{"title":"基于事件触发的异构车辆队列协同轨迹协调","authors":"Yang Fei, Liang Wang, Xiaobo Qu","doi":"10.1016/j.trc.2025.105049","DOIUrl":null,"url":null,"abstract":"<div><div>This article addresses the issue of achieving inter-vehicle cooperation for vehicles with heterogeneous dynamics. Inter-vehicle collaboration is achieved in the trajectory planning layer instead of the motion control layer to conquer the challenge led by dynamics mismatch. A novel sliding mode cooperative planning scheme is proposed based on a dynamically triggered distributed communication network. To ensure the practicality of the generated trajectories, both velocity constraints and input saturation phenomenon are considered for each vehicle. A reference filter is first designed to transform task information into smooth and trackable curves. The barrier Lyapunov function approach is then introduced to enhance the reachability of the trajectories by maintaining the difference between the planned trajectories and the actual trajectories. By proposing a new cooperative error, static and dynamic trigger schemes are developed for distributed vehicle communication. Comparative simulations regarding a ground–air multi-vehicle system are conducted to validate the effectiveness of our designs.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"173 ","pages":"Article 105049"},"PeriodicalIF":7.6000,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Event triggered cooperative trajectory coordination for platooning among heterogeneous vehicles\",\"authors\":\"Yang Fei, Liang Wang, Xiaobo Qu\",\"doi\":\"10.1016/j.trc.2025.105049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This article addresses the issue of achieving inter-vehicle cooperation for vehicles with heterogeneous dynamics. Inter-vehicle collaboration is achieved in the trajectory planning layer instead of the motion control layer to conquer the challenge led by dynamics mismatch. A novel sliding mode cooperative planning scheme is proposed based on a dynamically triggered distributed communication network. To ensure the practicality of the generated trajectories, both velocity constraints and input saturation phenomenon are considered for each vehicle. A reference filter is first designed to transform task information into smooth and trackable curves. The barrier Lyapunov function approach is then introduced to enhance the reachability of the trajectories by maintaining the difference between the planned trajectories and the actual trajectories. By proposing a new cooperative error, static and dynamic trigger schemes are developed for distributed vehicle communication. Comparative simulations regarding a ground–air multi-vehicle system are conducted to validate the effectiveness of our designs.</div></div>\",\"PeriodicalId\":54417,\"journal\":{\"name\":\"Transportation Research Part C-Emerging Technologies\",\"volume\":\"173 \",\"pages\":\"Article 105049\"},\"PeriodicalIF\":7.6000,\"publicationDate\":\"2025-02-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part C-Emerging Technologies\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0968090X25000531\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"TRANSPORTATION SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part C-Emerging Technologies","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0968090X25000531","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TRANSPORTATION SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Event triggered cooperative trajectory coordination for platooning among heterogeneous vehicles
This article addresses the issue of achieving inter-vehicle cooperation for vehicles with heterogeneous dynamics. Inter-vehicle collaboration is achieved in the trajectory planning layer instead of the motion control layer to conquer the challenge led by dynamics mismatch. A novel sliding mode cooperative planning scheme is proposed based on a dynamically triggered distributed communication network. To ensure the practicality of the generated trajectories, both velocity constraints and input saturation phenomenon are considered for each vehicle. A reference filter is first designed to transform task information into smooth and trackable curves. The barrier Lyapunov function approach is then introduced to enhance the reachability of the trajectories by maintaining the difference between the planned trajectories and the actual trajectories. By proposing a new cooperative error, static and dynamic trigger schemes are developed for distributed vehicle communication. Comparative simulations regarding a ground–air multi-vehicle system are conducted to validate the effectiveness of our designs.
期刊介绍:
Transportation Research: Part C (TR_C) is dedicated to showcasing high-quality, scholarly research that delves into the development, applications, and implications of transportation systems and emerging technologies. Our focus lies not solely on individual technologies, but rather on their broader implications for the planning, design, operation, control, maintenance, and rehabilitation of transportation systems, services, and components. In essence, the intellectual core of the journal revolves around the transportation aspect rather than the technology itself. We actively encourage the integration of quantitative methods from diverse fields such as operations research, control systems, complex networks, computer science, and artificial intelligence. Join us in exploring the intersection of transportation systems and emerging technologies to drive innovation and progress in the field.