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车路协同环境下车辆群体协同决策研究综述

张毅 裴华鑫 姚丹亚

张毅, 裴华鑫, 姚丹亚. 车路协同环境下车辆群体协同决策研究综述[J]. 交通运输工程学报, 2022, 22(3): 1-18. doi: 10.19818/j.cnki.1671-1637.2022.03.001
引用本文: 张毅, 裴华鑫, 姚丹亚. 车路协同环境下车辆群体协同决策研究综述[J]. 交通运输工程学报, 2022, 22(3): 1-18. doi: 10.19818/j.cnki.1671-1637.2022.03.001
ZHANG Yi, PEI Hua-xin, YAO Dan-ya. Research review on cooperative decision-making for vehicle swarms in vehicle-infrastructure cooperative environment[J]. Journal of Traffic and Transportation Engineering, 2022, 22(3): 1-18. doi: 10.19818/j.cnki.1671-1637.2022.03.001
Citation: ZHANG Yi, PEI Hua-xin, YAO Dan-ya. Research review on cooperative decision-making for vehicle swarms in vehicle-infrastructure cooperative environment[J]. Journal of Traffic and Transportation Engineering, 2022, 22(3): 1-18. doi: 10.19818/j.cnki.1671-1637.2022.03.001

车路协同环境下车辆群体协同决策研究综述

doi: 10.19818/j.cnki.1671-1637.2022.03.001
基金项目: 

国家重点研发计划 2018YFB1600600

详细信息
    作者简介:

    张毅(1964-),男,北京人,清华大学教授,工学博士,从事车路协同与自动驾驶理论与技术研究

  • 中图分类号: U491.2

Research review on cooperative decision-making for vehicle swarms in vehicle-infrastructure cooperative environment

Funds: 

National Key Research and Development Program of China 2018YFB1600600

More Information
  • 摘要: 从车路协同环境下车辆群体协同决策机制、协同决策方法与典型应用场景方面分析了国内外车辆群体协同决策的研究现状;考虑车辆群体协同决策机制的不同,系统梳理了集中式和分布式2种决策机制的相关研究;针对车辆群体协同决策方法的多样性,以基于优化和基于启发式2类决策方法为主线,对比分析了不同决策方法的优劣;考虑车辆群体协同决策应用场景的不同,全面分析了匝道、路口、路段和路网等多个应用场景下车辆群体协同决策的相关理论与研究;考虑国内外车辆协同决策典型项目进展,分别梳理了中国、美国、日本和欧洲代表性车辆群体协同决策项目任务、建设与实施情况;从系统结构、普适模型和示范场景3个方面提出了未来车路协同环境下车辆群体协同决策的发展趋势。研究结果表明:集中式车辆群体协同决策机制有助于提升局部区域内的车辆通行性能,分布式车辆群体协同决策机制有助于提升全局范围内的交通运行状态;基于优化的车辆群体协同决策方法在特定场景下可最大程度提升决策效果,基于启发式的车辆群体协同决策方法在大多数场景下可获得可行的决策效果;由于不同场景下车辆群体协同决策问题的复杂性有所不同,需要在统一框架下做针对性建模。研究结果可为车路协同环境下新型混合交通系统的管理与控制提供参考。

     

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出版历程
  • 收稿日期:  2021-12-24
  • 刊出日期:  2022-06-25

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