Deriving Operational Traffic Signal Performance Measures from Vehicle Trajectory Data

Abstract

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.

Estimation of Connected Vehicle Penetration on US Roads in Indiana, Ohio, and Pennsylvania

“…Every month, hundreds of billion passenger Journal of Transportation Technologies vehicle trajectory waypoints, consisting of latitude, longitude, heading, speed, and timestamp, are collected in the United States. The resulting data sets can provide agencies with a plethora of historically difficult to collect data, such as traffic signal performance measures, hard-braking events, interstate congestion, and common detours around road closures [1] [2] [3] [4].…”

Diverging Diamond Interchange Performance Measures Using Connected Vehicle Data

“…Vehicle trajectories have been used to estimate queue lengths [19] [20]. Traditional travel times [21] [22], Highway Capacity Manual (HCM) Level of Service (LOS) [23] [24] [25] [26] [27], and arrivals on green [24] [25] [26] [28] have also been calculated. In addition, critical analysis on the percentage of vehicles experiencing split failures and downstream blockage can also be derived from CV trajectory data [24] [25].…”

“…To accomplish this goal, a variation of the PPD by identifying the number of trajectories with two or more stops at a traffic signal since those events are indicative of split failures. Finally, downstream blockage, as defined in [24], can be identified by looking at the vehicle's progression immediately after crossing the far side of an intersection (blue lines). The more delay after a vehicle crosses the far side of an intersection, the more likely downstream blockage is experienced.…”

“…Apart from the performance graphics presented previously, it is useful for agen-cies to have graphics that can be used to rapidly understand temporal variations in the performance of all movements at a DDI. To address this need, graphics that provide a summary of performance measures, based in [24] [25], by TOD, in 15-minute periods, are provided. In these graphics, the trajectories' source is specified; further, if individual (1 or 2) or a combination (1 and 2) of traffic signals are analyzed is also indicated.…”

“…[25] is proposed. A PPD shows the linear-referenced progression of vehicles relative to the far side of an intersection, color-coded by the number of stops.…”