Autonomous Driving Strategies at Intersections

Scenarios, State-of-the-Art, and Future Outlooks

Conference Paper (2021)
Author(s)

Lianzhen Wei (Beijing Institute of Technology)

Zirui Li (Transport and Planning, Beijing Institute of Technology)

Jianwei Gong (Beijing Institute of Technology)

Gong Cheng (Beijing Institute of Technology)

Jiachen Li (University of California)

Transport and Planning
DOI related publication
https://doi.org/10.1109/ITSC48978.2021.9564518 Final published version
More Info
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Publication Year
2021
Language
English
Transport and Planning
Article number
9564518
Pages (from-to)
44-51
ISBN (print)
978-1-7281-9143-0
ISBN (electronic)
978-1-7281-9142-3
Event
2021 IEEE International Intelligent Transportation Systems Conference, ITSC 2021 (2021-09-19 - 2021-09-22), Indianapolis, United States
Downloads counter
243

Abstract

Due to the complex and dynamic character of intersection scenarios, the autonomous driving strategy at intersections has been a difficult problem and a hot point in the research of intelligent transportation systems in recent years. This paper gives a brief summary of state-of-the-art autonomous driving strategies at intersections. Firstly, we enumerate and analyze common types of intersection scenarios, corresponding simulation platforms, as well as related datasets. Secondly, by reviewing previous studies, we have summarized characteristics of existing autonomous driving strategies and classified them into several categories. Finally, we point out problems of the existing autonomous driving strategies and put forward several valuable research outlooks.