{"title":"基于数字地图的自动驾驶汽车轨迹规划","authors":"Jure Bajić, M. Herceg, Ivan Resetar, I. Velikic","doi":"10.1109/ZINC.2019.8769382","DOIUrl":null,"url":null,"abstract":"In this paper, an algorithm for autonomous vehicle trajectory planning is proposed. The proposed algorithm consists of two parts. In the first part, transformation of given coordinates from Cartesian system to Frenet-Serret system is applied, along with interpolation of points in trajectory. In the second part, most efficient trajectory is being chosen and optimized. The algorithm was developed in Udacity’s simulator, where it was tested and compared with other similar algorithms. The algorithm shows promising performance through testing.","PeriodicalId":190326,"journal":{"name":"2019 Zooming Innovation in Consumer Technologies Conference (ZINC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Trajectory Planning for Autonomous Vehicle Using Digital Map\",\"authors\":\"Jure Bajić, M. Herceg, Ivan Resetar, I. Velikic\",\"doi\":\"10.1109/ZINC.2019.8769382\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, an algorithm for autonomous vehicle trajectory planning is proposed. The proposed algorithm consists of two parts. In the first part, transformation of given coordinates from Cartesian system to Frenet-Serret system is applied, along with interpolation of points in trajectory. In the second part, most efficient trajectory is being chosen and optimized. The algorithm was developed in Udacity’s simulator, where it was tested and compared with other similar algorithms. The algorithm shows promising performance through testing.\",\"PeriodicalId\":190326,\"journal\":{\"name\":\"2019 Zooming Innovation in Consumer Technologies Conference (ZINC)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Zooming Innovation in Consumer Technologies Conference (ZINC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ZINC.2019.8769382\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Zooming Innovation in Consumer Technologies Conference (ZINC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ZINC.2019.8769382","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Trajectory Planning for Autonomous Vehicle Using Digital Map
In this paper, an algorithm for autonomous vehicle trajectory planning is proposed. The proposed algorithm consists of two parts. In the first part, transformation of given coordinates from Cartesian system to Frenet-Serret system is applied, along with interpolation of points in trajectory. In the second part, most efficient trajectory is being chosen and optimized. The algorithm was developed in Udacity’s simulator, where it was tested and compared with other similar algorithms. The algorithm shows promising performance through testing.