无人车集群协同围捕发展现状分析  

Analysis on Current Development Situation of Unmanned Ground Vehicle Clusters Collaborative Pursuit

作　　者：徐友春 郭宏达 娄静涛 叶鹏 苏致远 XU Youchun;GUO Hongda;LOU Jingtao;YE Peng;SU Zhiyuan(Army Military Transportation University,Tianjin 300161,China)

机构地区：[1]陆军军事交通学院,天津300161

出　　处：《电子与信息学报》2024年第2期456-471,共16页Journal of Electronics & Information Technology

摘　　要：无人车集群具有成本低、安全性好、自主程度高等优点,已成为无人驾驶领域的研究热点。基于无人车集群,研究人员提出多种不同协同策略以完成各类任务,其中协同围捕作为重要的应用方向,无论是在军用还是民用领域都受到了广泛关注。针对此问题,该文首先基于无人车集群的相关应用和架构,对协同围捕的策略机理进行了系统分析,并将协同围捕策略划分为搜索、追踪和围堵3个子模式。然后,从博弈论、概率分析和机器学习等角度梳理了协同围捕的关键方法,并对这些算法的优缺点进行了比较。最后,对未来研究提出了意见建议,为进一步提高无人车集群协同围捕的效率和性能提供参考和思路。In recent years,there has been a growing interest in unmanned ground vehicle clustering as a research topic in the unmanned driving field for its low cost,good secuity,and high autonomy.Various collaborative strategies have been proposed for unmanned vehicle clusters,with collaborative pursuit being a particularly important application direction that has garnered significant attention in various fields.A systematic analysis of the strategy mechanism for collaborative pursuit in unmanned vehicle clusters is provided,considering relevant applications and architectures.The collaborative pursuit strategy is divided into three sub-modes:search,tracking,and roundup.The key methods for unmanned vehicle cluster collaborative pursuit are compared from the perspectives of game theory,probabilistic analysis,and machine learning,the advantages and disadvantages of these algorithms are highlighted.Finally,comments and suggestions are provided for future research,considering offer references and ideas for further improving the efficiency and performance of collaborative pursuit in unmanned vehicle clusters.

关 键 词：无人车集群 协同围捕 策略机理 搜索 追踪 围堵 

分 类 号：TN929.5[电子电信—通信与信息系统] T249[电子电信—信息与通信工程]