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

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Suggested Citation:"T57054 txt_012.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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12 INNOVATIONS IN TRAVEL DEMAND MODELING, VOLUME 2 TABLE 1 Comparison of Design Features of Various Activity- Based Model Systems Model Design Portland San Francisco New York Columbus Feature METRO SFCTA NYMTC MORPC Controls and no. of categories for 4 household sizes, 4 household sizes, 5 household sizes, 5 household sizes, population synthesis 4 incomes, and 3 no. of workers, 4 no. of workers, 4 no. of workers, 4 ages 4 incomes, and and 4 incomes and 4 incomes 3 ages “Usual” work and school locations at top level? No–yes Yes No No Number of out- of- home activity purposes 3 / 8 3 4 7 Number of in- home activity purposes 3 1 1 1 Day pattern type linked explicitly across HH? No No No Yes, sequential Joint activities linked explicitly across HH? No No No Yes Allocated HH activities allocated explicitly? No No No Yes “Escort” trips linked explicitly across HH? No No No No Level where stop purpose and frequency modeled Person- day Person- day Tour Tour Network zones used (approx.) 1,250 1,900 6,000 2,000 Smaller spatial units used below zones? No–yes, 20K blocks No No No Mode and destination model estimation Simultaneous Sequential Sequential Sequential Network time periods per day 5 5 4 5 Modeled time periods 5 per day 5 per day 4 per day 1 hour Use of time window duration in scheduling? No No No Yes Tour time of day relative to mode Above both Above both Between them Between them and destination Departure time modeled separately at trip level? No No (may be added) No No Accessibility measures in upper level models Person- specific Jobs reached by Destination choice Destination choice mode–destination zone–mode–time logsums by zone– logsums by zone– logsums band mode–segment mode–segment a These model systems are currently in the design phase. HH = households. behaviorally and because Census Transportation Planning Package Table 1-75 provides a useful three- way joint distribution of household size, number of workers, and income for 2000. The Portland Metro and San Francisco County Transportation Authority models have also used age of head of household as a control variable, and the Atlanta Regional Commis- sion, the Bay Area (California), and Denver are all considering using age or age- related variables as well (e.g., presence of children, senior citizens, or both). The sample- generation software created for Atlanta has a flexible system for designating and combining control variables, as well as facilities for testing how well the synthetic population matches other variables for which there has not been explicit control. An important test will be how well the age distribution is matched when age is not one of the explicit control variables. “USUAL” WORK AND SCHOOL LOCATIONS MODELED AT TOP LEVEL The research community recognizes that the choices of where to work and go to school are longer- term decisions that are not adjusted day to day, similar to the choice of residence (which is implicitly modeled in the synthetic sample). In most models, and all the more recent ones, the “usual” work and school places are modeled at the top level, meaning that these are predicted before any choices specific to the travel day are predicted. The home location is typically one of the alternatives in the choice set for people whose main workplace is at home or who are homeschooled. Certain types of individuals, such as construction workers or traveling salespeople, may not have a usual workplace. And this model formulation requires that data be collected on each worker’s most fre- quent work location, even if that person does not visit

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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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