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Utility-based agent model for intermodal behaviors: a case study for urban toll in Lille

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Abstract

To reduce the congestion and pollution in urban cities, the political authorities encourage the modal shift from private cars in favor of sustainable trip behaviors such as intermodality (through combinations of private cars and public transport). Coercive decisions such as urban tolls are also an increasingly investigated solution. To avoid the cost of toll taxes, agents thus select intermodal transportation modes (private cars and public transport) by parking their vehicles in park-and-ride (PR) facilities at the entrance to the area toll. This paper proposes a methodology for an agent-based model (ABM), particularly a model called utility-based agent, to reproduce intermodal trip behaviors in a city and to assess the impact of an urban toll. In this context, we focus on multinomial logit models, coupled with the agent-and-activity simulation tool MATSim, is used to determine the modal choice for each agent. Based on open data (for European Metropolis of Lille, MEL), the simulation shows that \(\varvec{20}\) € (\(\varvec{21.75}\) $) of toll tax is sufficient to reduce by \(\varvec{20}\%\) the use of private vehicles.

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All data generated or analysed during this study are included in this published article.

Notes

  1. By definition, the multimodality refers to the availability of several possible transportation modes (alternatives) for a given trip, while the intermodality is characterized as a combination of these possibilities during the same trip [11].

  2. French acronym for Métropole Européenne de Lille.

  3. https://www.openstreetmap.org/about

  4. https://gtfs.org/

  5. https://www.insee.fr/fr/statistiques/3698339#consulter

  6. https://www.data.gouv.fr/fr/datasets/taux-de-motorisation-des-menages/

  7. https://opendata.lillemetropole.fr/explore/dataset/enquete-deplacement-2016/information /?location=10,50.65641,3.03338&basemap=jawg.streets

  8. \(\theta _{parkingSearchPenalty}\) allows to take into account the effects of the search for a parking space for the vehicle.

  9. \(\theta _{accessEgressWalkTime}\) captures the influence of walking time to go to the car and to the final destination.

  10. https://www.prefectures-regions.gouv.fr/hauts-de-france/Region-et-institutions/Portrait-de-la-region/Chiffres-cles/Chiffres-cles-de-la-region-Hauts-de-France

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Acknowledgements

We would like to thank the anonymous reviewers for many valuable comments improving our paper.

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The authors (A-O. D., G. L., A. D. and R. M.) contributed equally to this work.

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Correspondence to Guillaume Lozenguez.

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Diallo, A.O., Lozenguez, G., Doniec, A. et al. Utility-based agent model for intermodal behaviors: a case study for urban toll in Lille. Appl Intell 55, 282 (2025). https://doi.org/10.1007/s10489-024-05869-1

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