Trajectory Planning for Autonomous Driving Featuring Time-Varying Road Curvature and Adhesion Constraints

doi:10.1109/TITS.2024.3416289

	Trajectory Planning for Autonomous Driving Featuring Time-Varying Road Curvature and Adhesion Constraints
	Gao, Yifan 1; Li, Wei 2; Hu, Yu 2
	2024-06-25
发表期刊	IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
ISSN	1524-9050
页码	18
摘要	Among the various driving situations, there are challenging road conditions where both the texture and curvature are variables over time (e.g., mountainous area). However, it is found that the characteristics of road texture and curvature have been respectively considered in some of the existing studies to determine the vehicle speed for trajectory planning, but the complementary effect of these two factors is still yet to be incorporated. This could lead to unsafe vehicle behaviour. This limitation has led us to develop a trajectory planning method that gives a systematic consideration of road conditions and leverages the complementary effect of road curvature and adhesion on the vehicle speed. It prioritises the trajectory safety through a preview of road constraints (i.e., waypoints, curvature and adhesion) in a look-ahead distance and the real-time computation of the vehicle speed that satisfies the constraints. In the experiment, our method was compared with the state-of-the-art techniques in a simulated mountainous driving environment, namely Model Predictive Control (MPC), Deep Reinforcement Learning (DRL) and Hybrid A. The environment was built with abundant variation in road curvature and adhesion. The results showed that our approach was able to generate safe and comfort trajectories in both sharp turn and ice-covered driving scenarios, in which the vehicle successfully passed through the whole length of the global path without producing large deviations and exceeding lane boundaries. Whereas, the MPC, DRL and Hybrid A approaches resulted in the vehicle exceeding lanes at some point with completeness levels of 77.72%, 75.31% and 79.53%, respectively.
关键词	Roads Trajectory Adhesives Planning Accidents Vehicle dynamics Trajectory planning Road curvature road adhesion local trajectory planning autonomous driving varying road conditions
DOI	10.1109/TITS.2024.3416289
收录类别	SCI
语种	英语
资助项目	Key Research Project of Zhejiang Lab[2022PC0AC01]
WOS研究方向	Engineering ; Transportation
WOS类目	Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology
WOS记录号	WOS:001258806800001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/39871
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Li, Wei; Hu, Yu
作者单位	1.Zhejiang Lab, Res Ctr Frontier Fundamental Studies, Hangzhou 311121, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Res Ctr Intelligent Comp Syst, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Gao, Yifan,Li, Wei,Hu, Yu. Trajectory Planning for Autonomous Driving Featuring Time-Varying Road Curvature and Adhesion Constraints[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2024:18.
APA	Gao, Yifan,Li, Wei,&Hu, Yu.(2024).Trajectory Planning for Autonomous Driving Featuring Time-Varying Road Curvature and Adhesion Constraints.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,18.
MLA	Gao, Yifan,et al."Trajectory Planning for Autonomous Driving Featuring Time-Varying Road Curvature and Adhesion Constraints".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2024):18.