Travel Demand and the FSM
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Transcript of 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