The sequenced activity mobility simulator (SAMS): an integrated approach to modeling transportation, land use and air quality |
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Authors: | Ryuichi Kitamura Eric I. Pas Clarisse V. Lula T. Keith Lawton Paul E. Benson |
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Affiliation: | (1) Kyoto University, Kyoto, Japan;(2) Duke University, Durham, North Carolina, USA;(3) RDC, Inc., San Francisco, California, USA;(4) METRO, Portland, Oregon, USA;(5) California Department of Transportation, Sacramento, California, USA |
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Abstract: | The persistence of environmental problems in urban areas and the prospect of increasing congestion have precipitated a variety of new policies in the USA, with concomitant analytical and modeling requirements for transportation planning. This paper introduces the Sequenced Activity-Mobility Simulator (SAMS), a dynamic and integrated microsimulation forecasting system for transportation, land use and air quality, designed to overcome the deficiencies of conventional four-step travel demand forecasting systems. The proposed SAMS framework represents a departure from many of the conventional paradigms in travel demand forecasting. In particular, it aims at replicating the adaptative dynamics underlying transportation phenomena; explicitly incorporates the time-of-day dimension; represents human behavior based on the satisficing, as opposed to optimizing, principle; and endogenously forecasts socio-demographic, land use, vehicle fleet mix, and other variables that have traditionally been projected externally to be input into the forecasting process. |
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Keywords: | travel demand modeling travel forecasting activity-based travel modeling microsimulation behavioral travel demand modeling |
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