Motion Planning of Autonomous Driving Vehicles Based on Search Algorithms and Motion Primitives
Konferenz: ECITech 2022 - The 2022 International Conference on Electrical, Control and Information Technology
25.03.2022 - 27.03.2022 in Kunming, China
Tagungsband: ECITech 2022
Seiten: 6Sprache: EnglischTyp: PDF
Autoren:
Jin, Ma (Department of Electrical Engineering, Tsinghua University, Beijing, China & HRG (Hefei) International Institute for Research & Innovation, Hefei, China)
Chen, Xi; Wu, Zihan; Liu, Yiqun (School of Automotive Engineering, Harbin Institute of Technology, Weihai, China)
Li, Xiaolong; Xia, Kerui (HRG (Hefei) International Institute for Research & Innovation, Hefei, China)
Zhang, Pinjia (Department of Electrical Engineering, Tsinghua University, Beijing, China)
Inhalt:
Motion planning for autonomous vehicles not only requires real-time planning of maneuverable trajectories, but also requires it to have good environmental adaptability. This paper takes the intelligent vehicle as the research object, and establishes the kinematics/dynamics model of the vehicle and the kinematics monorail python model. Based on the manipulating automaton generator provided in CommonRoad and the parameters of the vehicle model actually established, a set of motion primitives suitable for general urban roads is generated. Through the improved A* search algorithm, a maneuvering automaton is constructed, and the results show that feasible solutions can be obtained under typical road traffic conditions, and the algorithm is effective and stable.