Travel Demand and the FSM

8/8/2019 Travel Demand and the FSM

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CIVL3420

Assignment 2Travel Demand

Brooke ReynoldsSamuel Carr

Adam Pollock


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Contents

1.0 Introduction

2.0 Part 1 Demand models

2.1 Summary of concerns

3.0 Part 2 Trip Generation

3.1 2-dimensional category analysis results

4.0 Part 3 Network Skimming

4.1 Working for Skim Matrix

4.2 Skim Matrix results

5.0 Part 4 Mode Split

5.1 Working for Binary Logit Model

5.2 Binary Logit Model results

6.0 Part 5 Trip Assignment

6.1 Working and Trip Assignment results

7.0 Conclusion

8.0 Appendix


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1.0 Introduction

This report will be based around how transport modelling is approached in Australia. The report will

be divided into five parts. The first being a summary of the paper, Clothing the Emperor?: Transport

Modelling and Decision Making in Australian Cities, with particular focus on the authors concerns

about the four step modelling approach and the further challenges for transport modelling. Then the

report will focus on the four step modelling approach and will be divided into four parts including

trip generation, network skimming, mode split and trip assignment.


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2.0 Part 1 Demand models

Thepaper,ClothingtheEmperor?:TransportModellingandDecisionMakinginAustralianCities,is

writtenaboutthefourstepmodel (FSM)whichisusedtomodeltransportandhelptransport

plannerstomakedecisions.Itexplainseachofthepartsofthe FSMandalsonotesthe

methodologicalconcernforeachpart.

2.1 Summary of concerns

Thispartofthereportwillfocusonthepapersexplanationofthesemethodologicalconcerns.

Withrespecttothefirststep,tripgeneration,theconcernsaremany.Inthispartofthemodelthe

concernsinclude

y thefactthattravelisgrosslysimplifiedwithoftennodiscriminationbetweenpedestrianandvehicletrips

y trip-chainingbehavioursareignoredduetocomplexityy spatialenvironmentalvariablesarerarelyconsideredy trip zonesareoftenlargewithlittleconsiderationtoshortdistancetravel

Thesecondstepofthemodelistripdistributionwhichisgeneratedfromtheoutputsoftrip

generation.Theconcernsforthispartinclude

y thesingularfocusontraveltimesandthefailuretoconsidersocio-culturalfactorsindestinationchoice

y thereislittleconsiderationofcongestionorotherfeedbackeffectsy theretendstobesignificanterrorsinthepredictionsofgravitymodelsy intra-zonaltripsarepoorlyhandled

Modalassignment,thethirdstep,assignsthetripnumbersderivedfromtheresultsofthetrip

distributionanalysistomode-specific journeys.Themethodologicalconcernsformodalassignment

include

y naivetytomany qualitativefeaturesofpublictransportservicesy exclusionorverylimitedconsiderationofnon-motorisedtripsy insensitivitytotraveloptionssuchascarpooling


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y thefocusoninterchangesandwaitingtimestopredictthemodetravellerswilluseisquestionable

y favourstheuseofprivatemotorvehicles

Thelaststepofthe FSMisroute/trafficassignment.Thisstepassignsthe zonalmodetripstospecific

transportnetworkroutesusingcomplexmathematicaloperations.Theconcernsforroute/traffic

assignmentincludes

y ignoringorplacinglessemphasisonintersectiondelaysy capacitiesareoftenover-simplifiedy intra-zonaltravelisignoredy travelmadeatdifferenttimesofdayisoftenreadjustedintothepeakhoury peakhourtravelisoveremphasised

FurtherchallengesfortransportmodellinginAustraliaincludetheinabilitytoconsidersuchthingsas

inducedtrafficandtravel,landuseandtransportinteractions,socio-economicstatusandtransport,

air quality,noiseandtransportsystems,climatechangeandgreenhousegasemissions,andoil

vulnerabilityandenergysecurityrisk.

Morespecificallythefurtherchallengesfortransportmodellinginclude

y fewtransportmodellersarecapableoffactoringinlongtermaffects,orofadjustingfrequencies

y transportmodelsfailtoconsidertheimpactsoflandusechangesontravely conventionaltransportmodelsmaybiastowardscartravelattheexpenseofpublictransport

y mostmodelsfailtoidentifyanybenefitsofimprovedlandusemixing,publictransport qualityorimprovedconditionsforwalkingandcycling

y muchtransportnetworkplanningstillfailstoconsiderenvironmentalimpactsatthetimefutureroadnetworkscenariosaremodelledandevaluated

y carbonisyettobeincorporatedintoAustralianprojectsorplanassessmentsy mostassessmentsarenaivetotheissueofpetroleumrisky notmuchinvestigationtoassessthelikelytraveldemandpatternsunderhigherfuelprices


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3.0 Part 2 Trip Generation

Thissectionofthereportwillusedatafromthegiventable (refer to figure 1 in Appendix)todevelop

a2-dimensionalcategoryanalysismodelfor HomeBasedWork (HBW)Tripproductions.

3.1 2-dimensional category analysis results

Cars/HH

Workers/HH 0 1 2+ Grand Total

0

CountofHBWTrip/HH 5 5 10

SumofHBWTrip/HH 5 10 15

AverageofHBWTrip/HH 1.00 2.00 1.50

1

CountofHBWTrip/HH 5 5 5 15

SumofHBWTrip/HH 5 9 12 26

AverageofHBWTrip/HH 1.00 1.80 2.40 1.73

2+

CountofHBWTrip/HH 5 5 10

SumofHBWTrip/HH 20 22 42

AverageofHBWTrip/HH 4.00 4.40 4.20

Total Count of HBW Trip/HH 10 15 10 35

Total Sum of HBW Trip/HH 10 39 34 83

Total Average of HBW Trip/HH 1.00 2.60 3.40 2.37


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4.0 Part 3- Network Skimming

Thissectioninvolvesgeneratingtheskimmatrixforthegivendatafromtheassignmentsheet.

