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Innovations in Travel Demand Modeling, Volume 2: Papers (2008)

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Suggested Citation:"T57054 txt_161.pdf." National Academies of Sciences, Engineering, and Medicine. 2008. Innovations in Travel Demand Modeling, Volume 2: Papers. Washington, DC: The National Academies Press. doi: 10.17226/13678.
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161 Modeling of Peak Hour Spreading with a Disaggregate Tour- Based Model Rebekah S. Anderson, Ohio Department of Transportation Robert M. Donnelly, PB Consult Over the last decade in all metropolitan areas, growingpeak period congestion has been accompanied byincreased demand from the peak hour into the shoul- der hours of the peak period. Conventional forecasting models generally adopt static diurnal factors and do not model time- of- day (TOD) choice, and are generally not well formulated to extend their capabilities to model travel by hour of day as a function of level of service and other factors, including simula- tion of peak hour spreading. As a disaggregate tour- based model, the Mid- Ohio Regional Planning Commission (MORPC) travel forecasting system fully incorporates a TOD choice model for a 19-h average weekday. Because the TOD model is sensitive to travel times, peak hour spreading as the consequence of increased levels of peak period congestion should be evident in the model’s application. This paper explores this aspect of the MORPC tour- based model in appli- cation, comparing observed traffic data with the simulated hourly demand results from a series of tests of the model. (Ref- erences 1–11 refer to TOD modeling and the Columbus tour- based model.) MORPC TIME- OF- DAY MODEL In October 2001, MORPC contracted PB Consult to develop a set of regional travel forecasting models. It developed a disaggregate tour- based model applied with the microsimulation of each individual household, per- son, or tour, mostly using Monte Carlo realization of each possibility estimated by the models, with a random number series to determine which possibility is chosen for that record. The set consists of nine models that are linked and applied sequentially. They are: population synthesis, auto ownership, daily activity pattern (mandatory tour generation), joint tour generation, individual non- mandatory tour generation, tour destination choice, TOD choice, tour mode choice, and stops and trip mode choice. The tour destination, TOD, and tour mode choices’ models are logit based and applied together. The “Log- Sum” composite impedance measure from the mode choice model is available to the other choice models, making them sensitive to changes in travel times due to congestion. The TOD model is based on the “time win- dows” concept, accounting for use of a person’s time budget over the day (16 h available per person). These models are applied at the tour level, yielding the primary destination, TOD, and mode choice for the entire tour, and consider both the outbound and inbound portions. The TOD model is a hybrid discrete choice departure time and duration model, with a temporal resolution of 1 h for the modeled period between 5:00 a.m. and 11:00 p.m. All tour departures before 5:00 a.m. were shifted to the 5:00 a.m. hour, and all tour arrivals after 11:00 p.m. were shifted to 11:00 p.m. The TOD model is applied sequentially among tours, with mandatory (work, uni- versity, and school) tours scheduled first. The model determines the departure time of each tour and the dura- tion of the activity associated with the tour. Therefore, the 190 departure and arrival time combinations can be applied with relatively few variables. As a result of this time- windows constrained formulation, the timing of the departure and arrival times on both legs of the tour

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TRB Conference Proceedings 42, Innovations in Travel Demand Modeling, Volume 2: Papers includes the papers that were presented at a May 21-23, 2006, conference that examined advances in travel demand modeling, explored the opportunities and the challenges associated with the implementation of advanced travel models, and reviewed the skills and training necessary to apply new modeling techniques. TRB Conference Proceedings 42, Innovations in Travel Demand Modeling, Volume 1: Session Summaries is available online.

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