Autonomous Driving Strategies at Intersections: Scenarios, State-of-the-Art, and Future Outlooks

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.

Automated summary

This paper provides a brief overview of state-of-the-art autonomous driving strategies at intersections, including common intersection scenarios, simulation platforms, and datasets. By reviewing previous studies, characteristics of existing autonomous driving strategies have been summarized and classified into categories. Finally, problems with current autonomous driving strategies are identified, and valuable research outlooks are proposed.