Collaborative multi-lane on-ramp merging strategy for connected and automated vehicles using dynamic conflict graph

作     者：Jia Shi Yugong Luo Pengfei Li Jiawei Wang Keqiang Li 

作者机构：School of Vehicle and MobilityTsinghua UniversityBeijing 100084China Department of Civil and Environmental EngineeringUniversity of MichiganAnn ArborMI 48109USA 

出 版 物：《Journal of Intelligent and Connected Vehicles》 (智能网联汽车（英文）)

年 卷 期：2024年第7卷第1期

页      面：38-51页

核心收录：

学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学] 

基　　金：supported by the National Key R&D Program of China(2022YFB2503200) the National Natural Science Foundation of China,Science Fund for Creative Research Groups(52221005) 

主　　题：cooperative merging multi-lane graph theory cyber-physical integration system 

摘      要：The on-ramp merging in multi-lane highway scenarios presents challenges due to the complexity of coordinating vehicles’merging and lane-changing behaviors,while ensuring safety and optimizing traffic ***,there are few studies that have addressed the merging problem of ramp vehicles and the cooperative lane-change problem of mainline vehicles within a unified framework and proposed corresponding optimization *** tackle this issue,this study adopts a cyber-physical integration perspective and proposes a graph-based solution ***,the information of vehicle groups in the physical plane is mapped to the cyber plane,and a dynamic conflict graph is introduced in the cyber space to describe the conflict relationships among vehicle ***,graph decomposition and search strategies are employed to obtain the optimal solution,including the set of mainline vehicles changing lanes,passing sequences for each route,and corresponding ***,the proposed dynamic conflict graph-based algorithm is validated through simulations in continuous traffic with various densities,and its performance is compared with the default algorithm in *** results demonstrate the effectiveness of the proposed approach in improving vehicle safety and traffic efficiency,particularly in high traffic density scenarios,providing valuable insights for future research in multi-lane merging strategies.