Artificial Intelligence for Automated Vehicle Control and Traffic Operations

Challenges and Opportunities

Book chapter (2022)

Authors

David Abbink Human-Robot Interaction - Mechanical, Maritime and Materials Engineering
Peng Hao University of California
Mohaiminul Haque The George Washington University
Jorge Laval Georgia Institute of Technology
Shai Shalev-Shwartz The Hebrew University of Jerusalem
Cathy Wu Massachusetts Institute of Technology
Terry Yang University of Utah
Samer Hani Hamdar The George Washington University
Danjue Chen University of Massachusetts Lowell
Yuanchang Xie University of Massachusetts Lowell
Xiaopeng Li University of South Florida Tampa
Research Group
Human-Robot Interaction (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2022 D.A. Abbink, Peng Hao, Jorge Laval, Shai Shalev-Shwartz, Cathy Wu, Terry Yang, Samer Hamdar, Danjue Chen, Yuanchang Xie, Xiaopeng Li, Mohaiminul Haque
DOI: https://doi.org/10.1007/978-3-030-80063-5_6
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Published Date

2022

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Human-Robot Interaction

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).

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