impact of side friction on speed-flow relationships

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HDMIV\REPORTS\SIDEFRICBandung 23 July 1995/KLBHDM4 project report

IMPACT OF SIDE FRICTION ON SPEED-FLOW RELATIONSHIPSFOR RURAL AND URBAN HIGHWAYSbyDr. Karl-L. Bang, SWEROAD Indonesia

TABLE OF CONTENTS

1. INTRODUCTION1.1 BACKGROUND1.2 OBJECTIVES1.3 SCOPE

2. DEFINITIONS3. GENERAL SPEED-FLOW MODEL3 - 1 Free -flow speed

3 - 2 Capacity3 -3 Traffic flow3 - 4 Actual speed4. SIDE FRICTION

4.1 General4 - 2 Identification of side frictional items4.2.1 Basic issues4.2.2 Selection of frictional items4.2.3 Field data collection4.3 Analysis of the impact of side friction4.3.1 Weighing of side friction events4.3.2 Definition of side friction classes4.4 Impact of side friction on traffic performance

4.4.1 General model4.4.2 Impact of side friction on free-flow speed4.4.3 Impact of side friction on capacity5. MODELLING OF CONGESTION AND SIDE FRICTION EFFECTS IN BDM-Q

5.1 Description of the model5.2 Comparison between the HDM-Q and IHCM speed predictionmodels.

6. CONCLUSIONS

APPEND1 ESA: Illustration of side friction conditions on interurban and urbanroads.B: Indonesian Highway Capacity Manual, Chapter 6 INTERURBAN ROADS(revised draft 23 July 1995)


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1. INTRODUCTIONBACKGROUND

In rapidly developing, densely populated countries in Asia andelsewhere considerable resources are invested in road transport whichis seen as a sector which is crucial to the development effort. In de-signing new roads and when maintaining and upgrading existing ones,procedures are needed for the estimation of traffic performance if bestuse is to be made of the resources spent for construction andmaintenance. Two different tools have been developed internationallyover the years to meet these demands:a) Highway capacity manuals (HCM), which emanate from the trafficengineering profession and are used for prediction of trafficperformance measures (speed, elay etc) as a function of trafficinteraction, geometric design and traffic control features.b) Highway design and maintenance models (HDM) which originate fromthe highway engineering profession and are primarily used for

selection of pavement management strategybymeans of comparisonsof road user costs and highway costs for different pavement typesand treatments. Free-flow speed is predicted as a basis for thesecalculations, which normally doe not include "congestioneffects".In HCM-models the analysis normally assumes flexible pavement in goodcondition, i.e. the effect of roughness is not included in themodelling. In HDM analysis on the contrary pavement condition is amajor variable influencing free-f ow speed, but congestion effects arenormally not modelled .The effect on speed of events happening along the road, commonlydescribed as side friction, is normally not included in HCM-models,which traditionally have originated from developed countries with ahigh level of motorization and low amount of road side activities.Although HDM-models often are based on field surveys in developingcountries, they also fail to include this effect. Attempts to tackleboth the congestion and the side friction effects have however beendone in Indonesia (Bang et a1 1995) and by the World Bank (Hoban et a11994) as described below.

1.2 OBJECTIVESSWEROAD has been contracted by the SwedishNational Road Administration(SNRA) to support the development of a new Highway Development andManagement Tool (HDM-4, ointly sponsored by IBRD, ADB, ODA and SNRA)concerning modification of vehicle speeds by congestion. Thisassistance is to a large part based on experiences gained in theongoing project to develop an Indonesian Highway Capacity Manual (IHCM)with SWEROAD as Lead Consultant. The objective of this report is toreview and discuss these results with special focus on the modellingof side friction impacts on speed and capacity for interurban roadlinks. This includes the following parts:a) Summary of analysis results of side friction impacts and speed-flow prediction modelling in IHCM.b) Discussion of speed-flow and side friction modelling in HDM-Q,and recommendations for application in HDM-4.


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C) Discussion regarding the implementation of the results in HDM-4in the form of the HDM-Q model.

1.3 SCOPEThe IHCM speed-flow prediction model assumes that the trafficperformance of a road link is a function of the conditions on the roadlink itself, i.e. the impact of bottlenecks such as major intersectionsare not included. Minor road junctions and exits/entries to roadsideproperties are however considered.Two slightly different models have been developed in IHCM for urban andinterurban conditions. The latter is used for analysis of a range ofconditions from rural, with basically undeveloped roadside land use,to almost continuous roadside (strip) residential and/or commercialdevelopment typical for interurban roads in densely populated areas.

