A reproducible pipeline for activity-based travel demand generation in England
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.
Authors
- Hussein Mahfouz (ORCID: https://orcid.org/0000-0002-6043-8616)
- Tao Cheng (ORCID: https://orcid.org/0000-0002-5503-9813)
- Sam F. Greenbury (ORCID: https://orcid.org/0000-0003-4452-2006)
- Bowen Zhang (ORCID: https://orcid.org/0000-0002-3026-1493)
- Stuart Lynn (ORCID: https://orcid.org/0000-0003-1227-2719)
Institutions
- University of Leeds (GB)
- The Alan Turing Institute (GB)
- University College London (GB)
Publication Details
- Journal
- Environment and Planning B Urban Analytics and City Science
- Published
- 2025-09-19
- DOI
- https://doi.org/10.1177/23998083251379620
- Primary Topic
- Urban Transport and Accessibility
- Type
- article
- Field-Weighted Citation Impact
- 0.00