Wang, ZheyuanCheng, GuoZheng, Jiang Yu2023-04-172023-04-172021-09Wang, Z., Cheng, G., & Zheng, J. Y. (2021). Planning Autonomous Driving with Compact Road Profiles. 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 899–906. https://doi.org/10.1109/ITSC48978.2021.9565033978-1-72819-142-3https://hdl.handle.net/1805/32452Current sensing and control of self-driving vehicles based on full-view recognition is hard to keep a high-frequency with a fast moving vehicle, as increasingly complex computation is employed to cope with the variations of driving environment. This work, however, explores a light-weight sensing-planning framework for autonomous driving. Taking the advantage that a vehicle moves along a smooth path, we only locate several sampling lines in the view to scan the road, vehicles and environments continuously, which generates a fraction of full video data. We have applied semantic segmentation to the streaming road profiles without redundant data computing. In this paper, we plan vehicle path/motion based on this minimum data set that contains essential information for driving. Based on the lane, headway length, and vehicle motion detected from road/motion profiles, a path and speed of ego-vehicle as well as the interaction with surrounding vehicles are computed. This sensing-planning scheme based on spatially sparse yet temporally dense data can ensure a fast response to events, which yields smooth driving in busy traffic flow.en-USPublisher PolicyAutonomous drivingvehicle interactionhuman driversArticle