DEFINITIONSThe terminology used in this paper has been developed in the IHCMproject (see Appendix B). A number of key terms are listed below:

C CAPACITY(pcu/h) Maximum sustainable (stable) trafficflow over a road section under givenconditions (e g geometric design,environment, traffic etc.)Q TRAFFIC FLOW Number of motorized vehicles passing apoint on a road per unit of time,expressed in veh/h (Q,,,, , pcu/h (Qpcu)rAADT (Annual Average Daily Traffic).pce PASSENGER CAR Factor describing different vehicle typesEQUIVALENT with regard to their impact on averagelight vehicle speed when added to a mixedflow as compared to that of a lightvehicle (i e for passenger cars and otherlight vehicles with similar chassis pce =

1-01.pcu PASSENGER CAR UNIT Unit for traffic flow, where the flow ofdifferent vehicle types have been

converted to the corresponding flow oflight vehicles using pce.DS DEGREE OFSATURATIONFV, BASE FREE-FLOWSPEED

Ratio of flow to capacity.DS = Qpcu/CpcuFree-flow speed for a road segment for apredetermined set of ideal conditions(geometry, traffic flow pattern and envi-ronmental factors)

FV FREE FLOW SPEED (1) The theoretical average speed oftraffic when density is zero, i-e, hereare no other vehicles present.


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V SPEED

W,, EFFECTIVECARRIAGEWAYWIDTH

(2) Speed of a vehicle which is notrestrained by any other vehicles (i.e.speed at which drivers feel comfortabletravelling under the geometric, environ-mental, and traffic control conditionsexisting on a road segment with no othertraffic)Actual space-mean speed during prevailinggeometric, environmental and trafficconditions.Carriageway width available fortraffic movement, after any reductiondue to parking. (Note: Paved shoulders areconsidered to be a part of the effectivecarriageway width in certain cases)

SF SIDE FRICTION Events causing an impact on traffic per-formance on the road segment.LV LIGHT VEHICLE Two-axle motor vehicle on four wheels withan axle spacing of 2.0 - 3.0 m used forpassenger and/or goods transportation.MHV MEDIUM HEAVY Two-axle motor vehicle with an axleVEHICLE spacing of 3.5 - 5.0 m (including smallbuses, 2-axle trucks with six wheels).LT LARGE TRUCK . Three-axle trucks and truck combinationswith axle spacing c 3-5 m (first tosecond axle).LB LARGE BUS

UM UNMOTORISEDVEHICLE

Two- or three-axle buses with an axlespacing of 5.0 - 6.0 m.Unmotorised vehicle on wheels (includingtricycles, bicycles, animal drawncarriages, pushcarts etc) Note: In IHCMunmotorised vehicles are not considered asa part of the traffic flow but as an el-ement of side friction.

3 . GENERAL SPEED-FLOW MODELThe single-regime model can be calibrated to mode1 speed-flowrelationships on most road types:v = wx[l - (D/D~)t - l l ] l / ( l - ml ; Do/Dj [ (1-m) ( P -m) l/"-l)whereD = Density (pcu/km) (calculated as Q/V)D = Density at completely "jammed" roadDO = Density at capacityP , m = Constants

for two-laneundividedroads the speed-flow relationship is often closeto linear. Figure 3:l illustrates Indonesian field data from a numberof sites normalized for a standard two-lane, wo-way undivided (2/2 D)urban road with carriageway 7 m. The observations are divided into twocategories representing stable (marked with circles) and unstable


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(marked with stars) flow conditions, where the latter are defined byhaving density higher tha n Do.

VALL vs FLOW for 212 URBAN RO ADS (CLASS=P)

Flow (pculh)

Figure 3 1 Field observations for 2/2 UD urban roads ( I H a )Figure 3 :2 illustrates a schematical speed-flow model for 2/2 UD roadsbased on these observations.

