Predictive Priority for Light Rail Transit

Abstract

The goal of this paper is to assess the operational implementation of strategies for predictive light rail priority through microsimulation. A 2-mi corridor in Salt Lake County, Utah, where the University Line of light rail line operates, was studied. The study used VISSIM microsimulation models to analyze light rail operations and the effects that light rail priority has on transit and vehicular traffic. Results showed that although the existing priority strategies had no effects on vehicular traffic along the corridor, they reduced train travel times by 20% to 30%. Left turns along the main corridor were slightly affected by the priority. Although the priority strategies could have minor to major effects on vehicular traffic along side streets through increased delays, they reduced train delays by 2.5 min along the corridor. Enabling priority at the 700 E intersection (where the priority was currently not active) would help reduce delays for trains by an additional 10%, with a small increase in vehicle delays. However, the coordinated north–south through movements would experience minimum impacts. Three recommendations emerged from the study: enable priority at 700 E to improve transit without major effects on vehicular traffic; reset priority parameters at intersections adjacent to light rail stations so that the priority call encompasses station dwell times; and consider removing the queue jump strategies, so as to reduce delays for the corridor through movements and help preserve coordination patterns.