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Department of Geography and Research Unit on Spatial Cognition and Choice ( RUSCC ) UCSB

The recent policy discussions about information technology in transport and traffic demand management have increased the interest in activity-based approaches to the analysis of travel behaviour, in particular in the modelling of household activity scheduling which is at the core of many of the required changes in travel behaviour. The paper is a state-of-the-art review of conceptualizations and models of activity scheduling with special regard to issues raised by the new policy instruments. In the course of the review, the validity of behavioral assumptions are critically examined and several needs for future research identified. Ben-Akiva, M. E., & Bowman, J. L. (1997). Activity based disaggregate travel demand model system with daily activity schedules. Transportation Research. Abstract: They present an integrated activity based discrete choice model system of an individual’s daily activity and travel schedule, intended for use in forecasting urban passenger travel demand. The system is demonstrated using a 1991 Boston travel survey and level of service data. They present an integrated activity based discrete choice model system of an individual’s daily activity and travel schedule, intended for use in forecasting urban passenger travel demand. The system is demonstrated using a 1991 Boston travel survey and level of service data. The model system represents a person’s choice of activities and associated travel as a daily activity pattern overarching a set of tours. The daily activity pattern includes (a) the primary activity of the day, with one alternative being to remain at home for all the day’s activities; (b) the type of tour for the primary activity, including the number, purpose and sequence of activity stops; and (c) the number and purpose of secondary tours. Tour models include the choice of time, destination and mode of travel, and are conditioned by the choice of a daily activity pattern. The choice of daily activity pattern is influenced by the expected maximum utility derived from the available tour alternatives.