Figure 3:2

Traffic flow Q pcu/h

General spee d-fl ow model for 2/2 UD roads (IHCM)5


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The speed at zero flow (point A) represents the free-flow speed (Fv)as determined by existing conditions. If there is no speed limit (orno enforcement of existing limit) the speed drops continuously as theflow increases.An almost flat portion of the speed-flow relationshipat low flow (represented by the dashed line B-C in the figure) can beobserved in cases when the speed resulting from an en rced speed-limitis lower than the free-flow speed as determined by geometric andenvironmental conditions only.When Q increases to a value (Q,) close to capacity C at point D in thegraph flow conditions change from "laminar" to "turbulentM withfrequent speed changes. This results in a steeper speed drop untilcapacity (C) is reached at point E at the speed V,,,. When the trafficdemand is near to or higher than capacity, the density will continueto increase which results in congested stop-and-go conditions withreduced flow and speed which stabilizes at Vja,.Prediction of actual speed thus requires the following steps asdescribed in Sections 3.1 - 3 4 below.1. Prediction of free-flow speed FV;2. Prediction of capacity C;3. Conversion of the traffic flow into passenger car units;4 . Calculation of actual speed using the calibrated speed-flowmodel.

3.1 FREE-FLOW SPEEDThe basic equation for prediction of FV developed in IHCM is asfollowsFV = (FVo+ V,) x FWsF FWR CwhereFV -- Free-flow speed for light vehicles at actualconditions (km/h)

N o -- Base free-flow speed for light vehicles at pre-determined standard (ideal) conditions (km/h)Fv, -- Adjustment for effective carriageway width (km/h)F%F -- Adjustment factor for side friction conditionsFWRC -- Adjustment factor for road function class

Base free-flowspeeds for different roadandvehicle types obtained forIndonesian conditions are shown in Appendix B, page 47 Table B-1 . Forflat terrain the vary between 81 - 58 km/h, for hilly terrain between60 - 38 km/h. IHCM also includes procedures for determination of FV forspecific horizontal and vertical alignment conditions, e.g. forspecific grades.CAPACITY

The basic equation for determination of capacity in IHCM is as follows:C = C, x FC, x FC,, x FC,,whereC = actual capacity (pcu/h)C, = base (ideal) capacity for predefined (ideal) conditions(pcu/h)FC, = road width adjustment


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FC,, = directional split adjustment factor for undivided roadsFC,, = side friction and shoulder width adjustment factorBase capacity values for different road and terrain types obtained forIndonesian conditions are summarized in Table 3:l below.

Table 3:l Base capacity C, for Indonesian interurban roads ( IHCM) .

Road type/Terrain typeFour-lane divided- Flat terrain- Rolling terrain- Hilly terrain

Four-lane undivided- Flat terrain- Rolling terrain- Hilly terrain

Two-lane undivided- Flat terrain- Rolling terrain- Hilly terrain

3 -3 TRAFFIC FLOWThe speed-flow relationship requires the flow to be expressed inpassenger carunits (pcu) throughmultiplicationofthe different partsof a mixed flow with the passenger car equivalent (pce) for eachvehicle type and condition.

Basecapacity(pcu/h)190018501800170016501600

310030002900

A set of passenger car equivalents (pce) for Medium heavy vehicles(MHV), Large buses (LB), Large trucks (LT) (including truckcombinations) and Motorcycles are given in IHCM as a function of roadtype, terrain type and traffic flow (veh/h) For 2/2 UD roads the pcefor Motorcycles (MC) also depend on the carriageway width. For LightVehicles (LV) pce is always 1.0. Unmotorised vehicles (UM) are notincluded in the traffic flow in IHCM, but are treated as a sidefriction events (slow-movingvehicles) s describedin Section 3 below.Table 3 2 below records pce for two- ane two-way undivided roads as afunction of total traffic flow (veh/h). The pce values are determinedby means of interpolation.

Comment

Per lane

Per lane

Total in bothdirections

3.4 ACTUAL SPEED

-

When the capacity (C) and the hourly traffic flow (Q) have beendetermined, the degree of saturation (DS) can be calculated by divisionof the demand flow Q with C (both expressed in pcu):

The actual speed at given traffic, side friction and geometricconditions is then determined as a function DS and free-f ow speed (FV)using Figure 3:3 (two-lane undivided roads 2/2 UD) and Figure 3:4(four-lane roads and one-way roads 4/21.


