0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.7979

µ=12

σ=2.4

A=0.08

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.8766

µ=10.7

σ=2.2

A=0.09

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.8898

µ=7.6

σ=1.5

A=0.13

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.923

µ=6

σ=1.1

A=0.17




Page-A46-


0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9157

µ=10.5

σ=2.5

A=0.08

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.8944

µ=7.4

σ=1.6

A=0.12

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9817

µ=6.2

σ=0.8

A=0.23

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9838

µ=5.7

σ=0.7

A=0.27



Figure F.19 Vessel speed distribution on location 1-4, for incoming vessels from size class >100,000 dwt

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.8813

µ=14.3

σ=2

A=0.1

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.8761

µ=12.3

σ=1.6

A=0.12

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9386

µ=8.3

σ=1.5

A=0.13

0 5 10 15 200

0.1

0.2


P (X

)

R 2=0.9604

µ=6.6

σ=1.3

A=0.15



Figure F.20 Vessel speed distribution on location 1-4, for outgoing vessels from size class >100,000 dwt

Page-A47-


F.3 Vessel speed distribution over cross section

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)



Figure F.21 Vessel speed distribution over cross sections 1-4, for incoming vessels from size class <10,000 dwt

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)



Figure F.22 Vessel speed distribution over cross sections 1-4, for outgoing vessels from size class <10,000 dwt

Page-A48-


−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)



Figure F.23 Vessel speed distribution over cross sections 1-4, for incoming vessels from size class 10,000-40,000 dwt

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)



Figure F.24 Vessel speed distribution over cross sections 1-4, for outgoing vessels from size class 10,000-40,000 dwt

Page-A49-


−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)




−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)




Page-A50-


−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)




−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)




Page-A51-


−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)



Figure F.29 Vessel speed distribution over cross sections 1-4, for incoming vessels from size class >100,000 dwt

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)

−200 −100 0 100 2000

5

10

15


Ave

rage

ves

sel s

peed

(kn)



Figure F.30 Vessel speed distribution over cross sections 1-4, for outgoing vessels from size class >100,000 dwt

AppendixG

Genericrules

Page-A54-

Genericrules

Appendix G Generic rules

Thisappendixshowsthecharacteristicsofthederivedgenericnormaldistributionsforthedifferentpre-definedcrosssections.Theresultsarepresentedintables,inwhichthedistributionforeverysizeclassispresent.Alsotheinfluenceoftheexternalcircumstancesishandledinthisappendix.Severalfiguresshowtherelationshipbetweentheexternalinfluenceandthedeviationfromtheaveragevesselpathandvesselspeed.

G.1 Vessel and vessel speed distribution

Thedifferentpartsinwhichthetotalcaseareaissplit,areintroducedinChapter8.Belowfirstafigureofthespecifiedpartisgiven,togetherwiththecrosssectionsthatarehandled.

G.1.1 Part 1

5.9 6 6.1 6.2 6.34.45

4.455

4.46

4.465

4.47

4.475

4.48

4.485

4.49


Y−po

si�o

n in

"Ri

jksd

rieh

oeks

grid

" [m

]

1 - A

1 - B

1 - D

1 - C

Figure G.1 The cross sections that are investigated in part 1

Table G.1 Characteristics of the different size classes in cross section 1-A

Widthofthewaterway:3000meters

Sizeclass(dwt)

Incoming Outgoing


Mean St Dev Mean St Dev Mean St Dev Mean St Dev

<10,000 2310 210 14.5 1.9 880 190 13.9 2.2

10,000-40,000 2240 310 15.1 2.1 970 230 14.7 2.5

40,0000-70,000 2100 290 11.9 2.3 1080 300 13.2 2.5

70,000-100,000 1960 250 11.5 2.2 990 370 11.5 1.9

>100,000 1900 270 12.6 2.7 1250 880 13.6 2.3

Page-A55-


Table G.2 Characteristics of the different size classes in cross section 1-B


Sizeclass(dwt)

Incoming Outgoing



<10,000 1630 130 14.1 1.9 680 160 14.3 2.1

10,000-40,000 1600 130 14.7 2.4 760 180 15.1 2.4

40,0000-70,000 1490 140 11.5 2.1 820 210 13.4 2.4

70,000-100,000 1430 140 11 2.1 860 260 11.8 2.4

>100,000 1400 130 11.7 2.8 910 260 14.2 2.2


<10,000 0.74 0.06 0.97 1.00 0.31 0.07 1.03 0.95

10,000-40,000 0.73 0.06 0.97 1.14 0.35 0.08 1.03 0.96

40,0000-70,000 0.68 0.06 0.97 0.91 0.37 0.10 1.02 0.96

70,000-100,000 0.65 0.06 0.96 0.95 0.39 0.12 1.03 1.26

>100,000 0.64 0.06 0.93 1.04 0.41 0.12 1.04 0.96

Table G.3 Characteristics of the different size classes in cross section 1-C


Sizeclass(dwt)

