{"title":"Path Planning for CAVs Considering Dynamic Obstacle Avoidance Based on Improved Driving Risk Field and A* Algorithm","authors":"Ye Tian, Huaxin Pei, Yi Zhang","doi":"10.1109/ISCTT51595.2020.00056","DOIUrl":null,"url":null,"abstract":"In vehicle path planning, safety is the most important consideration. As a main and popular index of traffic risk assessment, driving risk field can describe the comprehensive driving risk of complex traffic scenes, and has strong real-time performance. In view of the defects of the existing driving risk field model, this paper proposes an improved driving risk field with ellipse modification formula. Compared with the existing research, the improved model can take into account the safety differences in different directions of the road. Then, a path planning algorithm based on improved driving risk field and A * algorithm is proposed for CA V s, which considers dynamic obstacle avoidance. The simulation result shows that the algorithm is accurate and feasible, which can ensure the driving safety of vehicle in the process of path planning and improve the efficiency of the algorithm.","PeriodicalId":178054,"journal":{"name":"2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT)","volume":"311 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCTT51595.2020.00056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In vehicle path planning, safety is the most important consideration. As a main and popular index of traffic risk assessment, driving risk field can describe the comprehensive driving risk of complex traffic scenes, and has strong real-time performance. In view of the defects of the existing driving risk field model, this paper proposes an improved driving risk field with ellipse modification formula. Compared with the existing research, the improved model can take into account the safety differences in different directions of the road. Then, a path planning algorithm based on improved driving risk field and A * algorithm is proposed for CA V s, which considers dynamic obstacle avoidance. The simulation result shows that the algorithm is accurate and feasible, which can ensure the driving safety of vehicle in the process of path planning and improve the efficiency of the algorithm.