{"title":"Autonomous Vehicle Tracking and Collision Avoidance Using Adaptive Control Algorithms","authors":"Qianhong Zhao, G. Tao","doi":"10.1109/sieds55548.2022.9799339","DOIUrl":null,"url":null,"abstract":"This paper studies the control problems of a vehicle passing an intersection: the designed controller can make the controlled vehicle pass the intersection quickly and avoid any collision. In this research, the state-space model of the vehicle dynamics, containing several uncertain parameters, is established. The adaptive control method is adopted to deal with the systems parameter uncertainties in such vehicle control problems. For this study, two adaptive control designs are developed to solve the problem: a baseline adaptive control design and an enhanced adaptive control design. Unlike the classic PI controller which can only make the vehicle track constant velocity trajectories, both two adaptive control designs can achieve asymptotic tracking of arbitrary vehicle velocity trajectories. The enhanced adaptive design can even further improve the system tracking performance.","PeriodicalId":286724,"journal":{"name":"2022 Systems and Information Engineering Design Symposium (SIEDS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Systems and Information Engineering Design Symposium (SIEDS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/sieds55548.2022.9799339","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
This paper studies the control problems of a vehicle passing an intersection: the designed controller can make the controlled vehicle pass the intersection quickly and avoid any collision. In this research, the state-space model of the vehicle dynamics, containing several uncertain parameters, is established. The adaptive control method is adopted to deal with the systems parameter uncertainties in such vehicle control problems. For this study, two adaptive control designs are developed to solve the problem: a baseline adaptive control design and an enhanced adaptive control design. Unlike the classic PI controller which can only make the vehicle track constant velocity trajectories, both two adaptive control designs can achieve asymptotic tracking of arbitrary vehicle velocity trajectories. The enhanced adaptive design can even further improve the system tracking performance.