Incoming Outgoing



<10,000 1100 90 13.9 2.1 460 120 14.7 2.2

10,000-40,000 1080 100 14.6 2.4 520 130 15 2.1

40,0000-70,000 1000 90 11.1 1.5 560 120 13.6 2.3

70,000-100,000 980 90 10.6 1.8 600 140 12 2.4

>100,000 970 90 11 2.4 630 160 14.3 2


<10,000 0.85 0.07 0.96 1.11 0.35 0.09 1.06 0.95

10,000-40,000 0.83 0.08 0.97 1.14 0.40 0.10 1.02 0.84

40,0000-70,000 0.77 0.07 0.93 0.65 0.43 0.09 1.03 0.92

70,000-100,000 0.75 0.07 0.92 0.82 0.46 0.11 1.04 1.26

>100,000 0.75 0.07 0.87 0.89 0.48 0.12 1.05 0.87

Page-A56-

Genericrules

Table G.4 Characteristics of the different size classes in cross section 1-D


Sizeclass(dwt)

Incoming Outgoing



<10,000 660 60 13.6 2.2 230 110 15 1.9

10,000-40,000 640 60 13.8 3 240 110 15.3 2

40,0000-70,000 580 80 10.1 1.7 280 70 13.3 2.2

70,000-100,000 560 60 9.2 1.6 320 100 11.8 2.6

>100,000 560 70 9.4 2 320 110 14 1.9


<10,000 0.83 0.08 0.94 1.16 0.29 0.14 1.08 0.86

10,000-40,000 0.80 0.08 0.91 1.43 0.30 0.14 1.04 0.80

40,0000-70,000 0.73 0.10 0.85 0.74 0.35 0.09 1.01 0.88

70,000-100,000 0.70 0.08 0.80 0.73 0.40 0.13 1.03 1.37

>100,000 0.70 0.09 0.75 0.74 0.40 0.14 1.03 0.83

G.1.2 Part 2


6.2 6.25 6.3 6.35 6.4 6.45 6.5 6.554.435

4.44

4.445

4.45

4.455

4.46

4.465

4.47


Y−po

si�o

n in

"Ri

jksd

rieh

oeks

grid

" [m

]

2 - A

2 - B

2 - C

Page-A57-




Sizeclass(dwt)

Incoming Outgoing



<10,000 700 50 13.2 2.3 360 100 14.7 1.6

10,000-40,000 680 40 12.4 3.4 410 100 14.8 1.5

40,0000-70,000 650 50 8 1.1 420 60 12.8 2.1

70,000-100,000 640 40 7.5 1.4 460 90 11.2 2.4

>100,000 640 60 7.1 1.4 460 100 13.2 2


<10,000 0.82 0.06 0.91 1.21 0.42 0.12 1.06 0.73

10,000-40,000 0.80 0.05 0.82 1.62 0.48 0.12 1.01 0.60

40,0000-70,000 0.76 0.06 0.67 0.48 0.49 0.07 0.97 0.84

70,000-100,000 0.75 0.05 0.65 0.64 0.54 0.11 0.97 1.26

>100,000 0.75 0.07 0.56 0.52 0.54 0.12 0.97 0.87



Sizeclass(dwt)

Incoming Outgoing



<10,000 480 30 12.4 2.5 250 70 14 1.8

10,000-40,000 470 30 10.7 3.3 280 60 14.1 1.8

40,0000-70,000 440 40 7 1.4 290 60 11.7 1.9

70,000-100,000 440 40 6.8 1.1 310 60 10.2 2

>100,000 430 40 6.8 1.2 320 70 11.7 1.5


<10,000 0.74 0.05 0.86 1.32 0.38 0.11 1.01 0.82

10,000-40,000 0.72 0.05 0.71 1.57 0.43 0.09 0.96 0.72

40,0000-70,000 0.68 0.06 0.59 0.61 0.45 0.09 0.89 0.76

70,000-100,000 0.68 0.06 0.59 0.50 0.48 0.09 0.89 1.05

>100,000 0.66 0.06 0.54 0.44 0.49 0.11 0.86 0.65

Page-A58-

Genericrules



Sizeclass(dwt)