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' ( D H I ) speox ueqxruaquT clfl Z / Z uorqexnqesgo aax6ap pue paads ~0 13 -a ax g o uorqaung e se paads

HI) speox an z / z xog (aad) sq ua~ en rn ba e3 xa6uassed Z : E aTqeL

LTT?H

6 u r ~ ~ o x

7eTd

ad-hu r e x x a ~

-OOS7:


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Figure 3 4 . Speed as a function of free-flow speed and degree ofsaturation for f ur-lane and one-way interurban roads(IHCM)

S I D E FR ICT ION

In densely populated, developing countries there is often a great dealof activity at the edge of the road, both on the carriageway and onshoulders and sidewalks, which interacts with the flow of traffic,causing it to be more turbulent and adversely af fecting performance aswell as capacity. This effect occurs on both urban and rural roads,although the amount of activity 'and its effect is generally muchgreater on the former.Roadside activities in Asian cities giving rise to side frictioninclude- pedestrian movements, often taking place on the carriageway dueto sidewalks being blocked by street trading and otheractivities;- undisciplined stopping by small motorised public transportvehicles and human-powered pedal trishaws, which may stopanywhere to pick up and set down passengers;- on-street parking, including parking and unparking activities,often assisted by parking attendants;- vehicles entering and leaving roadside premises, via gates anddriveways, as there is generally no control of access.


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These activities either do not occur in Western countries, or theirintensity is generally so small that their effects have not beendirectly takeninto account in any western speed-flow odels andproce-dures for the estimation of highway capacity and performance.Side friction may be taken account of indirectly however, for examplein the U.S Highway Capacity Manual (TRB, ev 1994 in which adjustmentfactors for capacity and service flow of multilane highways arespecified according to whether a highway segment is "rural" orvsuburbanu. he "suburban" classification is intended to reflect thegreater density of roadside development and the frequency of minorjunctions and driveways on suburban as compared with rural roads.Though an indirect approach of this type was initially considered forIndonesian urban and suburban roads, it was found that with the greaterextent and intensity of frictional activities in Indonesia, theindirect approach was inadequate to reflect the importance of sidefriction in capacity and traffic performance analysis.

4.2 IDENTIFICATION OF SIDE FRICTIONAL ITEMS4.2.1 Basic issuesConsideration was given in IHCM to incorporate side friction effectsindirectly in the analysis, by classify%nghighway segments in relationtoa) Location:

- CBD- Collar (the remainder of the urban area)- Edge (suburban highways linking with the regional highwaynetwork)b) Road function- Arterial- Collector- LocalC) Roadside landuse- urban: Percentage of road segment frontage withcommercial, educational, residential etc.deve pment- interurban: Percentage of road segment frontage which hadany built development.d) Population (only for urban areas)

Although some of these factors were found to have a significant impacton free-flow speed, and were subsequently incorporated in theIndonesian manual, they were not sufficiently correlated with thefrequency of side friction events to be able to ignore that variablein the speed-flow model.A further issue was whether some potential frictional items should betreated separately or considered to be part of the flow of traffic. Onesuch item was minibuses, which form a large proportion of traffic insome cities, but which stop at any point to pick up and to set downpassengers they may also cruise slowly in the hunt for passengers. ManyAsian cities also have pedal trishaws which may form a large part ofvehicle flow, but which also stop to serve passengers.


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4 . 2 . 2 Selection of frictional itemsIn deciding which side-frictional items to measure, as having thepotential significantly to affect capacity and performance, generalobservation of the characteristics of Indonesian traffic wassupplemented by prior research on the effects of side friction on threeurban/suburban roads in Bandung (Negara, 19 1 unpublished) This workconfirmed the prior expectation that pedestrian movements, stoppingpublictransportvehicles, arking activities andvehicles enteringandleaving roadside premises all had significant capacity effects. Ini-tially, these items were measured in a disaggregated way, but laterwere combined into fewer, broader classes as described below.The side frictional items which were finally to be included in datacollection were as follows, for urban roads:1. Pedestrian movements:

- Total flow of pedestrians along the highway (ped/h)- Total numbers of pedestrians crossing the highway

(ped/h/km)2. Vehjcles stopping, differentiated according to whether the stopwas on the shoulder or the carriageway. (veh/h/km):

- Public transport minibuses ("angkutan kota")- Large buses- Unmotorised public transport ("trishaws")- Non-public transport vehicles

3 Parking (veh/h/km)- No. of parked vehicles (on carriageway or on shoulder)- No. of unparking maneuvers4. Access to roadside premises:- No. of vehicles entering and leaving roadside premises(veh/h/km)For interurban roads, the following items were selected:1. Number of pedestrians, whether walking along or crossing(ped/h/km)2. Number of stopping and parking maneuvers (veh/h/km);3. Number of motor vehicle entries and exits into and out ofroadside properties and side roads (veh/h/km);4. Flow of slow-moving vehicles (bicycles, trishaws, horsecarts,oxcarts,. tc) (veh/h)

4 . 2 . 3 Field data collectionOverall, data were collected from 35 urban/suburban road segments in1991-1992, and 115 interurban road segments in 1993-1994. For urbansites the data collection was based on video observation (flow andspeed) and manual observation (friction) over a long base, as shown inFigure 4 3 l. Each half of the long base had a separate team offriction surveyors who recorded friction events manually.


