Ning Wu, Weiwei Huang, Zhiwei Song, Xiaojun Wu, Qun Zhang, Susu Yao
{"title":"基于DDP路径规划器的自动驾驶车辆轨迹跟踪自适应动态预览控制","authors":"Ning Wu, Weiwei Huang, Zhiwei Song, Xiaojun Wu, Qun Zhang, Susu Yao","doi":"10.1109/IVS.2015.7225817","DOIUrl":null,"url":null,"abstract":"For autonomous navigation system of intelligent vehicle, robust and stable control with accurate tracking ability is one of the key requirements. In this paper, we present a systematic controller design approach for autonomous vehicle navigation system. The proposed controller integrates dynamic vehicle model and online updated path model by quadratic programming (QP) cost function, which considers both tracking error and stability. A novel path planner based on the differential dynamic programming (DDP) with consideration of the kinematic feasibility is used. The path tracking accuracy has been improved by utilizing the proposed dynamic preview controller. Promising experimental results showed that the overall navigation system is robust and stable.","PeriodicalId":294701,"journal":{"name":"2015 IEEE Intelligent Vehicles Symposium (IV)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Adaptive dynamic preview control for autonomous vehicle trajectory following with DDP based path planner\",\"authors\":\"Ning Wu, Weiwei Huang, Zhiwei Song, Xiaojun Wu, Qun Zhang, Susu Yao\",\"doi\":\"10.1109/IVS.2015.7225817\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For autonomous navigation system of intelligent vehicle, robust and stable control with accurate tracking ability is one of the key requirements. In this paper, we present a systematic controller design approach for autonomous vehicle navigation system. The proposed controller integrates dynamic vehicle model and online updated path model by quadratic programming (QP) cost function, which considers both tracking error and stability. A novel path planner based on the differential dynamic programming (DDP) with consideration of the kinematic feasibility is used. The path tracking accuracy has been improved by utilizing the proposed dynamic preview controller. Promising experimental results showed that the overall navigation system is robust and stable.\",\"PeriodicalId\":294701,\"journal\":{\"name\":\"2015 IEEE Intelligent Vehicles Symposium (IV)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-08-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE Intelligent Vehicles Symposium (IV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IVS.2015.7225817\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Intelligent Vehicles Symposium (IV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2015.7225817","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive dynamic preview control for autonomous vehicle trajectory following with DDP based path planner
For autonomous navigation system of intelligent vehicle, robust and stable control with accurate tracking ability is one of the key requirements. In this paper, we present a systematic controller design approach for autonomous vehicle navigation system. The proposed controller integrates dynamic vehicle model and online updated path model by quadratic programming (QP) cost function, which considers both tracking error and stability. A novel path planner based on the differential dynamic programming (DDP) with consideration of the kinematic feasibility is used. The path tracking accuracy has been improved by utilizing the proposed dynamic preview controller. Promising experimental results showed that the overall navigation system is robust and stable.