@article{ref1,
title="Deriving operational traffic signal performance measures from vehicle trajectory data",
journal="Transportation research record",
year="2021",
author="Saldivar-Carranza, Enrique and Li, Howell and Mathew, Jijo and Hunter, Margaret and Sturdevant, James and Bullock, Darcy M.",
volume="2675",
number="9",
pages="1250-1264",
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.<p /> <p>Language: en</p>",
language="en",
issn="0361-1981",
doi="10.1177/03611981211006725",
url="http://dx.doi.org/10.1177/03611981211006725"
}