{"title":"An Improved Local Dynamic Path Planning Algorithm for Autonomous Driving","authors":"Huakang Chen, Pengju Chen, Haiying Liu, J. Gu, Lixia Deng, Juanting Zhou, Huiyuan Zhou","doi":"10.1109/ROBIO49542.2019.8961468","DOIUrl":null,"url":null,"abstract":"In this paper, an improved autonomous driving local dynamic path planning algorithm is proposed. Based on the predefined road center points, a set of path control points is constructed, and a one-dimensional cubic equation is used to fit the path and construct a center line. A new curved coordinate system is provided using the center line, and the path candidates are generated by arc length and lateral offset. The overall path is selected in consideration of the total cost of path safety and comfort. The results showed that under different scenarios, the proposed local path planning algorithm can plan an optimal path that does not collide with static obstacles, and can ensure the comfort of autonomous driving vehicles and the real-time path planning.","PeriodicalId":121822,"journal":{"name":"2019 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conference on Robotics and Biomimetics (ROBIO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBIO49542.2019.8961468","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, an improved autonomous driving local dynamic path planning algorithm is proposed. Based on the predefined road center points, a set of path control points is constructed, and a one-dimensional cubic equation is used to fit the path and construct a center line. A new curved coordinate system is provided using the center line, and the path candidates are generated by arc length and lateral offset. The overall path is selected in consideration of the total cost of path safety and comfort. The results showed that under different scenarios, the proposed local path planning algorithm can plan an optimal path that does not collide with static obstacles, and can ensure the comfort of autonomous driving vehicles and the real-time path planning.