{"title":"Consensus-Based Fault-Tolerant Platooning for Connected and Autonomous Vehicles","authors":"Tzu-Yen Tseng, Ding Huang, Jia-You Lin, Po-Jui Chang, Chung-Wei Lin, Changliu Liu","doi":"10.1109/IV55152.2023.10186667","DOIUrl":null,"url":null,"abstract":"Platooning is a representative application of connected and autonomous vehicles. The information exchanged between connected functions and the precise control of autonomous functions provide great safety and traffic capacity. In this paper, we develop an advanced consensus-based approach for platooning. By applying consensus-based fault detection and adaptive gains to controllers, we can detect faulty position and speed information from vehicles and reinstate the normal behavior of the platooning. Experimental results demonstrate that the developed approach outperforms the state-of-the-art approaches and achieves small steady state errors and small settling times under scenarios with faults.","PeriodicalId":195148,"journal":{"name":"2023 IEEE Intelligent Vehicles Symposium (IV)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE Intelligent Vehicles Symposium (IV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IV55152.2023.10186667","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
Platooning is a representative application of connected and autonomous vehicles. The information exchanged between connected functions and the precise control of autonomous functions provide great safety and traffic capacity. In this paper, we develop an advanced consensus-based approach for platooning. By applying consensus-based fault detection and adaptive gains to controllers, we can detect faulty position and speed information from vehicles and reinstate the normal behavior of the platooning. Experimental results demonstrate that the developed approach outperforms the state-of-the-art approaches and achieves small steady state errors and small settling times under scenarios with faults.