| 基于群体决策的多交叉口协同控制方法 |
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| 引用本文： | 马成元,朱际宸,赖金涛,张振,杨晓光.基于群体决策的多交叉口协同控制方法[J].交通运输工程学报,2022,22(3):152-161. |
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| 作者姓名： | 马成元 朱际宸 赖金涛 张振 杨晓光 |
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| 作者单位： | 同济大学 道路与交通工程教育部重点实验室，上海 201804 |
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| 基金项目： | 国家重点研发计划2018YFB1600600 |
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| 摘 要： | 基于竞争-合作的群体决策机制，将单点信号优化构建为各相位的交叉口通行权的竞争过程，将多点协同构建为上下游相位之间的协作过程，提出了一种兼顾多交叉口协同效益和单交叉口控制优化的路网信号配时设计方法；利用车路协同环境下路网内车辆路径信息的可感知性，动态精准地量化解析上下游交通耦合关系；在此基础上建立了分层动态决策框架，在单层决策中剥离了上下游交叉口控制决策对本地决策的影响，解耦协同控制模型中路网交通状态和信号控制决策之间的复合关系；设计了基于交叉口内各交通流向竞争力的分布式信号配时决策算法，并通过仿真试验平台比较了群体决策协同控制方法与传统协同控制方法的控制效果。研究结果表明: 相较于传统协同控制方法，群体决策协同控制方法可动态适应路网交通需求，在交通效率和稳定性上具有显著优势，在不同饱和度的交通需求水平下可降低车均延误15%以上；在路网交通饱和度较高的情况下, 群体决策协同控制方法延误降低幅度可达19.2%，控制优势更加明显；由于群体决策协同控制方法可在下游交叉口进口道车辆排队过长时减少上游车辆流出，可降低路网最大排队长度超40%，有效规避路网溢流风险；通过对群体决策协同控制模型的分布式求解，可实现单次决策过程计算时间小于0.01 s，具有应用于大规模复杂路网的实时信号配时决策的潜力。
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| 关 键 词： | 交通控制 车路协同系统 信号配时 多交叉口信号协同 群体决策 优化控制 |
| 收稿时间： | 2021-12-13 |
Multi-intersection coordinated control method based on group decision-making |
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| MA Cheng-yuan,ZHU Ji-chen,LAI Jin-tao,ZHANG Zhen,YANG Xiao-guang.Multi-intersection coordinated control method based on group decision-making[J].Journal of Traffic and Transportation Engineering,2022,22(3):152-161. |
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| Authors: | MA Cheng-yuan ZHU Ji-chen LAI Jin-tao ZHANG Zhen YANG Xiao-guang |
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| Affiliation: | Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China |
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| Abstract: | On the basis of the group decision-making mechanism with competition and cooperation, the isolated signal optimization was modeled as the right-of-way competition process of all phases at intersections, and the coordination among many intersections was modeled as the cooperation process between upstream and downstream phases. A signal timing design method for road networks was proposed under considering both the multi-intersection synergy and the optimal control of isolated intersections. The perceptibility of the vehicle route information in road networks under the vehicle-road cooperative environment was used to quantitatively analyze the coupling relationship between upstream and downstream traffic in a dynamic and accurate manner. On this basis, a hierarchical dynamic decision-making framework was established to avoid the impact of the control decisions of upstream and downstream intersections on local decisions in single-layer decision-making, and the composite relationship between the traffic states of road networks and the signal control decision in the cooperative control model was decoupled. A distributed decision-making algorithm for signal timing was designed based on the competitiveness of each traffic flow at intersections, and the performances of the proposed group decision-making cooperative control method and the traditional cooperative control method was compared by a simulation test platform. Research results show that compared with the traditional cooperative control method, the group decision-making cooperative control method can dynamically adapt to the traffic demand of the road network, and has significant advantages in traffic efficiency and stability. Under the traffic demand levels with different saturation degrees, the average vehicle delay can reduces by more than 15%. In the case of high traffic saturation, the delay can reduce by 19.2%, so the control advantage is more obvious. As the upstream outflow of the vehicles can be reduced by the group decision-making cooperative control method when the vehicle queues at downstream intersections for inflow are long, the maximum queue length in road networks can be cut by over 40%. In this way, the overflow risk in road networks can be avoided. Through the distributed solution of the group decision-making cooperative control method, the calculation time of a single decision-making process is less than 0.01 s, so the method has the potential to be applied to the real-time signal timing decision in large-scale complex road network. 1 tab, 7 figs, 31 refs. |
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