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Study section 2 0 0 m to 300 rn

Figure 4.2: Layout of the long base study section (IHCM)

For interurban roads, friction was collected in conjunction with spotspeed data collection by means of pairs of pneumatics tubes. Frictiondata was manually collected over a long base extending about 100 m eachside of the spot-speed measurement station. The side friction surveyresults weremanually transcribe into computer files directlyfromthefield data sheets.

4.3 ANALYSIS OF THE IMPACT OF SIDE FRICTION4.3.1 Weighing of side friction eventsA number of factors were identified, initially by correlation andregression analysis for individual sites, variations in which wereconsidered to be likely to affect the speed-flow elationships. Thesewere as follows:- Carriageway width- Presence of shoulder or curb- Shoulder width and usability for traffic and parking- Presence or absence of a mediah/divider- Directional split- Side friction events (see above)- City size (a proxy for driver behavior variation)- Road function class- Road side land use

The next step in the analysis was to combine the data from all sitesin each road class in one data base, and to make multiple regressionanalysis with space mean speed as the dependent variable. The resultsfrom this analysis were then used to adjust (normalise) the speedobservation for eachindividual site to reflect the differences betweeneach actual site and a pre-defined base case for all variables exceptside friction. The adjustments during the normalisation process weremade to flow, thus moving the speed-flow curve to the right or to theleft if the studied casewas sub-standardor ver-standard respectivelyThe normalised data was then used for multiple regression analysis ofthe impact of the different side friction events on light vehicle free-


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f l o w s p e e d a s a b a s i s f o r c a l c u l a t i o n o f r e l a t i v e i m p a c t o f e a c h t y p eo f e v e n t , see T a b l e 4 . 3: 1 b e l o w .

T a b l e 4 .3 : l R e l a t i v e i m p a c t o f s i d e f r i c t i o n e v e n t s o n l i g h tv e h i c l e s p e e d

E v e n t t y p e

P e d e s t r i a n f l o w( W a l k i n g p e d / h +c r o s s i n g p e d Ih ,2 0 0m )V e h i c l e s t o p s a nd p a r k i n gm a n u e v r e s( e v e n t s / h 1 2 0 0 m )V e h i c l e e n t e r i n g a n de x i t i n g r o a d s i d e p r e m i s e s( v e h / h , 2 00m)S l o w - m o v i n g v e h i c l e s( v e h / h )

4 . 3 . 2 D e f i n i t i o n o f s i d e f r i c t i o n c l a s s e sT h e r e l a t i v e w e i g h t s r e c o r d e d i n T a b l e 4 . 3 : l w e r e u s e d t o c a l c u l a t e aw e i g h t e d t o t a l o f s i d e f r i c t i o n e v e n t s ( F R I C ) a s e x e m p l i f i e d f o ri n t e r u r b a n r o a d s b e l ow :

C o d e

PED

PSV

EEV

SMV

FRIC = PEDx0.6 + PSVx0.8 + EEVxl .0 + SMVx0.4To s i m p l i f y c o n s i d e r a t i o n o f s i d e f r i c t i o n i n t h e s p e e d- fl o w a n a l y s i sa n um ber o f s i d e f r i c t i o n c l a s ses w e r e d e f i n e d a s sh ow n i n T a b l e s 4 .3 :a n d 4 .3 :3 b el ow f o r i n t e r u r b a n a n d u r b a n r o a d s . T he d i f f e r e n t s i d ef r i c t i o n c lasses a r e a l s o e x e m p l i f i e d b y m ea ns o f p h o t o g r a p h s made f r o ms i t e s d u r i n g m an u al s i d e f r i c t i o n r e c o r d i n g . F rom t h i s m a t e r i a lp h o t o g r a p h s h a v e be en s e l e c t e d w h i ch r e p r e s e n t e a c h s i d e f r i c t i o n c l a s sf o r u r b a n a s w e l l a s i n t e r u r b a n c o n d i t i o n s a s s ho wn i n A p p e n d i x A.

