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

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Suggested Citation:"T57054 txt_005.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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TAXONOMY OF TRANSPORTATION SYSTEM MODELING APPROACHES The existing approaches in transportation system model- ing tend to sit along a diagonal from upper left to lower right in Figure 1; the recent increasing use of process sim- ulation has arisen in conjunction with a swing to greater use of explicit representation of individual agents. Clearly, the ability to handle systems with large numbers of interacting agents (with the advent of increasing com- puting capabilities) has led to more attempts at explicit representation of the behavioral processes involved at the individual level. It appears that more and more analysts— at least implicitly— are taking the view that enough is known about the nature of individual agents’ behavior (possibly in part because these analysts are such agents themselves in the real world and thus have insight gained by experience) to result in modeling systems that provide more accurate, or at least more faithful, repre- sentations of reality. A range of other combinations off the diagonal are available in transportation system and related modeling. Some of these other combinations are now being explored so as to gain some of the available advantages. Examples of these other combinations are 1. Cambridge Solutions modeling system (Caruso 2005): This system uses a bid- choice framework to allo- cate individual households to residential locations within a particular transportation analysis zone consistent with the results of a combined land use transport model that is equilibrium based (that uses the MEPLAN framework) to refine the search for the equilibrium solution and to explore further the aspects of this equilibrium solution at the level of individual households. A detailed resolution is provided without giving up desirable equilibrium properties. 2. Calgary commercial vehicle movement model (Stef - an et al. 2005): This model uses a tour- based microsimu- lation framework with Monte Carlo simulation in which logit choice models provide the sampling distributions to simulate the movements of commercial vehicles in the delivery of goods and services. It runs in combination with an equilibrium- based model of household travel demands. Trip tables from multiple runs of the commer- cial movement model are averaged to obtain a trip table of expected movements, and this table is combined with trip tables from the household demands model and then assigned to road networks by means of techniques for stochastic user equilibrium. The resulting congested travel times are fed back to both the household demands model and the commercial vehicle movements model in an iterative process that runs to a convergence. A con- verged system is obtained with a household demands model at equilibrium and a process simulation tour- based microsimulation representation of commercial vehicle movements. 3. Oregon2 integrated land use transport model (Hunt et al. 2001): This model includes a spatially disag- gregated input–output model that is based on equilib- rium to represent industrial and government activity, process- oriented microsimulations of household demo- 5LEVELS OF DISAGGREGATION AND DEGREES OF AGGREGATE CONSTRAINT degree of aggregate constraint aggregate system optimal equilibrium path independence converged stable bounded agent processes entire aggregate population aggregate population segments sample enumeration synthesized agents observed agents chaotic emergent simple mechanical systems Mandelbrot drawings competing biological population simulations SWARM UrbanSIMLand ILUTE BE-microsim Paramics VISSIM UPlan SATURN CONTRAM MEPLAN, TRANUS LOWRY, PECAS-AA multi-class assignment Frank-Wolfe MSAWardrop1stWardrop2nd TOPAZ POLIS supply-demand curves direct demand models Oregon2 PECAS-SD ALBATROSS Furness simulated annealing population synthesis activity-based travel demand Calgary CVM SOLUTIONS be ha vi or a l u ni t FIGURE 1 Comparison of modeling approaches for level of aggregation (i.e., behavioral unit) and degree of aggregate constraint (i.e., aggregate behavioral construct).

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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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