Operations-oriented traffic signal performance measures are important for identifying the need for retiming to improve traffic signal operations. Currently, most traffic signal performance measures are obtained from high-resolution traffic signal controller event data, which provides information on an intersection-by-intersection basis and requires significant initial capital investment. Over 400 billion vehicle trajectory points are generated each month in the United States. This paper proposes using high-fidelity vehicle trajectory data to produce traffic signal performance measures such as: split failure, downstream blockage, and quality of progression, as well as traditional Highway Capacity Manual level of service. Geo-fences are created at specific signalized intersections to filter vehicle waypoints that lie within the generated boundaries. These waypoints are then converted into trajectories that are relative to the intersection. A case study is presented that summarizes the performance of an eight-intersection corridor with four different timing plans using over 160,000 trajectories and 1.4 million GPS samples collected during weekdays in July 2019 between 5:00 a.m. and 10:00 p.m. The paper concludes by commenting on current probe data penetration rates, indicating that these techniques can be applied to corridors with annual average daily traffic of ~15,000 vehicles per day for the mainline approaches, and discussing cloud-based implementation opportunities.

面向操作的交通信号灯性能指标对于确定重新定时以改善交通信号灯操作的需求非常重要。当前，大多数交通信号性能度量是从高分辨率交通信号控制器事件数据获得的，该数据以逐个交叉点的方式提供信息，并且需要大量的初始资金投入。在美国，每月产生超过4000亿的车辆轨迹点。本文建议使用高保真车辆轨迹数据来生成交通信号性能指标，例如：分割故障，下游阻塞和行驶质量，以及传统的公路通行能力手册服务水平。在特定的信号交叉口创建地理围栏，以过滤位于生成边界内的车辆航路点。然后将这些航路点转换为相对于交叉点的轨迹。提出了一个案例研究，总结了一个具有四个不同时序计划的八路口走廊的性能，使用了2019年7月工作日上午5:00至晚上10:00期间收集的160,000条轨迹和140万个GPS样本根据当前的探测数据渗透率，表明这些技术可应用于干线方法的年平均日流量为每年约15,000辆车的走廊，并讨论了基于云的实施机会。