A reproducible pipeline for activity-based travel demand generation in England

Hussein Mahfouz, Sam F. Greenbury, Bowen Zhang, Stuart Lynn and Tao Cheng

Environment and Planning B, 2025, vol. 52, issue 9, 2326-2339

Abstract: Agent-based transport models are gaining popularity due to their ability to model features such as heterogenous individual behaviour, household dependencies, and new dynamic modes of travel. Such models require as input disaggregate population datasets with detailed daily activity diaries (activity-based travel demand). While there is extensive literature on activity-based travel demand generation, few open-source tools are available for producing such datasets, and those that do exist are often difficult to adapt to different study areas. In this work, we present an open-source modular pipeline for generating activity-based travel demand for any region in England, producing individuals with household structures and geographically and temporally explicit daily activity plans. The framework includes activity scheduling and location assignment for a synthetic population, as well as self-consistency and validation frameworks to help fine-tune parameters.

Keywords: activity-based travel demand; synthetic populations; open-source; reproducible (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:sae:envirb:v:52:y:2025:i:9:p:2326-2339

DOI: 10.1177/23998083251379620

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