Signal Timing Optimization for Corridors with Multiple Highway-Rail Grade Crossings Using Genetic Algorithm


Safety and efficiency are two critical issues at highway-rail grade crossings (HRGCs) and their nearby intersections. Standard traffic signal optimization programs are not designed to work on roadway networks that contain multiple HRGCs, because their underlying assumption is that the roadway traffic is in a steady-state.During a train event, steady-state conditions do not occur.This is particularly true for corridors that experience high train traffic (e.g., over 2 trains per hour). In this situation, the non-steadystate conditions predominate. This paper develops a simulation-based methodology for optimizing traffic signal timing plan on corridors of this kind.The primary goal is to maximize safety, and the secondary goal is to minimize delay. A Genetic Algorithm (GA) was used as the optimization approach in the proposed methodology. A new transition preemption strategy for dual tracks (TPS DT) and a train arrival prediction model were integrated in the proposed methodology. An urban road network withmultiple HRGCs in Lincoln, NE, was used as the study network.The microsimulation model VISSIMwas used for evaluation purposes and was calibrated to local traffic conditions. A sensitivity analysis with different train traffic scenarios was conducted. It was concluded that the methodology can significantly improve both the safety and efficiency of traffic corridors with HRGCs

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