Incoming Outgoing



<10,000 340 40 11.7 2.4 190 80 12.9 1.7

10,000-40,000 320 30 10.1 2.8 190 70 12.3 1.7

40,0000-70,000 270 50 6.6 1.2 190 60 10.1 1.8

70,000-100,000 270 40 6.7 1.1 200 50 8.6 1.6

>100,000 270 40 6.5 1.3 200 40 9.6 1.5


<10,000 0.76 0.09 0.81 1.26 0.42 0.18 0.93 0.77

10,000-40,000 0.71 0.07 0.67 1.33 0.42 0.16 0.84 0.68

40,0000-70,000 0.60 0.11 0.55 0.52 0.42 0.13 0.77 0.72

70,000-100,000 0.60 0.09 0.58 0.50 0.44 0.11 0.75 0.84

>100,000 0.60 0.09 0.52 0.48 0.44 0.09 0.71 0.65

G.1.3 Part 3

6.48 6.5 6.52 6.54 6.56 6.58 6.6 6.62

4.43

4.432

4.434

4.436

4.438

4.44

4.442

4.444


Y−po

si�o

n in

"Ri

jksd

rieh

oeks

grid

" [m

]

3 - A

3 - B

Figure G.3 The cross sections that are investigated in part 3.

Page-A59-




Sizeclass(dwt)

Incoming Outgoing



<10,000 820 40 10.8 2.3 650 130 11.9 1.9

10,000-40,000 800 50 9.3 2.8 620 120 11.4 2.2

40,0000-70,000 710 70 6.3 1.1 630 90 8.8 1.7

70,000-100,000 720 50 6.2 0.9 630 70 7.7 1.5

>100,000 700 60 6.2 1 650 70 8.6 1.6


<10,000 0.91 0.04 0.74 1.21 0.72 0.14 0.86 0.86

10,000-40,000 0.89 0.06 0.62 1.33 0.69 0.13 0.78 0.88

40,0000-70,000 0.79 0.08 0.53 0.48 0.70 0.10 0.67 0.68

70,000-100,000 0.80 0.06 0.54 0.41 0.70 0.08 0.67 0.79

>100,000 0.78 0.07 0.49 0.37 0.72 0.08 0.63 0.70



Sizeclass(dwt)

Incoming Outgoing



<10,000 480 40 10 2.1 320 80 11.5 2.1

10,000-40,000 450 60 8.6 2.5 310 60 11 2

40,0000-70,000 380 60 6.1 0.7 310 40 8.3 1.6

70,000-100,000 380 60 5.7 0.8 320 40 7.1 1.5

>100,000 380 60 6 0.9 330 60 7.8 1.6


<10,000 0.87 0.07 0.69 1.11 0.58 0.15 0.83 0.95

10,000-40,000 0.82 0.11 0.57 1.19 0.56 0.11 0.75 0.80

40,0000-70,000 0.69 0.11 0.51 0.30 0.56 0.07 0.63 0.64

70,000-100,000 0.69 0.11 0.50 0.36 0.58 0.07 0.62 0.79

>100,000 0.69 0.11 0.48 0.33 0.60 0.11 0.57 0.70

Page-A60-

Genericrules

G.1.4 Part 4

6.44 6.46 6.48 6.5 6.52 6.54 6.56 6.58 6.6 6.62 6.64

4.41

4.415

4.42

4.425

4.43


Y−po

si�o

n in

"Ri

jksd

rieh

oeks

grid

" [m

]

x10⁵

x10⁴

4 - A

4 - C

4 - B




Sizeclass(dwt)

Incoming Outgoing



<10,000 400 70 9.2 2.3 290 60 10.4 1.7

10,000-40,000 370 70 8.1 2.5 300 50 9.8 2

40,0000-70,000 300 50 5.9 0.6 310 30 7 1.4

70,000-100,000 310 50 5.6 0.7 320 30 6 1.1

>100,000 300 60 5.7 0.7 330 30 6.6 1.3


<10,000 0.57 0.10 0.63 1.21 0.41 0.09 0.75 0.77

10,000-40,000 0.53 0.10 0.54 1.19 0.43 0.07 0.67 0.80

40,0000-70,000 0.43 0.07 0.50 0.26 0.44 0.04 0.53 0.56

70,000-100,000 0.44 0.07 0.49 0.32 0.46 0.04 0.52 0.58

>100,000 0.43 0.09 0.45 0.26 0.47 0.04 0.49 0.57

Page-A61-




Sizeclass(dwt)

