Characterizing Traffic-Signal Performance and Corridor Reliability Using Crowd-Sourced Probe Vehicle Trajectories

Abstract

Performance measures offer an essential management tool for transportation engineers to make decisions along signalized corridors. Current signal performance strategies assess coordination of a corridor using intersection-level metrics while relying on expensive infrastructure to measure vehicle arrivals. Recent crowd-sourced data collection strategies have allowed for the ubiquitous collection of individual vehicle waypoints. These trajectories can be used to replicate existing signal performance measures and improve upon current practices. This paper uses trajectory data from numerous corridors around the state of Michigan to illustrate the merit and versatility of crowd-sourced probe vehicle trajectory-based performance measures. Findings from this paper show that some current automated traffic-signal performance measures (ATSPMs), such as percent arrival on green and delay quantification, can be replicated using low-penetration-rate vehicle trajectory data. Also, the reliability-based performance metric, level of travel time reliability (LOTTR), can be improved using trajectories of vehicles known to travel the complete corridor instead of aggregating segmented probe vehicle data.