decision support systems for evacuation planning: supply, assignment and routing, di giuseppe...

Decision Support System for evacuation planning: supply, assignment and routing

Giuseppe Musolino, Antonio Polimeni, Antonino Vitetta,

[email protected], [email protected], [email protected]

UNIVERSITÀ DEGLI STUDI MEDITERRANEA DI REGGIO CALABRIADipartimento di Informatica, Matematica, Elettronica e Trasporti

Facoltà di Ingegneria

Sesta Conferenza Nazionale in Informatica e Pianificazione Urbana e TerritorialeSesta Conferenza Nazionale in Informatica e Pianificazione Urbana e Territoriale13 - 15 September 2010, Potenza - Italy13 - 15 September 2010, Potenza - Italy

mailto:[email protected]



2Progetto Progetto SICUROSICURO

STRUCTURE OF THE PRESENTATIONSTRUCTURE OF THE PRESENTATION

I. INTRODUCTION

II. DECISION SUPPORT SYSTEM (DSS)

III. APPLICATION

IV. CONCLUSION



I. INTRODUCTION


III. APPLICATION

IV. CONCLUSION


Natural Man-made

DANGEROUS EVENT

Introduction


DANGEROUS EVENT EVOLUTION

t0 emergency planning activities start

t1 occurrence of forthcoming disaster is notified or supposed forecasted

t2 event occurs and starts its effects

t3 system vulnerability starts to change

t4 system vulnerability stops changing

IntroductionDANGEROUS EVENT


Emergency ConditionsOrdinary

Conditions OrdCond

•evacuation procedures

identification


simulation


validation


organization


execution

OPERATIVE STAGE

EVACUATION

PLANNING

ApplicationACTIVITIES IN RESPONSE TO DANGEROUS EVENT


tA first evacuated vehicle departure time

tP last evacuated vehicle arrival time

tA tPt1 t4t0

time

t3

EVACUATION CAN’T START

RESIDUAL RISK

IntroductionACTIVITIES IN RESPONSE TO DANGEROUS EVENT


tA tPt1 t4

t0

time

t3tP

II TARGET minimize tp - taI TARGET ta , tp < t3

tA first evacuated vehicle departure time

tP last evacuated vehicle arrival time



PROBLEM

Introduction

path choice

ACTIVITIES IN RESPONSE TO DANGEROUS EVENT


path choice

driver

external authority

PROBLEM DECISION MAKER



path choice

driver

external authority

PROBLEM DECISION MAKER SUPPORT

driver’s experience GPS navigator



path choice

driver

external authority



DSS(Decision Support System)



path choice

driver

external authority




and Tools



Introduction

DSS

EVACUATION PLANNING OPERATIVE STAGE


Introduction

DSS

EVACUATION PLANNING OPERATIVE STAGE

LITERATURE REVIEW

DSS FOR SUPPLY- DEMAND DSS FOR PATH/ROUTE


ORDINARY CONDITIONS

DYNAMIC PROCEDURES

TEMPORAL SYSTEM EVOLUTION

•Peak hours•Temporary over-saturation phenomena•Queues formation and dispersion•Driver behaviour (microscopic approach)o on link

• acceleration• speed• lane-changing

o at node• gap-acceptance

o on network• path choice

SUPPLY-DEMAND INTERACTION

STATIC PROCEDURES

STATIONARY CONDITIONS

•Constant demand•Constant supply

Introduction

SUPPLY-DEMAND


EMERGENCY CONDITIONS

DYNAMIC PROCEDURES







STATIC PROCEDURES

STATIONARY CONDITIONS

•Constant demand•Constant supply

Introduction

SUPPLY-DEMAND


EMERGENCY CONDITIONS

DYNAMIC PROCEDURES







Departure time schedule

Supply modifications

Introduction

SUPPLY-DEMAND


Introduction

• ONE TO MANYONE TO MANY

• ONE TO ONEONE TO ONE

(Vehicle Routing Problem)

(Shortest Path Problem)

