The turning movement count data is crucial for traffic signal design, intersection geometry planning, traffic flow, and congestion analysis. This work proposes three methods called dynamic, static, and hybrid configuration for TMC-based traffic signals. A vision-based tracking system is developed to estimate the TMC of six intersections in Las Vegas using traffic cameras. The intersection design, route (e.g. vehicle movement directions), and signal configuration files with compatible formats are synthesized and imported into Simulation of Urban MObility for signal evaluation with realistic data. The initial experimental results based on estimated waiting times indicate that the cycle time of 90 and 120 seconds works best for all intersections. In addition, four intersections show better performance for dynamic signal timing configuration, and the other two with lower performance have a lower ratio of total vehicle count to total lanes of the intersection leg. Since daily traffic flow often exhibits a bimodal pattern, we propose a hybrid signal method that switches between dynamic and static methods, adapting to peak and off-peak traffic conditions for improved flow management. So, a built-in traffic generator module creates vehicle routes for 4 hours, including peak hours, and a signal design module produces signal schedule cycles according to static, dynamic, and hybrid methods. Vehicle count distributions are weighted differently for each zone (i.e., West, North, East, South) to generate diverse traffic patterns. The extended experimental results for 6 intersections with 4 hours of simulation time imply that zone-based traffic pattern distributions affect signal design selection. Although the static method works great for evenly zone-based traffic distribution, the hybrid method works well for highly weighted traffic at intersection pairs of the West-East and North-South zones.

翻译：转向流量计数数据对于交通信号灯设计、交叉口几何规划、交通流及拥堵分析至关重要。本研究提出了三种基于TMC的交通信号灯配置方法，分别称为动态、静态及混合配置。开发了一套基于视觉的追踪系统，利用交通摄像头估算拉斯维加斯六个交叉口的TMC。综合交叉口设计、路线（如车辆行驶方向）及兼容格式的信号配置文件，并将其导入城市交通仿真平台，使用真实数据进行信号评估。基于预估等待时间的初步实验结果表明，90秒和120秒的周期时长对所有交叉口效果最佳。此外，四个交叉口在动态信号配时配置下表现更优，而另外两个表现较差的交叉口，其总车辆数与交叉口支路总车道数的比值较低。鉴于日常交通流常呈现双峰模式，我们提出一种混合信号方法，可在动态与静态方法间切换，以适应高峰与平峰时段的交通状况，从而优化流量管理。为此，内置的交通生成模块创建了包含高峰时段在内的4小时车辆路径，信号设计模块则根据静态、动态及混合方法生成信号配时周期。各区域（即西、北、东、南）的车辆计数分布采用差异化权重，以生成多样化的交通模式。对6个交叉口进行4小时仿真的扩展实验结果表明，基于区域的交通模式分布会影响信号设计的选择。尽管静态方法在区域均衡的交通分布下表现优异，混合方法则在西-东和北-南区域对交叉口对交通量赋予高权重时效果显著。