Cover Image

Not for Sale



View/Hide Left Panel
Click for next page ( 88


The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 87
76 I N N O VAT I O N S I N T R AV E L D E M A N D M O D E L I N G , V O L U M E 2 CONCLUSIONS AND DISCUSSION Models of Activity-Travel Choice Dynamics. Transporta- tion, Vol. 32, pp. 321340. This paper has reported progress and plans in the devel- Arentze, T. A., and H. J. P. Timmermans. 2006. Multi-Agent opment, testing, and implementation of a multiagent Models of Spatial Cognition, Learning, and Complex activity-based model of (re)scheduling behavior called Choice Behavior in Urban Environments. In Complex Arti- Aurora. An operational and extended version of this ficial Environments (J. Portugal, ed.), Spring Verlag, Berlin, model will be developed specifically for Flanders, Bel- pp. 181200. gium, under the acronym Feathers. Data collection for Bellemans, T., B. Kochan, D. Janssens, and G. Wets. 2005. estimating the various components is on its way. Plans Collecting Activity-Travel Diary Data by Means of a GPS- are to report the first empirical results in the near future. Enabled Personal Digital Assistant. Colloquium Vervoers- Unlike the activity-based models mentioned in the planologisch Speurwerk, Vol. 32, Nov. 2425, pp. paper's introduction, this model has the potential value to 21112131. simulate short-term dynamics. As such, it should be pri- Bhat, C. R., J. Y. Guo, S. Srinivasan, and A. Sivakumar. 2004. A marily relevant to simulate dynamics in day-to-day traffic Comprehensive Micro-Simulator for Daily Activity-Travel flows and their environmental impacts. Its development Patterns. Proc., Conference on Progress in Activity-Based into a model that can be used for longer-term assessment Models (CD-ROM), Maastricht, Netherlands, May 2831. would require additional components. Such projects are on Han, Q., and H. J. P. Timmermans. 2006. Interactive Learning their way as well but not part of Feathers at this stage. The in Transportation Networks Under Conditions of with future will then tell whether the greater complexity implied Uncertainty, Bounded Rationality, And Strategic Choice by these and other extensions will be feasible, not only Behavior: Quantal Response Model. In Transportation from a modeling and computational standpoint but also in Research Record: Journal of the Transportation Research relation to acceptance by practitioners and policy makers. Board, No. 1964, Transportation Research Board of the National Academies, Washington, D.C., pp. 2734. Joh, C.-H., T. A. Arentze, and J. J. P. Timmermans. 2003. ACKNOWLEDGMENT Understanding Activity Scheduling and Rescheduling Behaviour: Theory and Numerical Simulation. In Model- The research program presented in this paper was sup- ling Geographical Systems (B. N. Boots, A. Okabe, and R. ported by the Institute for the Promotion of Innovation Thomas, eds.), Kluwer Academic Publishers, Dordrecht, by Science and Technology in Flanders. Netherlands, pp. 7395. Joh, C.-H., T. A. Arentze, and H. J. P. Timmermans. 2004. Activity-Travel Rescheduling Decisions: Empirical Estima- REFERENCES tion of the Aurora Model. In Transportation Research Record: Journal of the Transportation Research Board, No. Arentze, T. A., C. Pelizaro, and H. J. P. Timmermans. 2005. 1898, Transportation Research Board of the National Acad- Implementation of a Model of Dynamic Activity-Travel emies, Washington, D.C., pp. 1018. Rescheduling Decisions: An Agent-Based Micro-Simula- Kochan, B., T. Bellemans, D. Janssens, and G. Wets. 2006. tion Framework. Proc., Computers in Urban Planning and Dynamic Activity-Travel Diary Data Collection: Using a Urban Management Conference (CD-ROM), London. GPS-Enabled Personal Digital Assistant. In Conference Arentze, T. A., and H. J. P. Timmermans. 2000. Albatross: A Proceedings 42: Innovations in Travel Modeling Confer- Learning-Based Transportation Oriented Simulation Sys- ence, Transportation Research Board of the National Acad- tem. European Institute of Retailing and Services Studies, emies, Washington, D.C., pp. 9497. Eindhoven, Netherlands. Pendyala, R. M., R. Kitamura, A. Kikuchi, T. Yamamoto, and Arentze, T. A., and H. J. P. Timmermans. 2004. A Theoretical S. Fujii. 2005. Florida Activity Mobility Simulator: Framework for Modeling Activity-Travel Scheduling Deci- Overview and Preliminary Validation Results. In Trans- sions in Non-Stationary Environments Under Conditions portation Research Record: Journal of the Transportation of Uncertainty and Learning. Proc., International Confer- Research Board, No. 1921, Transportation Research Board ence on Activity-Based Analysis (CD-ROM), Maastricht, of the National Academies, Washington, D.C., pp. 123130. Netherlands. Sun, Z., T. A. Arentze, and H. J. P. Timmermans. 2005. Mod- Arentze, T. A., and H. J. P. Timmermans. 2005a. Albatross 2: eling the Impact of Travel Information on Activity-Travel A Learning-Based Transportation Oriented Simulation Sys- Rescheduling Decisions Under Conditions of Travel Time tem. European Institute of Retailing and Services Studies. Uncertainty. In Transportation Research Record: Journal Eindhoven, Netherlands. of the Transportation Research Board, No. 1926, Trans- Arentze, T. A., and H. J. P. Timmermans. 2005b. Representing portation Research Board of the National Academies, Mental Maps and Cognitive Learning in Micro-Simulation Washington, D.C., pp. 7987.