Synthetic population and travel demand for Paris and Île-de-France based on open and publicly available data. (September 2021)

• Record Type: Journal Article
• Authors: Hörl, Sebastian; Balac, Milos
• Is Part Of: Transportation research. Volume 130(2021)
• Publication Date: 2021-09
• Subjects: Open -- Agent-based -- Transport -- Simulation -- Synthetic -- Population -- Paris -- Île-de-France; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2021.103291
• Languages: English
• ISSNs: 0968-090X

Abstract

Abstract: Synthetic populations of travelers and their detailed mobility behavior are an important basis for agent-based transport simulations, which are increasingly used in transport planning and research today. To date, research based on such simulations is rarely replicable as it is based on proprietary data and tools. To foster the discussion and steer research towards reproducible transport simulations, this paper introduces a process for generating a synthetic travel demand with individual households, persons, and their daily activity chains for Paris and its surrounding region Île-de-France — entirely based on open data and open software and replicable by any researcher. The resulting travel demand is published for others to use as a comprehensive data basis for agent-based transport simulations and as a test bed for population and demand synthesis algorithms. Furthermore, it is discussed how implicit correlation structures impact the potential use cases of the synthetic travel demand for simulation and analysis purposes and how the common practice of using population samples for downstream simulations affects the results. Highlights: Open-source pipeline for population and travel demand synthesis for Île-de-France. Reproducible approach that utilizes only open data and software. Modular approach that is transferable to any region in France. Validation and sampling error analysis of the generated synthetic travel demand. Discussion of correlations between variables impacting later practical use.