Incoming Outgoing



<10,000 350 80 8 2.1 290 80 9.9 1.6

10,000-40,000 320 70 7 2.3 300 60 8.6 2

40,0000-70,000 250 40 5.1 0.9 310 60 6 1.1

70,000-100,000 250 40 4.9 0.7 300 30 5.2 0.9

>100,000 260 40 5.1 0.8 320 30 5.4 0.8


<10,000 0.50 0.11 0.55 1.11 0.41 0.11 0.71 0.73

10,000-40,000 0.46 0.10 0.46 1.10 0.43 0.09 0.59 0.80

40,0000-70,000 0.36 0.06 0.43 0.39 0.44 0.09 0.45 0.44

70,000-100,000 0.36 0.06 0.43 0.32 0.43 0.04 0.45 0.47

>100,000 0.37 0.06 0.40 0.30 0.46 0.04 0.40 0.35



Sizeclass(dwt)

Incoming Outgoing



<10,000 350 90 6.3 1.9 310 90 8.6 1.8

10,000-40,000 320 90 5.8 1.7 310 70 6.7 2

40,0000-70,000 230 30 4.3 0.9 320 70 4.6 0.8

70,000-100,000 280 70 4 0.8 300 50 3.7 0.6

>100,000 250 40 4 0.9 300 40 3.8 0.9


<10,000 0.47 0.12 0.43 1.00 0.41 0.12 0.62 0.82

10,000-40,000 0.43 0.12 0.38 0.81 0.41 0.09 0.46 0.80

40,0000-70,000 0.31 0.04 0.36 0.39 0.43 0.09 0.35 0.32

70,000-100,000 0.37 0.09 0.35 0.36 0.40 0.07 0.32 0.32

>100,000 0.33 0.05 0.32 0.33 0.40 0.05 0.28 0.39

Page-A62-

Genericrules

G.2 External influences

Asexplainedinchapter8ofthemainreport,theresultsfromthecasestudyconcerningtheexternalinflu-encesaretranformedintogenericrules.ThisisdonebygeneralisingtheX-axis,afterwhichaquantifiedlinearrelationshipisobtained.Belowthisisdoneforeveryexternalinfluencethatisfound.

G.2.1 Wind influences

−15 −10 −5 0 5 10 15−40

−20

0

20

40

60

devi

a�on

from

ave

rage

trac

k (m

)

<-- Wind from port side (m/s).......wind from stern side (m/s) −−>

> 8 5.5−8 0−5.5 0−5.5 5.5−8 > 8 −40

−20

0

20

40

60

devi

a�on

from

ave

rage

trac

k (m

)

<-- Wind from port side (m/s).......wind from stern side (m/s) −−>

y (x) = 6.25 - 2.1861 * x

Figure G.5 Influence of cross winds in the Maasmond on the average path. The left figure shows the split up in different wind speed classes.

> 8 5.5−8 0−5.5 0−5.5 5.5−8 > 8 −4

−3

−2

−1

0

1

2

o <-- Wind from port side (m/s).......wind from starboard side (m/s) −−>

devi

a�on

from

ave

rage

spe

ed (%

)

−15 −10 −5 0 5 10 15−12

−10

−8

−6

−4

−2

0

2

4

o

devi

a�on

from

ave

rage

spe

ed (%

)

<-- Wind from port side (m/s).......wind from starboard side (m/s) −−>

y (x) = 2.11 + 0.13 * x

Figure G.6 Influence of cross winds in the Maasmond on the average speed. The left figure shows the split up in different wind speed classes.

Page-A63-


> 8 5.5−8 0−5.5 0−5.5 5.5−8 > 8 −10

−5

0

5

10

15

−15 −10 −5 0 5 10 15−10

−5

0

5

10

15

<−− wind from behind (m/s).... ...wind from front (m/s) −de

via�

on fr

om a

vera

ge tr

ack

(m)

<−− wind from behind (m/s).... ...wind from front (m/s) −

devi

a�on

from

ave

rage

trac

k (m

)

y (x) = 3.7 - 0.61 * x

Figure G.7 Influence of parallel winds in the Maasmond on the average path. The left figure shows the split up in different wind speed classes.

> 8 5.5−8 0−5.5 0−5.5 5.5−8 > 8 −3

−2

−1

0

1

2

3


devi

a�on

from

ave

rage

spe

ed (%

)

−15 −10 −5 0 5 10 15−3

−2

−1

0

1

2

3

4

devi

a�on

from

ave

rage

spe

ed (%

)


y (x) = 0.64 - 0.20 * x

Figure G.8 Influence of parallel winds in the Maasmond on the average speed. The left figure shows the split up in different wind speed classes.

