A multiclass simulation-based dynamic traffic assignment model for mixed traffic flow of connected and autonomous vehicles and human-driven vehicles

Journal Article (2023)
Author(s)

B.B.M. Bamdad Mehrabani (Université Catholique de Louvain)

Jakob Erdmann (Deutsches Zentrum für Luft- und Raumfahrt (DLR))

Luca Sgambi (Université Catholique de Louvain)

Seyedehsan Seyedabrishami (University of Sydney)

M. Snelder (TU Delft - Transport and Planning, TNO)

Transport and Planning
Copyright
© 2023 B.B.M. Bamdad Mehrabani, Jakob Erdmann, Luca Sgambi, Seyedehsan Seyedabrishami, M. Snelder
DOI related publication
https://doi.org/10.1080/23249935.2023.2257805
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 B.B.M. Bamdad Mehrabani, Jakob Erdmann, Luca Sgambi, Seyedehsan Seyedabrishami, M. Snelder
Transport and Planning
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Issue number
2
Volume number
21
Pages (from-to)
1-32
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Abstract

Connected and Autonomous Vehicles (CAVs) may exhibit different driving and route choice behaviours compared to Human-Driven Vehicles (HDVs), which can result in a mixed traffic flow with multiple classes of route choice behaviour. Therefore, it is necessary to solve the Multiclass Traffic Assignment Problem (TAP) for mixed traffic flow. However, most existing studies have relied on analytical solutions. Furthermore, simulation-based methods have not fully considered all of CAVs’ potential capabilities. This study presents an open-source solution framework for the multiclass simulation-based TAP in mixed traffic of CAVs and HDVs. The proposed model assumes that CAVs follow system optimal with rerouting capabilities, while HDVs follow user equilibrium. It also considers the impact of CAVs on road capacity at both micro and meso scales. The proposed model is demonstrated through three case studies. This study provides a valuable tool that can consider several assumptions for better understanding the impact of CAVs on mixed traffic flow.

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