The path design problem for emergency vehicle in road evacuation (during a dangerous event) to take weak users, is faced with two approaches:

PATH / ROUTE DESIGN



I. INTRODUCTION


III. APPLICATION

IV. CONCLUSION


USER NEEDS

•Indicators o link o demand-supplyo evolution indicators •Input needs o key parameters user-definedo integration with other modelso integration with other DB and GIS o graphical network buildero graphical animation of results•ITS functionso signal optimizationo ramp metering o variable message signs

MODELLING FEATURES

•Modelling traffic assignmento static o dynamic (macro, meso, micro)

•Cost function specification o fixed o different given alternatives o user defined•Demand-supply interactiono path-choice (pre-trip, en-route, stochastic, deterministic)o assignment (network loading, user equilibrium, system optimum, within day dynamic)

DSS

Decision Support System (DSS)

SUPPLY-DEMAND


DSS L1 L2 L3 L4 DS1 DS2 DS3 DS4 DS5 E1 E2

Emme/2 X X X -- X X X X -- -- --

TransCAD X X X -- -- -- X X -- -- --

MT Model X X X -- -- X -- X -- -- --

VISUM X X X -- X X X X X X --

OmniTRANS X X X X -- -- -- -- -- -- --

Cube Avenue X X X X -- -- -- -- X X --

DYNASMART X X X X X X X X X X --

TransModeler X X X X X X X X X -- --

DynaMIT X X -- X -- -- -- X -- -- --

DSS SICURO X X -- X -- -- X X -- X X

AIMSUN X X X X X X X X X X --

INTEGRATION X X X -- X X X X X X X

MITSIMLab X X -- -- X X X X X -- --

PARAMICS X X X X -- -- -- -- -- -- --

VISSIM X X X X X X X X X -- --


SUPPLY-DEMAND: user needs indicators

LINK INDICATORS: L1=flow, L2=average speed, L3=flow/capacity, L4=queue length; DEMAND-SUPPLY INTERACTION INDICATORS: DS1=average travel distance per vehicle, DS2=total travel distance, DS3=average travel time per vehicle, DS4=total travel time, DS5=average speed on the network; SYSTEM EVOLUTION INDICATORS: E1=number of vehicles on the network, E2=number of vehicles that reach each destination; --=not-available or not-stated



Emme/2 X X X -- X X X X -- -- --

TransCAD X X X -- -- -- X X -- -- --

MT Model X X X -- -- X -- X -- -- --


OmniTRANS X X X X -- -- -- -- -- -- --




DynaMIT X X -- X -- -- -- X -- -- --





PARAMICS X X X X -- -- -- -- -- -- --






DSS 1 2 3 4 5

Emme/2 X X X X X

TransCAD -- -- X -- X

MT Model X -- -- -- X

VISUM X X X X X

OmniTRANS X X X X --

Cube Avenue X X X -- X

DYNASMART X X -- -- X

TransModeler X X X -- X

DynaMIT -- X -- -- --

DSS SICURO X -- -- X X

AIMSUN X X X X X

INTEGRATION

X -- -- -- X

MITSIMLab X -- -- -- X

PARAMICS X X -- X X

VISSIM X X X X X


SUPPLY-DEMAND: user needs input

1=Key parameters can be user-defined, 2=Integration with other models, 3=Integration with other databases and Geographic Information System, 4=Graphical Network Builder, 5=Graphical Animation of Results, --=not-available or not-stated


DSS 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Emme2 -- -- -- -- -- -- -- -- -- -- -- -- -- -- --

