Fan Bailin, Ren Haixiao, Deng Zhangshen, Chen Jianhua
{"title":"基于混合算法的智能车辆路径规划","authors":"Fan Bailin, Ren Haixiao, Deng Zhangshen, Chen Jianhua","doi":"10.1109/ICISCAE51034.2020.9236842","DOIUrl":null,"url":null,"abstract":"Aiming at the path planning problem of smart cars in complex environments, a hybrid algorithm was proposed for path planning. In the hybrid algorithm, the A * algorithm was combined with the artificial potential field method. The hybrid algorithm fully absorbed the advantages of the two algorithms and made up for the shortcomings of their respective algorithms. The existing problems of traditional A * algorithm and artificial potential field method were improved respectively. Then, the two improved algorithms were merged. And the shortest path was obtained by using A * algorithm. The improved artificial potential field method could effectively avoid various obstacles on the road. The hybrid algorithm appearing above made up for the shortcomings that the A * algorithm couldn't be applied to dynamic environments, and the artificial potential field method couldn't plan the shortest path. The effectiveness of the improved algorithm and hybrid algorithm was verified by MATLAB software.","PeriodicalId":355473,"journal":{"name":"2020 IEEE 3rd International Conference on Information Systems and Computer Aided Education (ICISCAE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Intelligent Vehicle Path Planning Based on Hybrid Algorithm\",\"authors\":\"Fan Bailin, Ren Haixiao, Deng Zhangshen, Chen Jianhua\",\"doi\":\"10.1109/ICISCAE51034.2020.9236842\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the path planning problem of smart cars in complex environments, a hybrid algorithm was proposed for path planning. In the hybrid algorithm, the A * algorithm was combined with the artificial potential field method. The hybrid algorithm fully absorbed the advantages of the two algorithms and made up for the shortcomings of their respective algorithms. The existing problems of traditional A * algorithm and artificial potential field method were improved respectively. Then, the two improved algorithms were merged. And the shortest path was obtained by using A * algorithm. The improved artificial potential field method could effectively avoid various obstacles on the road. The hybrid algorithm appearing above made up for the shortcomings that the A * algorithm couldn't be applied to dynamic environments, and the artificial potential field method couldn't plan the shortest path. The effectiveness of the improved algorithm and hybrid algorithm was verified by MATLAB software.\",\"PeriodicalId\":355473,\"journal\":{\"name\":\"2020 IEEE 3rd International Conference on Information Systems and Computer Aided Education (ICISCAE)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 3rd International Conference on Information Systems and Computer Aided Education (ICISCAE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICISCAE51034.2020.9236842\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 3rd International Conference on Information Systems and Computer Aided Education (ICISCAE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISCAE51034.2020.9236842","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Intelligent Vehicle Path Planning Based on Hybrid Algorithm
Aiming at the path planning problem of smart cars in complex environments, a hybrid algorithm was proposed for path planning. In the hybrid algorithm, the A * algorithm was combined with the artificial potential field method. The hybrid algorithm fully absorbed the advantages of the two algorithms and made up for the shortcomings of their respective algorithms. The existing problems of traditional A * algorithm and artificial potential field method were improved respectively. Then, the two improved algorithms were merged. And the shortest path was obtained by using A * algorithm. The improved artificial potential field method could effectively avoid various obstacles on the road. The hybrid algorithm appearing above made up for the shortcomings that the A * algorithm couldn't be applied to dynamic environments, and the artificial potential field method couldn't plan the shortest path. The effectiveness of the improved algorithm and hybrid algorithm was verified by MATLAB software.