针对城市路网拥堵问题，以紧密联系的交叉口所构成OD路径为切入点，建立基于离散性、阻滞性的路径关联指标进行比拟，选取出关键路径、次关键路径与非关键路径，进而建立智慧子区划分算法。在智慧子区内部，根据车队到达时刻与绿灯启亮时刻的关系，建立干线双向滤波协同控制模型，按照路径的关键程度依次进行优化，进而建立“线–轴”协同控制算法。为验证所提算法的可靠性，采用VISSIM微观仿真软件对算法进行评估，利用C++语言进行二次开发，并将算法的最新控制方案反馈到VISSIM仿真环境中，通过对VISSIM产生的实时数据分析，发现实施本设计控制方案后子区内通行量增加了约7.15%，初步验证了本设计方案的有效性。
Aiming at the problem of urban road network congestion, taking OD paths formed by closely connected intersections as the starting point, the paper establishes a path correlation index based on discreteness and blockade to compare, selects critical paths, sub-critical paths and non-critical paths, and then establishes an intelligent sub-area partition algorithm. In the intelligent sub-area, according to the relationship between the arrival time of the convoy and the green light turning on time, the two-way filtering cooperative control model of trunk line is established, which is optimized according to the critical degree of the path, and then the “line-axis” cooperative control algorithm is established. In order to verify the reliability of the proposed algorithm, VISSIM micro-simulation software is used to evaluate the algorithm, C++ language is used for secondary development, and the latest control scheme of the algorithm is fed back to the VISSIM simulation environment. Through real-time data analysis generated by VISSIM, it is found that the traffic volume in the sub-area increases after the implementation of the control scheme. About 7.15% is achieved, which preliminarily verifies the validity of the design scheme.
