文章基本信息

标题：An Improved Artificial Potential Field Model Considering Vehicle Velocity for Autonomous Driving
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作者：Hu Hongyu ; Zhang Chi ; Sheng Yuhuan 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：31
页码：863-867
DOI：10.1016/j.ifacol.2018.10.095
语种：English
出版社：Elsevier
摘要：AbstractPath planning is one of the most crucial technologies for autonomous driving. An improved artificial potential field method considering vehicle velocity for path planning is presented in this paper. At first, a combined artificial potential field model is proposed, which includes five components, target potential, road potential, lane potential, vehicle potential and velocity potential. Road potential and lane potential considers the road structure and traffic rules in highway driving. In addition, for vehicle potential, a potential field model is constructed with the absolute velocity and relative velocity which influences the safe distance between the host vehicle and the obstacle vehicle. The design of velocity potential is to prevent unnecessary lane changing behavior. Finally, the collision avoidance path for autonomous driving is calculated with gradient method from the superposition of disparate potential function. According to the simulation experimental validation, the results show the proposed method can achieve good performance for autonomous driving in highway.
关键词：Keywordsautonomous drivingpath planningartificial potential fieldvehicle velocity