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

The Rachel and Selim Benin School of Engineering and Computer Science

The Hebrew University of Jerusalem

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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	Lecture Notes in Mobility
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	60-72
Number of pages	13
DOIs	https://doi.org/10.1007/978-3-030-80063-5_6
State	Published - 2022

Publication series

Name	Lecture Notes in Mobility

Keywords

Artificial intelligence
Automated vehicles
Control
Traffic flow modeling
Traffic operations

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Automotive Engineering
Transportation
Energy (miscellaneous)

Access to Document

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

Cite this

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 Lecture Notes in Mobility (pp. 60-72). (Lecture Notes in Mobility). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-80063-5_6

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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",

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doi = "10.1007/978-3-030-80063-5_6",

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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 Lecture Notes in Mobility. Lecture Notes in Mobility, Springer Science and Business Media Deutschland GmbH, pp. 60-72. 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.
Lecture Notes in Mobility. Springer Science and Business Media Deutschland GmbH, 2022. p. 60-72 (Lecture Notes in Mobility).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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AU - Abbink, David A.

AU - Hao, Peng

AU - Laval, Jorge

AU - Shalev-Shwartz, Shai

AU - Wu, Cathy

AU - Yang, Terry

AU - Hamdar, Samer

AU - Chen, Danjue

AU - Xie, Yuanchang

AU - Li, Xiaopeng

AU - Haque, Mohaiminul

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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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KW - Automated vehicles

KW - Control

KW - Traffic flow modeling

KW - Traffic operations

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

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Keywords

All Science Journal Classification (ASJC) codes

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