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- W2159616827 abstract "Activity-based travel demand models generate activity-travel schedules for individual travellers or homogeneous groups of travellers. Travel demand is derived from these activitytravel schedules by the fact that most activities take place at different locations and people need to travel between these. The agent-based micro-simulation toolkit MATSim implements an activity-based approach to travel demand generation for large samples. A co-evolutionary learning process assigns every agent with an all-day activity-travel schedule. The schedule holds information on which activities the agent performs, in which order, where and for how long, and which travel modes the agent uses between the activities including corresponding routes. This paper proposes a new MATSim utility function for the performance of activities, based on an asymmetric S-shaped curve with an inflection point. The new utility function can cope with a flexible number of activities in a schedule as it formulates an optimal activity duration by its functional form. It has become necessary since a new algorithm was added to MATSim’s replanning step that comprehensively optimizes schedules, including their activity chain sequences. This paper further presents a methodology to empirically estimate the parameters of the new utility function through an enhanced Multinomial Logit (MNL) model. A similarity attribute in the systematic part of the utility function allows to overcome the MNL model’s IIA property. First estimates of a limited set of parameters are presented although the results are still preliminary and ambiguous." @default.
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- W2159616827 date "2009-10-01" @default.
- W2159616827 modified "2023-09-22" @default.
- W2159616827 title "Generating Comprehensive All-day Schedules: Expanding Activity-based Travel Demand Modelling" @default.
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- W2159616827 doi "https://doi.org/10.3929/ethz-a-005899597" @default.
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