Artificial Intelligence for Automated Vehicle Control and Traffic Operations: Challenges and Opportunities

David A. Abbink; Peng Hao; Jorge Laval; Shai Shalev-Shwartz; Cathy Wu; Terry Yang; Samer Hamdar; Danjue Chen; Yuanchang Xie; Xiaopeng Li; Mohaiminul Haque

doi:10.1007/978-3-030-80063-5_6

Artificial Intelligence for Automated Vehicle Control and Traffic Operations: Challenges and Opportunities

David A. Abbink, Peng Hao, Jorge Laval, Shai Shalev-Shwartz, Cathy Wu, Terry Yang, Samer Hamdar^*, Danjue Chen, Yuanchang Xie, Xiaopeng Li, Mohaiminul Haque

^*Corresponding author for this work

Human-Robot Interaction

Research output: Chapter in Book/Conference proceedings/Edited volume › Chapter › Scientific › peer-review

2 Citations (Scopus)

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Abstract

This chapter summarizes the presentations of speakers addressing such issues during the Automated Vehicles Symposium 2020 (AVS20) held virtually on July 27–30, 2020. These speakers participated in the break-out session titled “Artificial Intelligence for Automated Vehicle Control and Traffic Operations: Challenges and Opportunities”. The corresponding discussion and recommendations are presented in terms of the lessons learned and the future research directions to be adopted to benefit from AI in order to develop safer and more efficient connected and automated vehicles (CAV). This session was organized by the Transportation Research Board (TRB) Committee on Traffic Flow Theory and Characteristics (ACP50) and the TRB Committee on Artificial Intelligence and Advanced Computing Applications (AED50).

Original language	English
Title of host publication	Road Vehicle Automation 8
Editors	Gereon Meyer, Sven Beiker
Publisher	Springer
Pages	60-72
ISBN (Electronic)	978-3-030-80063-5
ISBN (Print)	978-3-030-79818-5
DOIs	https://doi.org/10.1007/978-3-030-80063-5_6
Publication status	Published - 2022
Event	Automated Vehicles Symposium (AVS) 2020 - Duration: 20 Jul 2020 → 30 Jul 2020

Publication series

Name	Lecture Notes in Mobility
ISSN (Print)	2196-5544
ISSN (Electronic)	2196-5552

Conference

Conference	Automated Vehicles Symposium (AVS) 2020
Period	20/07/20 → 30/07/20

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.

Keywords

Artificial intelligence
Automated vehicles
Control
Traffic flow modeling
Traffic operations

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10.1007/978-3-030-80063-5_6

978-3-030-80063-5_6Final published version, 237 KB

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Abbink, D. A., Hao, P., Laval, J., Shalev-Shwartz, S., Wu, C., Yang, T., Hamdar, S., Chen, D., Xie, Y., Li, X., & Haque, M. (2022). Artificial Intelligence for Automated Vehicle Control and Traffic Operations: Challenges and Opportunities. In G. Meyer, & S. Beiker (Eds.), Road Vehicle Automation 8 (pp. 60-72). (Lecture Notes in Mobility). Springer. https://doi.org/10.1007/978-3-030-80063-5_6

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abstract = "This chapter summarizes the presentations of speakers addressing such issues during the Automated Vehicles Symposium 2020 (AVS20) held virtually on July 27–30, 2020. These speakers participated in the break-out session titled “Artificial Intelligence for Automated Vehicle Control and Traffic Operations: Challenges and Opportunities”. The corresponding discussion and recommendations are presented in terms of the lessons learned and the future research directions to be adopted to benefit from AI in order to develop safer and more efficient connected and automated vehicles (CAV). This session was organized by the Transportation Research Board (TRB) Committee on Traffic Flow Theory and Characteristics (ACP50) and the TRB Committee on Artificial Intelligence and Advanced Computing Applications (AED50).",

keywords = "Artificial intelligence, Automated vehicles, Control, Traffic flow modeling, Traffic operations",

author = "Abbink, {David A.} and Peng Hao and Jorge Laval and Shai Shalev-Shwartz and Cathy Wu and Terry Yang and Samer Hamdar and Danjue Chen and Yuanchang Xie and Xiaopeng Li and Mohaiminul Haque",

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.; Automated Vehicles Symposium (AVS) 2020 ; Conference date: 20-07-2020 Through 30-07-2020",

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Abbink, DA, Hao, P, Laval, J, Shalev-Shwartz, S, Wu, C, Yang, T, Hamdar, S, Chen, D, Xie, Y, Li, X & Haque, M 2022, Artificial Intelligence for Automated Vehicle Control and Traffic Operations: Challenges and Opportunities. in G Meyer & S Beiker (eds), Road Vehicle Automation 8 . Lecture Notes in Mobility, Springer, pp. 60-72, Automated Vehicles Symposium (AVS) 2020, 20/07/20. https://doi.org/10.1007/978-3-030-80063-5_6

Artificial Intelligence for Automated Vehicle Control and Traffic Operations: Challenges and Opportunities. / Abbink, David A.; Hao, Peng; Laval, Jorge et al.
Road Vehicle Automation 8 . ed. / Gereon Meyer; Sven Beiker. Springer, 2022. p. 60-72 (Lecture Notes in Mobility).

Research output: Chapter in Book/Conference proceedings/Edited volume › Chapter › Scientific › peer-review

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AB - This chapter summarizes the presentations of speakers addressing such issues during the Automated Vehicles Symposium 2020 (AVS20) held virtually on July 27–30, 2020. These speakers participated in the break-out session titled “Artificial Intelligence for Automated Vehicle Control and Traffic Operations: Challenges and Opportunities”. The corresponding discussion and recommendations are presented in terms of the lessons learned and the future research directions to be adopted to benefit from AI in order to develop safer and more efficient connected and automated vehicles (CAV). This session was organized by the Transportation Research Board (TRB) Committee on Traffic Flow Theory and Characteristics (ACP50) and the TRB Committee on Artificial Intelligence and Advanced Computing Applications (AED50).

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Artificial Intelligence for Automated Vehicle Control and Traffic Operations: Challenges and Opportunities

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