TransCAD X -- -- -- -- -- -- -- -- -- -- -- -- -- --

MT Model -- -- -- -- -- -- -- -- -- -- -- -- -- -- --

VISUM -- -- -- -- -- -- -- -- -- -- -- -- -- -- --

OmniTRANS X X X X -- -- -- -- -- -- -- -- -- -- --

Cube Avenue X X -- -- -- -- X -- -- -- -- -- -- -- X

DYNASMART -- X X -- X -- X X -- -- -- -- -- -- X

TransModeler -- -- X -- X -- X -- -- -- X -- -- -- X

DynaMIT X X -- -- X X X X X X -- X -- -- X

DSS SICURO -- -- -- -- -- -- -- -- -- -- X -- -- -- X

AIMSUN X X X X X X X X -- -- -- -- X -- X

INTEGRATION X X X X X -- X X -- X -- X X -- --

MITSIMLab X X X X X -- X X -- -- -- X X -- X

PARAMICS -- X X X X X X X -- -- -- X X -- --

VISSIM -- X X X X X X X -- X X X X -- --

SUPPLY-DEMAND: user needs ITS functions


1=Signal optimization, 2=Co-ordinated traffic signals, 3=Adaptive traffic signals, 4=Priority to public transport vehicles, 5=Ramp metering, 6=Zone access control, 7=Variable message signs, 8=Route guidance, 9=Parking guidance, 10=Public transport information, 11=Support for pedestrians and cyclists, 12=Probe vehicles, 13=Vehicle detectors, 14=Contraflow/lane reversal, 15=Incidents, --=not-available or not-stated


APPROACH: STA=Static Traffic Assignment, meso=mesoscopic Dynamic Traffic Assignment, micro=microscopic Dynamic Traffic Assignment; LINK/NODE: V=cost function specification can be chosen among different given alternatives or it can be user defined, F=cost function specification is fixed, --=not-stated; PATH CHOICE: S=stochastic, D=deterministic, PT=pre-trip, ER=en-route; ASSIGNMENT: NL=network loading, UE=user equilibrium, SO=system optimum, WD=within day dynamic

DSS APPROACHSUPPLY MODEL DEMAND-SUPPLY INTERACTION

LINK NODE PATH CHOICE ASSIGNMENTEmme/2 STA V -- S NL-UE-SOTransCAD STA F -- S, PT NL-UE-SOMT Model STA V -- S-D NL-UEVISUM STA V F S, PT NL-UE-SOOmniTRANS STA V V S-D, PT NL-UECube Avenue meso -- -- S, ER WDDYNASMART meso V V PT-ER WDTransModeler STA

meso-micro V V S, PT UEWD

DynaMIT meso -- -- S, PT WDDSS SICURO meso V -- S-D, PT WDAIMSUN micro F V S-D, PT-ER WDINTEGRATION micro F F D, PT WDMITSIMLab micro V V S, PT-ER WDPARAMICS micro V -- S, PT WDVISSIM micro F F S, PT WD


SUPPLY-DEMAND: modelling features


USER NEEDS MODELLING FEATURES

DSS


simulate the problem for a large number of weak users

ability of the tools to solve theproblem according to its size

PATH/ROUTE DESIGN

generation of optimal sequences of weak users according to several criteria

kind of problem solved by the tools;

possibility to define the link costfunction

travel time estimation for emergency vehicles and network performance

outputs in terms of service and network indicators

low computation time computation time


DSS and Tools: one to one

Kind of problem (B) Tools Software Library

Shortest Path k- Shortest Path

Cost function (C)

Autoroute X X X YES

BGL X X YES

GoodRoute X X X NO

Multi Graph X X NO

Transcad X X X YES

TOOLS NAME

SOFTWARE or LIBRARY

SOLVED PROBLEM

COST FUNCTION DEFINED BY THE USERS


PATH/ROUTE DESIGN


PATH/ROUTE DESIGN

Size of problem (A) Kind of problem (B) Solution Approach Tools Software Library Number

of weak users Number

of vehicles VRP

VRP TW

Other Cost function

(C) Outputs

(D) Exact Heuristic

ArcLogistics X U U X X Yes ND ND ND

Jcell X X ND ND G

JDI X U U X X Yes Yes NSH

JOpt.ASP X U U X X TSP Yes Yes MA

JOpt.J2EE X U U X X TSP Yes Yes MA JOpt.NET X U U X X TSP CVRTW Yes Yes MA JOpt.SDK X U U X X TSP Yes Yes MA

... ... ... ... ... ... ... ... ... ... ... ...