R e l a t i v e w e i g h tU r b a nr o a d s

0 . 5

1 . 0

0 .7

0 . 4

T a b l e 4 . 3 : 2 C l a s s i f i c a t i o n o f s i d e f r i c t i o n f o r i n t e r u r b a n r o a d s( I H C M )

I n t e r u r b a nr o a d s0 . 6

0 . 8

1 . 0

0 .4

Weighted frequencyof events (both sides ofroad) FRIC< 5 0

50 - 149150 - 249250 - 350

> 350

Typical conditions

Rural, agriculture or undeveloped;almost no activitiesRural, som e roadside buildings &activitiesVillage, local transport & activi-tiesVillage, som e market activitiesAlmost urban, market/businessactivities

Side frictionclassVery lowLowMediumHighVeryhigh

VLLMHVH


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Table 4.3:3 Classification of side friction forurban roads (IHCM)

Weighted frequencyof events (both sid es ofroad) FRIC< 100

100 - 299300 - 499

500 - 899

> 900

4.4 IMPACT OF SIDE FRICTION ON TRAFFIC PERFORMANCE4.4.1 General model

Typical conditions

Residential area, almost noactivitiesResidential area, some publictransport etcIndustrial area with some roadsideshops etcCommercial area with high roadsideactivityCommercial area with very highroadsi de market activity

Side friction events have a negative impact on traffic performance overthe whole flow range as discussed below:a) Im~act n free-flow sweed

Side frictionclass

The desired speed at free-flow conditions is a function of roadalignment, cross section and road type as well as environmentalconditions regarding type of area and roadside activities. Sidefriction events such as stopping vehicles, pedestrians etc.reduce the desired speed in order for the driver to maintain asafe speed with consideration tothe risk for unexpected roadwayblockage and conflicts with other traffic elements which maysuddenly appear. This effect is illustrated with a free-flowspeed reduction from FV, to FV when the speed-flow curveintercept with the Y-axis moves from A, to A in Figure 4 -4 1below.

Very lowLowMediumH i g hV e r yhigh

Imwact on cawacitv

V LLMHVH

As the speed is reduced due to traffic interaction when the flowincreases, the impact of side friction events on speed forreasons of traffic safety is gradually reduced. The side frictionhowever reduces the capacity of the road due to factors such as:- temporary reduction of carriageway width at parking andstopping manuevres- change from un-interrupted to partially interrupted flowconditions due to crossing conflicts with pedestrians,entry of vehicles from minor roads and roadside premisesetc.

This effect is illustrated in Figure 4.4:l by a reduction incapacity from C, to C, and a corresponding drop of the speed atcapacity from V,~,,, to V,,, .The side friction impacts on free-flow speed and capacity thus causea reduction of speed over the entire flow range as well as a reductionof capacity. This is illustrated in Figure 4.4 1 by a shift of thespeed-flow curve from A,- Do - E, to A - D - E. Since the generalizedspeed curves in IHCM as shown in Figures 3:3-4 above show the


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relationship between free-flow speed, degree of saturation (DS Q/C)and actual speed, they are able to cope with both these effects withoutchanging the shape of the generalized model.

Speed Kmlht

C CoTraffic flow pculhLegend Curve A, - D, - E, No side frictionCurve A - D - E: High side friction

Figure 4.4 1 Impact of side friction on speed and capacity

4 . 4 . 2 Impact of side friction on free-flow speedThe normalised data base described in Sections 3 and 4.1-3 above wasused to analyze the impact of side friction events on free-f ow speed.Since it was found that the impact was correlated with effectiveshoulder width, this variable was also included in the resulting Table4.4:l for interurban roads below.The impact of side friction in the most severe case for 2/2 UDinterurban roads shown in the table reduces free-flow speed with afactor 0.76,e.g. a free-flow speed at 65 km/h at no side friction isreduced by 16 km/h to 49 km/h at very high side friction and narrowshoulders.Similar analysis for 2/2 UDurban roads showedthatthe free-flow speedwas reduced from 44 km/h at no friction to 26 km/h at very high sidefriction as defined for urban conditions, i e. by 18 km/h or a factor0.59. For four-lane roads the observed side friction impact wasslightly less, with a small further reduction also observed due to theexistence of a median.

