presented to time of day subcommittee may 9, 2011 time of day modeling in fsutms
TRANSCRIPT
Presented to Presented to
Time of Day Subcommittee Time of Day Subcommittee
May 9, 2011May 9, 2011
Time of Day Modeling in Time of Day Modeling in FSUTMSFSUTMS
Time of Day Modeling in FSUTMS
BackgroundBackground
► Currently not a part of FSUTMSCurrently not a part of FSUTMS► Identified as a top priority by Model Task Force Identified as a top priority by Model Task Force
in 2008in 2008► Essential in supporting MTF’s high-priority Essential in supporting MTF’s high-priority
activitiesactivitiesNew StartsNew StartsAir Quality AnalysisAir Quality AnalysisPricing studiesPricing studiesTransit ForecastingTransit Forecasting
2
Time of Day Modeling in FSUTMS
BackgroundBackground
► TOD research project divided into two phasesTOD research project divided into two phasesPhase I: Fixed TOD Factoring and Procedure Phase I: Fixed TOD Factoring and Procedure
DevelopmentDevelopmentPhase II: Development and implementation of Phase II: Development and implementation of
TOD peak spreading model.TOD peak spreading model.
3
Time of Day Modeling in FSUTMS
Why Consider TOD Modeling in FSUTMSWhy Consider TOD Modeling in FSUTMS
► Characteristics of travel Characteristics of travel vary by time of day and vary by time of day and locationlocation
► Knowledge of temporal Knowledge of temporal distribution of travel distribution of travel demand provides useful demand provides useful insights for planning and insights for planning and operationsoperations
► Daily models not Daily models not sensitive to time sensitive to time dependent travel dependent travel behaviorbehavior
Source: FHWA, Our Nation’s Highway, 2010
4
Time of Day Modeling in FSUTMS
Why Consider TOD Modeling in FSUTMSWhy Consider TOD Modeling in FSUTMS
► Required by FTA for New Starts Alternatives Required by FTA for New Starts Alternatives AnalysisAnalysis
► Required by FHWA and EPA for Vehicle Required by FHWA and EPA for Vehicle Emissions AnalysisEmissions Analysis
► Required for analysis of transportation policies Required for analysis of transportation policies that have temporal sensitivity (e.g. Managed that have temporal sensitivity (e.g. Managed Lanes, Pricing, Alternative Work Schedules)Lanes, Pricing, Alternative Work Schedules)
5
Time of Day Modeling in FSUTMS
Static Time of Day ModelStatic Time of Day Model
► Fixed TOD factors derived from local travel Fixed TOD factors derived from local travel patterns. (patterns. (The common practiceThe common practice))Relatively easy to implementRelatively easy to implementAssumes travel patterns will remain the same in Assumes travel patterns will remain the same in
the future the future Not sensitive to LOS changesNot sensitive to LOS changes
► Adequate for regions where congestion growth Adequate for regions where congestion growth is limited or negligibleis limited or negligible
► Essential for transit modeling to reflect Essential for transit modeling to reflect changes in transit service and fares from peak changes in transit service and fares from peak to off-peak periodsto off-peak periods
6
Time of Day Modeling in FSUTMS
Time of Day Choice Feedback ModelTime of Day Choice Feedback Model
► Dynamic model, predicts shifts in time of travelDynamic model, predicts shifts in time of travel► Can model “peak spreading” over time.Can model “peak spreading” over time.► Sensitive to trip purposes and changes in LOS Sensitive to trip purposes and changes in LOS
on specific routes. on specific routes. ► Useful in regions where peak period is greater Useful in regions where peak period is greater
than two hours and growing.than two hours and growing.
7
Time of Day Modeling in FSUTMS
Approach for FSUTMS TOD ModelingApproach for FSUTMS TOD Modeling
► Implement TOD model after Trip GenerationImplement TOD model after Trip Generation► Static TOD model for base year scenarioStatic TOD model for base year scenario
Fixed TOD factors developed from observed local data. Fixed TOD factors developed from observed local data.
► TOD Choice feedback model for future year TOD Choice feedback model for future year scenariosscenarios Incremental logit model formIncremental logit model form Feedback of TOD choice to Trip DistributionFeedback of TOD choice to Trip Distribution Fixed TOD factors for initial TOD stratificationFixed TOD factors for initial TOD stratification
► TOD periods of 1 hour to several hours TOD periods of 1 hour to several hours durationduration
8
Time of Day Modeling in FSUTMS
The Existing Model StructureThe Existing Model Structure
Trip Generation (Daily)
Trip Distribution(Daily)
Mode Choice(Daily)
Trip Assignment: (Highway – Daily; Transit – PK/OP)
Any Scenario Year
9
Time of Day Modeling in FSUTMS
Apply TOD Choice (Peak Spreading) Model by Trip Purpose
Trip Generation
Factor P’s & A’s by Fixed TOD Factors
Trip Distribution by TOD
Mode Choice by TOD
Highway Assignment by TOD
Skim Base Year LOS by TOD
Trip Generation
Factor P’s & A’s by Fixed TOD Factors
Trip Distribution by TOD
Mode Choice by TOD
Assignment by TOD
Skim Future Year LOS by TOD
Base Year Future Year
Convergence?NoYes
END
Transit Assignment
Transit Assignment
The Revised Model Structure (Draft)The Revised Model Structure (Draft)
10
Time of Day Modeling in FSUTMS
TOD Choice (Peak Spreading) ModelTOD Choice (Peak Spreading) Model
► Incremental logit model
► Driven by difference in travel impedance
► Apply in future year where significant congestion growth is expected
► Requires all TOD periods to be modeled explicitly► Model applied for each trip purpose independently► Creates adjusted trip tables for iterative feedback through trip
distribution, mode choice and assignment
11
Time of Day Modeling in FSUTMS
ConclusionConclusion
► TOD choice modeling in FSUTMS will provide:TOD choice modeling in FSUTMS will provide:Improved understanding of temporal travel behaviorImproved understanding of temporal travel behaviorImproved forecast of highway LOS by TODImproved forecast of highway LOS by TODImproved estimation of highway speeds for Improved estimation of highway speeds for
modeling transit, resulting in improved transit modeling transit, resulting in improved transit forecastsforecasts
► Logical stepping stone to implementation in an Logical stepping stone to implementation in an activity-based FSUTMSactivity-based FSUTMSTOD choice more robust when implemented with TOD choice more robust when implemented with
additional explanatory variables, such as family additional explanatory variables, such as family structure, joint travel, income and mode constraintsstructure, joint travel, income and mode constraints
12
Time of Day Modeling in FSUTMS
Questions?Questions?
Thank You!Thank You!
13