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Scalable Operational Traffic Signal Performance Measures from Vehicle Trajectory Data

Operations-oriented traffic signal performance measures are important for identifying retiming needs to improve traffic signal operations. Enhancements on traffic signal timings can lead to a decrease on delays, fuel consumption, and air pollutants.

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. Further, maintenance of the required sensing and communication equipment can represent a significant cost.

Over 400 billion vehicle trajectory points are generated each month in the United States. This high volume of data provides more than 95% of road network coverage. This thesis proposes using vehicle trajectory data to produce traffic signal performance measures such as: traditional Highway Capacity Manual (HCM) Level of Service (LOS), quality of progression, split failure, and downstream blockage.

Geo-fences are created at specific signalized intersections to filter vehicle’s waypoints that lie within the generated boundaries. These waypoints are then converted into trajectories that are relative to the intersection. Subsequently, trajectory attributes, such as delay and location and number of stops, are analyzed to produce the mentioned performance measures.

A case study is presented to demonstrate the methodology, which summarizes the performance of an 8-intersection corridor with 4 different timing plans using over 117,000 trajectories and 1.5 million GPS samples collected during weekdays in July 2019. Graphics to analyze entire corridors and to effectuate temporal comparisons are proposed.

The thesis concludes by discussing the required effort and recommendations for scalability, cloud-based implementation opportunities and costs, reviewing current probe data penetrations rates, and indicating that these techniques can be applied to corridors with Annual Average Daily Traffic (AADT) of ~15,000 vehicles-per-day (VPD) for the mainline approaches.

Funding

Pooled Fund Study (TPF-5(377))

History

Degree Type

Master of Science in Civil Engineering

Department

Civil Engineering

Campus location

West Lafayette

Advisor/Supervisor/Committee Chair

Darcy M. Bullock

Additional Committee Member 2

Andrew P. Tarko

Additional Committee Member 3

Ayman F. Habib