Ran Yi , Yifan Yao , Fan Pu , Yang Zhou , Xin Wang
{"title":"Cooperative CAV mandatory lane-change control enabled by V2I","authors":"Ran Yi , Yifan Yao , Fan Pu , Yang Zhou , Xin Wang","doi":"10.1016/j.commtr.2024.100126","DOIUrl":null,"url":null,"abstract":"<div><p>This paper presents a spatially formulated cooperative dynamic mandatory connected automated vehicle (CAV) lane-changing and car-following approach on curved highways with the assistance of vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication. This work proposes mandatory lane-changing control in a spatial domain to accomplish car-following and lane-changing efficiency in a systematic manner. This control technique initially creates a virtual CAV car-following lane by assigning CAVs sequential numbers based on their spatial position. On this basis, a multi-objective model predictive control (MPC) strategy in the spatial domain is designed to optimize the trajectories in a rolling horizon fashion in order to maintain the inter-vehicle spacing and speed difference while simultaneously satisfying collision avoidances, traffic regulations, and vehicle kinematics constraints. Multi-scenario numerical simulations are conducted to validate the control efficacy of our technique.</p></div>","PeriodicalId":100292,"journal":{"name":"Communications in Transportation Research","volume":"4 ","pages":"Article 100126"},"PeriodicalIF":12.5000,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S277242472400009X/pdfft?md5=05853561b7b736da6439f4266819c14b&pid=1-s2.0-S277242472400009X-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications in Transportation Research","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S277242472400009X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents a spatially formulated cooperative dynamic mandatory connected automated vehicle (CAV) lane-changing and car-following approach on curved highways with the assistance of vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication. This work proposes mandatory lane-changing control in a spatial domain to accomplish car-following and lane-changing efficiency in a systematic manner. This control technique initially creates a virtual CAV car-following lane by assigning CAVs sequential numbers based on their spatial position. On this basis, a multi-objective model predictive control (MPC) strategy in the spatial domain is designed to optimize the trajectories in a rolling horizon fashion in order to maintain the inter-vehicle spacing and speed difference while simultaneously satisfying collision avoidances, traffic regulations, and vehicle kinematics constraints. Multi-scenario numerical simulations are conducted to validate the control efficacy of our technique.