动态物理拓扑下基于CPS的混合交通牵制控制
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作者单位:

1. 重庆大学 自动化学院,重庆 400030;2. 重庆大学 信息物理社会可信服务计算 教育部重点实验室,重庆 400030;3. 重庆大学 计算机学院,重庆 400030

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E-mail: d3sun@163.com.

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TP273

基金项目:

国家重点研发计划项目(2018YFB1600600).


CPS-based mixed traffic pinning control considering dynamic physical topology
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Affiliation:

1. School of Automation,Chongqing University,Chongqing 400030,China;2. Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education,Chongqing University,Chongqing 400030,China;3. College of Computer Science,Chongqing University,Chongqing 400030,China

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    摘要:

    随着自动驾驶技术的发展,传统人驾车与自动驾驶车将在一段时间内共存,形成一类新型混合交通.网联自动车的出现为车辆协同行驶提供了新的控制手段,传统的混合交通效率优化控制方法更多地立足于宏观流量的控制或小群体的局部优化,CAV对交通优化作用的潜能还有待开发.鉴于此,首先给出混合交通的信息物理描述,揭示混合交通物理拓扑的动态性;然后提出一种动态物理拓扑下基于CPS的混合交通牵制控制方法,该方法通过调节网联自动车的行驶状态,间接影响、诱导和控制交通中存在的传统人驾车,从而优化整个交通系统.基于Matlab的仿真实验验证了所提出方法的有效性,而基于SUMO的仿真实验表明所提出的牵制控制方法在更真实的场景下依然适用.

    Abstract:

    With the development of autonomous driving technology, human driving vehicles and automated driving vehicles will coexist for a period of time, forming a new type of mixed transportation. Connected and automated vehicles(CAVs) could bring new control methods for coordinated driving of vehicles. Mixed traffic efficiency optimization control methods are more based on macro-flow control or local optimization of small groups. The potential of CAVs for traffic optimization has yet to be developed. Therefore, first, the cyber physical description of mixed traffic is given, and the dynamics of the physical topology of mixed traffic is revealed. Then, a CPS-based mixed traffic pinning control method considering dynamic physical topology from the perspective of cyber-physical is given. This method adjusts the motion state of the CAV to indirectly influence, induce and control the human driving vehicles in traffic, thereby optimizing the entire transportation system. The simulation experiment based on Matlab verifies the effectiveness of the proposed method, and the simulation experiment based on SUMO shows that the proposed pinning control method is applicable in more realistic scenarios.

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孙棣华,刘忠诚,赵敏,等.动态物理拓扑下基于CPS的混合交通牵制控制[J].控制与决策,2023,38(3):729-737

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  • 在线发布日期: 2023-02-17
  • 出版日期: 2023-03-20
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