4 . 4 . 3 Impact of side friction on capacitySpeed-flowdensityregressions sing the single-regime odel describedin Section 3 above was applied for analysis of the impact of sidefriction on capacity. Table 4.4:2 shows the resulting side frictionadjustment factor for different side friction classes for interurbanroads. For urban roads the capacity reduction generally was 30% higher


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in each friction class (i.e. a reduction factor 0.90 for interurbanroads becomes 0.87 for urban roads).

Table 4.4 :1 Adjustment factor FFV,, for the influence of sidefriction and shoulder width on the free-f ow speed oflight vehicles, interurban roads (IHCM)

Road type

Four-lane divided4/2 D

Four- aneundivided4/2 UD

Two-lane undivid-ed2/2 UD

Table 4.4 2 Adjustment factor FC,, for the influence of sidefriction on capacity, interurban roads (IHCM).

Side fric-tion class(SFC)

Very lowLowMediumHighVery highVery lowLowMediumHighVery highVery lowLowMediumHighVery high

Road type

4/2 D

2/2 UD4/2 UD

Adjustment factor for sidefriction and shoulder width(km/h)- - - - - - - - - - - - - - - - - - - - - - - -Effective average shoulderwidth Ws (m)

Side fric-t ionclass

VLLMHVHVLLMHVH

2 m1.000.980.970.960.951.000.980.970.960.951.000.980.970.950.93

< 0.50.990.950.910.870.830.970.930.880.840.80

1.51.010.990.970.950.931-000.970.940.910.88

1.01-000.970 :940.910.880.990.950.910.870.83

> 2.01.031-011.000.990.971.021-000.980.950.93 -


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5. MODELLING OF CONGESTION AND SIDE FRICTION EFFECTS IN HDM-Q5.1 DESCRIPTION OF THE MODELThe World Bank Highway Design and Maintenance Model is widely used forthe evaluation of road maintenance and improvement options. Asignificant limitation of the current standard model (HDM-111) s thatit does not take account of speed reduction caused by trafficinteractions as the flowincreases. Additional features have thereforebeen suggested (Hoban et a1 1994) to allow these types of analysis. Theexpanded model is known as HDM-Q, which is designed primarily foranalysis of interurban roads.The generalised speed-f ow model used in HDM-Q is shown in Figure 5.1:below.

Speed

tS IS2 .s3-

Smin --

I I I IQ 1 4 2 QCAP Flow(Q 1 =XQ1 x QCAP) (42=XQ2 QCAP)

Figure 5.1:l Speed-flow model used in HDM-Q (Hoban et a1 1994)

The main parameters used in HDM-Q are as follows:- QCAP: Road capacity 2-way (pcu/h)- XQ1 & XQ2 Default values see Table 5.1:l below- S1, S2, S3: Free speed (function of desired speed, roadwidth, grades, curves & roughness determined

for each vehicle type using the HDM-I11 model.- SMIN Speed of a typical slow vehicle (15th ercentilespeed for the slowest vehicle class)- CV: Coeff. of variation of speeds for the abovevehicle class (standard deviation divided bymean) Default 0.15.- SJAM: Absolute minimum average speed under heavytraffic condition. Default see Table 5.1:l.

- XFRI: Side friction effect: 0 - 1 (from high to lowlevel), regarding impact on s~eed (i.e notcapacity)


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XQl = No volume effect on speed (proportion of capacity)XQ2 = Speeds converge (proportion of capacity)QCAP = Road capacity, 2-way (pch)SJAM = Jam speed at capacity (kmlh)

Road Type

Single Lane RoadIntermediate RoadTwo Lane RoadWide Two Lane RoadFour Lane Road

Table 5.1:l Speed-flow-capacity arameters in HDM-Q (Hoban et a11994)

5.2 COMPARISON OF THE HDM-Q AND IHCM SPEED PREDICTION MODELSIn principal the speed-flow models proposed for 2/2 UD roads in IHCMand HDM-Q are very similar. Some modifications to the HDM-Q model arediscussed below which would lead Co better compatibility between thetwo models and improve the speed-prediction model in HDM-Q.

Width(of traveled w ay )

u p t o 4 m4 to 5.5 m5.5 to 9 m9 t o 1 2 m

12 m or wider

a) Free-flow sweed

xQ1

0.00.00.10.20.4

XQ2

0.70.70.90.90.95

- HDM-111 uses a mechanistic model for the determination of free-flow speed as a function of alignment, cross section androughness. This method is best suited for analysis of specificsegments for which these data is available. For longer roadsegments the IHCM approach based on general terrain types mightbe more suitable for estimation of base free-f ow speed, exceptthat the impact of roughness has to be added.- IHCM also considers road function class and landuse as adjustmentfactors.

