Artificial Intelligence for Automated Vehicle Control and Traffic Operations
Challenges and Opportunities
David A. Abbink (TU Delft - Mechanical Engineering)
Peng Hao (University of California)
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 Hamdar (The George Washington University)
Danjue Chen (University of Massachusetts Lowell)
Yuanchang Xie (University of Massachusetts Lowell)
Xiaopeng Li (University of South Florida Tampa)
Mohaiminul Haque (The George Washington University)
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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).