Assumptionmadeisthattheintrazonaltravelcostsare50%ofthecosttothenearest zone.

4.1 Working for Skim Matrix

Trip A-11 11-12 11-13 11-14 12-14 13-14 13-C 14-B

Dirn 1 (1) 1.0 1.0 0.6 1.2 0.6 2.1 0.6 1.0

Dirn 2 (-1) 0.9 0.6 0.5 1.3 0.5 1.0 0.6 1.0

Total Result

A-B 1 1 1 1 3.60

A-B 1 1 1 3.20 A-B

A-B 1 1 1 1 4.70

A-C 1 1 1 2.20 A-C

A-C 1 1 1 -1 1 4.20

A-C 1 1 -1 1 3.80

B-A -1 -1 -1 -1 3.00 B-A

B-A -1 -1 -1 3.20

B-A -1 -1 -1 -1 3.40

B-C -1 -1 -1 2.60 B-C

B-C -1 1 -1 1 -1 3.30

B-C 1 -1 1 -1 3.50

C-A -1 -1 -1 2.00 C-A

C-A -1 -1 -1 1 -1 4.70

C-A -1 -1 1 -1 4.90

C-B 1 -1 1 3.70

C-B 1 -1 1 -1 1 3.70

C-B -1 1 -1 1 3.30 C-B


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Trip

Lowest

Trip Equation Result

Intrazonal

Travel

A-A C-A 2.0/2 1.0

B-B B-C 2.6/2 1.3

C-C C-A 2.0/2 1.0

4.2 Skim Matrix results

A B C

A 1.0 3.2 2.2

B 3.0 1.3 2.6

C 2.0 3.3 1.0


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5.0 Part 4 Mode Split

Thispartofthereportinvolvescalibratingabinarylogitmodelusingdatafromthegiventablefrom

assignmentsheet.

5.1 Working for Binary Logit Model

%ModeShare TravelCost

Zone Car Bus Car Bus (Cbus- Ccar) ln(Pcar/Pbus)

1 51 49 20.4 16.6 -3.8 0.04

2 54 46 16.3 12.9 -3.4 0.16

3 61 39 16.9 14.5 -2.4 0.45

4 66 34 17.9 16.4 -1.5 0.66

5 62 38 10.9 8.7 -2.2 0.49

6 67.23 32.77 10.9 9.57 10%

increase

in bus

cost

-1.33 0.72

100

From

graph

ln(Pcar/Pbus) = b(Cbus - Ccar)+bd

b= 0.2727

bd= 1.0854

y=0.272x + 1.085

0.00

0.20

0.40

0.60

0.80

1.00

1.20

-4 -3 -2 -1 0 1

ln(P1/P2)

C2 - C1

Graph for

Binary Logit Model

Series1

Linear (Series1)


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5.2 Binary Logit Model results

%ModeShare TravelCost

Zone Car Bus Car Bus

6 67.23 32.77 10.9 9.57


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6.0 Part 5- Trip assignment

Thissectioninvolvescalculatingthedailytrafficvolumesonthetowncentrerouteandthebypass

routeinthefiguregivenintheassignmentsheet.

6.1 Working and trip assignment results

A) All-or-nothingAssignmentTab=4700vpd

Fastestroutethroughtowncentre

4700vpdthroughtowncentre

B) Incrementalassignment

IncrementalAssignment

Iteration Vb Vtc Cb Ctc Shortest fraction Trips

0 0 0 25 11 TC 0.4 1880

1 0 1880 25 86.2 b 0.2 940

2 940 1880 32.52 86.2 b 0.2 940

3 1880 1880 40.04 86.2 b 0.1 470

4 2350 1880 43.8 86.2 b 0.1 470

Totals 2820 1880

C) Theequilibriumsolution

AtEquilibriumcostofallroutesareequaltherefore

Subinequation (1)


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Sub (2)into (1)


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7.0 Conclusion

Inconclusionthisreportdiscussedthesectionsofthe FSMincludingalookatthemethodological

concernsraisedinthepaper ClothingtheEmperor?:TransportModellingandDecisionMakingin

AustralianCities,andanexampleinvolvingeachofthestepsinthe FSMtripgeneration,trip

distribution (networkskimming),modalassignmentandrouteassignment.The FSMdoeshaveits

flaws,asraisedinthereferredpaper,butitisstillinusetohelpindeterminingtrafficdemandin

Australiaandoverseas.Inthefutureabettermodelmaybedesignedbutitwillmostlikely justbean

extensionofthe FSMoramorepracticalversionofthecurrent FSM.


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8.0 Appendix

ID Wkr/HH Car/HH

HBW

Trip/HH

1 3 2 3

2 4 5 6

3 4 1 4

4 1 0 0

5 0 0 1

6 1 0 1

7 1 5 3

8 0 0 0

9 5 2 6

10 1 1 0

11 2 1 4

12 1 0 013 1 2 3

14 0 0 2

15 1 0 3

16 0 1 5

17 1 1 2

18 1 4 4

19 1 0 1

20 1 2 2

21 0 1 3

22 0 1 2

23 1 1 224 3 1 3

25 1 1 3

26 0 1 0

27 0 1 0

28 0 0 1

29 0 0 1

30 1 1 2

31 5 1 4

32 1 3 0

33 2 1 5

34 2 3 435 2 4 3

Figure1Dataforpart1

Travel Demand and the FSM

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