QCAP

6001800280032008000

- In IHCM the side friction adjustment factor is a function ofshoulder width, in HDM-Q not. Furthermore it is related to actual

SJAMkmh--102025

3040


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event frequency, which even if it is not measured can beestimated with the help of standard photographs (Appendix A) anddescriptions for different friction classes as shown above.

- HDM-Q only considers the effect of roadwidth, IHCM also considersthe effect of side friction/shoulder width and directional spliton capacity.- IHCM uses pce regarding the impact on speed which are determinedas function of traffic flow level expressed in veh/h.

- IHCM uses a relationship between speed and degree of saturation,which has advantages in terms of generalisation of the model.- HDM-Q uses a set of linear models to describe the speed-flowrelationship. In IHCM a linear model is used for two-lane roads,with the breakpoint 92 and the corresponding speed SJAMdetermined as function of free-flow speed. For multi-lane roadsIHCM uses the single-regime model with parameters determined asa function of free-flow speed and capacity.- HDM-Q applies a constant speed-adjustment factor due to side-friction over the entire speed-flow ange. In IHCM the adjustmentis made to free-f ow speed and to capacity, which also leads toa side friction impact over the whole range degree of saturation.

6. CONCLUSIONSActivities at the roadside can always be expected to affect thecapacity of a highway and the speed at which it operates. However, inmany developing Asian countries, the range and intensity of such sidefriction is so great that these activities need to be incorporatedexplicitly into procedures for calculation of speed and capacity ofroad links. Empirical studies carried out in the Indonesian HCM project(IHCM) have shown that side friction may reduce free-f ow speed on two-lane two-way interurban roads with up to 16 km/h, and capacity with upto 20 per cent in comparison with very low friction conditions. It istherefore evident that the impacts of side friction need to be takeninto account in geometric design analysis as well as in pavementmanagement analysis for many countries in Asia and elsewhere.The experience from Indonesia (IHCM) has shown how side frictioneffects can be incorporated in general speed-flowmodels for differentroad types in urban as well as interurban areas. The HDM-Q model alsohas this capability, and can already in its present version becalibrated to model most of the factors identified in IHCM with acertain amount of "manipulation". number of suggestions have howeverbeen made for revision of the HDM-Q model, which would improve itsspeed prediction capability and make it easier to calibrate for localconditions. The HDM-Q model should theref re be a workable base for theISOHDM project


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REFERENCES

1. Bang, K-L; Bergh T. and Marler N. . Highway Capacity Manual PartI Urban Roads. Directorate General of Highways Indonesia NO.09/T/BNKT/1993, Indonesia, January 1993.2. Bang, K-L; Carlsson A. Interim Manual for Interurban Roads andMotorways. Indonesian Highway Capacity Manual Project, Bandung.Directorate General of Highways Indonesia August 1994 (revisedJuly 1995).3. TRB, Highway Capacity Manual (Revision of 1985 edition).Transportation Research Board; Washington D.C. 1994.4. Hoban, C.J.; William Reilly, Archondo-Callao. Economic Analysisof Road Projects with Congested Traffic. Infrastructure & UrbanDevelopment Department, The World Bank, Washington, D.C. USADecember 1994.5. Bang, Karl-L.; Carlsson, Arne; Palgunadi. Development of speed-flow relationships for Indonesian rural roads using empiricaldata and simulation. Paper 950397 presented at TRE3 AnnualMeeting, Washington D.C. January 1995 (under publication).6. Bang, Karl-L.; Harahap, Gandhi; Speed and congestion effectmodelling in Indonesia. Proceedings ofthe ISOHDM Workshop, KualaLumpur November 1994.7. Easa, S .M; ay A. ; Generalized Procedure for Estimating Single-and Two-Regime Traffic-Flow Models. Transportation ResearchRecords 772; Washington D.C. USA 1980.


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Figure A-4:3 Med ium sid e friction on an interurban road

Figure A-4:4 High side friction on an interurban road46


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F i g u r e 6 . V e r y Low S i d e F r i c t i o n o n An U r b a n R o a d

F i g u r e 7 . Low S i d e ~ r i c t i o n n An Ur b a n R o ad


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6

p-

p


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F i g u r e 1 0 . V e ry H i gh S i d e F r i c t i o n o n An U r ba n Road

impact of side friction on speed-flow relationships

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