Symphony X X X TSP Yes ND B&C

Transcad X U U X X Yes Yes G

TruckStops X 100 > 5 X Yes ND B&B

WInRoute X X ND ND ND ND

DSS and Tools: one to many

TOOLS NAME

SOFTWARE or LIBRARY

PROBLEM SIZE

SOLVED PROBLEM

COST FUNCTION DEFINED BY THE USERS

ALGORITHM

OUTPUT TYPEU: UnlimitedTSP: Travelling Salesman ProblemCVRTW: Capacitated Vehicle Routing Problem with Time WindowsND: Non-definedB&B: Branch & Bound; B&C: Branch & CutG: Genetic; MA: Memetic AlgorithmTS: Tabù Search; NSH: Non-specified heuristic




I. INTRODUCTION


III. APPLICATION

IV. CONCLUSION



Conditions OrdCond



identification


simulation


validation


organization


execution

OPERATIVE STAGE

EVACUATION

PLANNING

Application



Conditions OrdCond


OPERATIVE STAGE

EVACUATION

PLANNING

Application


•ACTIVITY: operative stage supported by DSS

•TARGET: evacuation procedures validation

•PROCEDURE: technical operations (STEPS) reproduction

•REFERENCE: real simulation of evacuation in Melito Porto Salvo (Italy)