Page-A64-

Genericrules

−15 −10 −5 0 5 10 15−10

−5

0

5

10

<-- Wind from port side (m/s).....wind from stern side (m/s) −−>

devi

a�on

from

ave

rage

trac

k (m

)

−15 −10 −5 0 5 10 15−4

−2

0

2

4

6

<-- Wind from port side (m/s).....wind from stern side (m/s) −−>de

via�

on fr

om a

vera

ge s

peed

(m/s

) y (x) = 1.08 - 0.56 * x y (x) = 0.41 - 0.25 * x

−15 −10 −5 0 5 10 15−14

−12

−10

−8

−6

−4

−2

0

2

p<-- Wind from port side (m/s).....wind from starboard side (m/s) −−>

devi

a�on

from

ave

rage

trac

k (m

)

y (x) = -4.81 + 0.14 * x

Figure G.9 Influence of cross winds in the Beerkanaal on the average path (left) and speed (right).

Figure G.10 Influence of parallel winds in the Beer-kanaal on the average path.

Page-A65-


j

G.2.2 Current influence

−15 −10 −5 0 5 10 15−16

−14

−12

−10

−8

−6

−4

−2

0

2

4

devi

a�on

from

ave

rage

spe

ed (m

/s)

<-- Wind from port side (m/s)......wind from starboard side (m/s) −−>

−15 −10 −5 0 5 10 15−6

−4

−2

0

2

4

6

8

<-- Wind from port side (m/s)......wind from starboard side (m/s) −−>

devi

a�on

from

ave

rage

spe

ed (m

/s)

y (x) = 1.01 - 0.43 * x

y (x) = 2.03 + 0.10 * x -0.069*x^2

Figure G.11 Influence of parallel winds in the Beerkanaal on the average speed, for incoming (left) and outgoing (right) vessels.

−1.4−1.2 −1−0.8−0.6−0.4−0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4−30

−20

−10

0

10

20

<−− current from port side(m/s).......current from starboard side(m/s) −−>

devi

a�on

from

ave

rage

trac

k (m

))

−1.2 −0.8 −0.4 0 0.4 0.8 1.2−12

−10

−8

−6

−4

−2

0

2

4

devi

a�on

from

ave

rage

spe

ed (%

)

<−− current from port side(m/s).......current from starboard side(m/s) −−>

y (x) = -8.87 - 23.4 * x

y (x) = 0.34 +1.47* x-5.35*x^2

Figure G.12 Influence of cross current in part 1 on the vessel path (left) and vessel speed (right)

Page-A66-

Genericrules

Appendix H

−1.4−1.2 −1−0.8−0.6−0.4−0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4−40

−20

0

20

40

60

devi

a�on

from

ave

rage

trac

k (m

))

−1.4−1.2 −1−0.8−0.6−0.4−0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4−6

−4

−2

0

2

4

6

<−− current from behind (m/s).......current from front (m/s) −−>de

via�

on fr

om a

vera

ge s

peed

(%)

<−− current from behind (m/s).......current from front (m/s) −−>

y (x) = -11.18 + 38.08 * x y (x) = -0.33 - 3.93 * x

Figure G.13 Influence of parallel current in part 1 on the vessel path (left) and vessel speed (right)

−1.4−1.2 −1−0.8−0.6−0.4−0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4−20

−10

0

10

20

−<-− current from behind (m/s).......current from front (m/s) −−>

devi

a�on

from

ave

rage

trac

k (m

)

−1.4−1.2 −1−0.8−0.6−0.4−0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4−6

−4

−2

0

2

4

6

devi

a�on

from

ave

rage

spe

ed (%

))

<-− current from behind (m/s).......current from front (m/s) −−>

y (x) = 1.41+ 11.53 * x y (x) = -0.52 - 3.98 * x

Figure G.14 Influence of parallel current in part 2 on the vessel path (left) and vessel speed (right)

Page-A67-


−1.4 −1.2 −1 −0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4−20

−15

−10

−5

0

5

10

15

<−− current from behind (m/s).......current from front (m/s) −−>

devi

a�on

from

ave

rage

trac

k (m

)

y (x) = -1.88 + 12.08 * x

Figure G.15 Influence of parallel current in part 4 on the vessel path.

overview of a part of maasvlakte i, port of rotterdam

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