{"title":"具有网络延迟和干扰的自主车辆鲁棒学习控制","authors":"Jing Wang, Engang Tian, Huaicheng Yan","doi":"10.1080/15472450.2024.2329912","DOIUrl":null,"url":null,"abstract":"This paper deals with a robust learning nonlinear model predictive control (RL-NMPC) scheme under time-varying delays and disturbances. It is well known that the in-vehicle network has considerable...","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"67 1 1","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Robust learning control for autonomous vehicle with network delays and disturbances\",\"authors\":\"Jing Wang, Engang Tian, Huaicheng Yan\",\"doi\":\"10.1080/15472450.2024.2329912\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with a robust learning nonlinear model predictive control (RL-NMPC) scheme under time-varying delays and disturbances. It is well known that the in-vehicle network has considerable...\",\"PeriodicalId\":54792,\"journal\":{\"name\":\"Journal of Intelligent Transportation Systems\",\"volume\":\"67 1 1\",\"pages\":\"\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Intelligent Transportation Systems\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/15472450.2024.2329912\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"TRANSPORTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Intelligent Transportation Systems","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/15472450.2024.2329912","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TRANSPORTATION","Score":null,"Total":0}
Robust learning control for autonomous vehicle with network delays and disturbances
This paper deals with a robust learning nonlinear model predictive control (RL-NMPC) scheme under time-varying delays and disturbances. It is well known that the in-vehicle network has considerable...
期刊介绍：
The Journal of Intelligent Transportation Systems is devoted to scholarly research on the development, planning, management, operation and evaluation of intelligent transportation systems. Intelligent transportation systems are innovative solutions that address contemporary transportation problems. They are characterized by information, dynamic feedback and automation that allow people and goods to move efficiently. They encompass the full scope of information technologies used in transportation, including control, computation and communication, as well as the algorithms, databases, models and human interfaces. The emergence of these technologies as a new pathway for transportation is relatively new.
The Journal of Intelligent Transportation Systems is especially interested in research that leads to improved planning and operation of the transportation system through the application of new technologies. The journal is particularly interested in research that adds to the scientific understanding of the impacts that intelligent transportation systems can have on accessibility, congestion, pollution, safety, security, noise, and energy and resource consumption.
The journal is inter-disciplinary, and accepts work from fields of engineering, economics, planning, policy, business and management, as well as any other disciplines that contribute to the scientific understanding of intelligent transportation systems. The journal is also multi-modal, and accepts work on intelligent transportation for all forms of ground, air and water transportation. Example topics include the role of information systems in transportation, traffic flow and control, vehicle control, routing and scheduling, traveler response to dynamic information, planning for ITS innovations, evaluations of ITS field operational tests, ITS deployment experiences, automated highway systems, vehicle control systems, diffusion of ITS, and tools/software for analysis of ITS.
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