•AIM: test DSS effectiveness

CHARACTERISTICS

Application

OPERATIVE STAGE


Procedure

STEP 1

STEP 2

STEP 3

STEP 4

STEP 5

STEP 6

SUPPLY DESIGN

EVACUATION DEMAND

DEMAND-SUPPLY INTERACTION

INDICATORS/ANALYSIS

RISK ASSESSMENT

HISTORICAL DEMAND

time

LOWER BOUND

UPPER BOUND

Application

SUPPLY-DEMAND


STEP 1

STEP 2

STEP 3

STEP 4

STEP 5

STEP 6

10 MIN

SUPPLY DESIGN

EVACUATION DEMAND


INDICATORS/ANALYSIS

RISK ASSESSMENT

HISTORICAL DEMAND

5 MIN

time

LOWER BOUND

UPPER BOUND

5 MIN

10 MIN

Application

ProcedureSUPPLY-DEMAND


STEP 1

STEP 2

STEP 3

STEP 4

STEP 5

STEP 6

15 MIN

SUPPLY DESIGN

EVACUATION DEMAND


INDICATORS/ANALYSIS

RISK ASSESSMENT

HISTORICAL DEMAND

10 MIN

time

LOWER BOUND

UPPER BOUND

5 MIN

10 MIN

5 MIN

5 MIN

15 MIN

10 MIN

Application



STEP 1

STEP 2

STEP 3

STEP 4

STEP 5

STEP 6

SUPPLY DESIGN

EVACUATION DEMAND


INDICATORS/ANALYSIS

RISK ASSESSMENT

HISTORICAL DEMAND

time

LOWER BOUND

UPPER BOUND

5 MIN

10 MIN

5 MIN

5 MIN

1 MIN

1 MIN

16 MIN

11 MIN

16 MIN

11 MIN

Application



STEP 1

STEP 2

STEP 3

STEP 4

STEP 5

STEP 6

SUPPLY DESIGN

EVACUATION DEMAND


INDICATORS/ANALYSIS

RISK ASSESSMENT

HISTORICAL DEMAND

time

LOWER BOUND

UPPER BOUND

5 MIN

10 MIN

5 MIN

5 MIN

1 MIN

1 MIN

5 MIN

10 MIN

26 MIN

16 MIN

26 MIN

16 MIN

26 MIN

16 MIN

Application



STEP 1

STEP 2

STEP 3

STEP 4

STEP 5

STEP 6

SUPPLY DESIGN

EVACUATION DEMAND


INDICATORS/ANALYSIS

RISK ASSESSMENT

HISTORICAL DEMAND

time

LOWER BOUND

UPPER BOUND 66 MIN

46 MIN

5 MIN

10 MIN

5 MIN

5 MIN

1 MIN

1 MIN

5 MIN

10 MIN

46 MIN

26 MIN

10 MIN

20 MIN

Application



STEP 1

STEP 2

STEP 3

STEP 4

STEP 5

STEP 6

SUPPLY DESIGN

EVACUATION DEMAND


INDICATORS/ANALYSIS

RISK ASSESSMENT

HISTORICAL DEMAND

time

LOWER BOUND

UPPER BOUND

5 MIN

10 MIN

5 MIN

5 MIN

1 MIN

1 MIN

5 MIN

10 MIN

10 MIN

20 MIN

66 MIN

36 MIN

10 MIN

20 MIN

Application



EVACUATION DEMAND SUPPLY

ONE TO ONE(Shortest Path)

SHORTEST PATHS between every o/d

ONE TO MANY(Routing)

OPTIMAL ROUTE

Application

ProcedurePATH/ROUTE DESIGN


STEP 1

STEP 1

STEP 2

STEP 3

STEP 4

STEP 6

SUPPLY

SIMULATION

ANALYSIS

EVACUATION DEMAND

time

LOWER BOUND

UPPER BOUND 66

Application



STEP 1

STEP 1

STEP 2

STEP 3

STEP 4

STEP 6

SUPPLY

SIMULATION

ANALYSIS

EVACUATION DEMAND

time

LOWER BOUND

UPPER BOUND

1 MIN

1 MIN

66

Application



STEP 1

STEP 1

STEP 2

STEP 3

STEP 4

STEP 6

SUPPLY

SIMULATION

ANALYSIS

EVACUATION DEMAND

time

LOWER BOUND

UPPER BOUND

1 MIN

1 MIN

1 MIN

10 MIN

66

Application



STEP 1

STEP 1

STEP 2

STEP 3

STEP 4

STEP 6

SUPPLY

SIMULATION

ANALYSIS

EVACUATION DEMAND

time

LOWER BOUND

UPPER BOUND

1 MIN

1 MIN

1 MIN

10 MIN

5 MIN

15 MIN

66

Application



STEP 1

STEP 1

STEP 2

STEP 3

STEP 4

STEP 6

SUPPLY

SIMULATION

ANALYSIS

EVACUATION DEMAND

time

LOWER BOUND

UPPER BOUND

1 MIN

1 MIN

1 MIN

10 MIN

5 MIN

15 MIN

66 MIN

1 MIN

40 MIN

Application

Procedure

8 MIN

PATH/ROUTE DESIGN



I. INTRODUCTION


III. APPLICATION

IV. CONCLUSION


Commercial tools that can be used to simulate evacuation

operations were analyzed

Several user needs that the tools able to support

evacuation were analyzed

A step-by-step procedure to test DSS effectiveness in

emergency conditions were described

Lack of a full DSS to simulate evacuation operations

Conclusion

Decision Support System for evacuation planning: supply, assignment and routing

Giuseppe Musolino, Antonio Polimeni, Antonino Vitetta,

[email protected], [email protected], [email protected]

UNIVERSITÀ DEGLI STUDI MEDITERRANEA DI REGGIO CALABRIADipartimento di Informatica, Matematica, Elettronica e Trasporti

Facoltà di Ingegneria

Sesta Conferenza Nazionale in Informatica e Pianificazione Urbana e TerritorialeSesta Conferenza Nazionale in Informatica e Pianificazione Urbana e Territoriale13 - 15 September 2010, Potenza - Italy13 - 15 September 2010, Potenza - Italy





path choice

PROBLEM

Introduction


path choice

driver

PROBLEM DECISION MAKER

Introduction


path choice

driver




for external authority

Introduction

decision support systems for evacuation planning: supply, assignment and routing, di giuseppe...

Documents

dangerous event t

time t

supply demand dss

targetminimize t p t

introduction dangerous

dangerous event evolution

forecasted t

effects t