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BREAKOUT SESSION Activity-Based Models Theo Arentz, TU Eindhoven, the Netherlands Harry Timmermans, TU Eindhoven, the Netherlands Davy Janssens, Hasselt University, Transportation Research Institute, Belgium Geert Wets, Hasselt University, Transportation Research Institute, Belgium Chandra Bhat, University of Texas at Austin Abdul Pinjari, University of Texas at Austin Naveen Eluru, University of Texas at Austin Ipek Sener, University of Texas at Austin Rachel Copperman, University of Texas at Austin Jessica Guo, University of Wisconsin, Madison Sivaramakrishnan Srinivasan, University of Florida Kay Axhausen, Swiss Federal Institute of Technology Ram Pendyala, University of South Florida Ryuichi Kitamura, Kyoto University Kaira Kikuchi, Kyoto University MODELING SHORT-TERM DYNAMICS IN Several activity-travel demand models, including ACTIVITY-TRAVEL PATTERNS: FROM AURORA nested logit models, are in operation. These models tend TO FEATHERS to focus on activity-travel patterns. Also emerging are more robust, fully operational, activity-based models. Theo Arentz, Harry Timmermans, Davy Janssens, Even with these advancements, there is still more to be and Geert Wets accomplished to enhance activity-based models and pro- mote their use. Areas of possible improvement include Davy Janssens described an ongoing research program in short-term dynamics or rescheduling of travelers' behav- the Netherlands and Belgium on activity-based travel ior, and incorporating uncertainty, learning, and nonsta- models. He discussed the Aurora model and the Fore- tionary environments. Modeling route choice behavior casting Evolutionary Activity-Travel of Households and and the aggregate impact of individual route choice on Their Environmental Repercussions (Feathers) process. activity generation and rescheduling represents another Volume 2 provides a paper on the topic.1 The following area for enhancements. points were covered in his presentation. The Aurora model incorporates some of these ele- ments. Aurora develops an agent-based microsimulation 1 system of dynamic activity-travel choice where agents See Arentze, T., H. Timmermans, D. Janssens, and G. Wets. Modeling Short-Term Dynamics in Activity-Travel Patterns: From represent individuals. These individuals have limited Aurora to Feathers. In Conference Proceedings 42: Innovations in knowledge of their environment. An activity schedule is Travel Demand Modeling, Volume 2: Papers, Transportation generated for each agent for each day and implements the Research Board of the National Academies, Washington, D.C., 2008, schedule in space and time. In making trips, individuals pp. 7177. may experience congestion and adapt their schedules. 27