Optimizing Transit Vehicle Performance:A Simulation Study of TSP with Trajectory Smoothing in VISSIM

Abstract: This study proposes a simulation analysis of Transit Signal Priority (TSP) using a rudimentary trajectory smoothing algorithm, implemented through an automation script in VISSIM. The goal is to enhance the performance of connected transit vehicles by dynamically adjusting their speeds to reduce stop delays at signalized intersections. Using the Multi-Modal Intelligent Traffic Signal System (MMITSS) framework Using the Multi-Modal Intelligent Traffic Signal System (MMITSS) framework, developed by the University of Arizona under the guidance of the U.S. Department of Transportation in a Connected Vehicles Pooled Fund (CVP) study. Specifically focusing on TSP, the simulation will evaluate its effectiveness in minimizing travel times for transit vehicles and optimizing real-time signal timing based on vehicle trajectory data. An automation script developed to interface with VISSIM via its COM interface, integrating a basic trajectory smoothing algorithm that adjusts the speeds of connected vehicles (CVs) depending on their distance to upcoming traffic signals and the current signal status. Various comparative scenarios will be examined, including: a baseline scenario with no TSP, TSP without trajectory smoothing, and TSP with trajectory smoothing, to determine whether speed adjustments lead to reduced travel times and delays. A scenario exploring different levels of connected vehicle penetration will also be simulated to assess system performance as V2I (Vehicle-to-Infrastructure) technology adoption increases. The analysis includes an evaluation of the impact on side-street traffic, measuring the trade-offs between improved transit vehicle efficiency and possible increases in delays for other vehicles. Additionally, the system's performance will be tested under high congestion levels to assess its effectiveness during peak traffic conditions. The results are expected to demonstrate improvements in transit vehicle travel times, reductions in intersection delays, and overall enhanced traffic flow efficiency. Through this simulation approach, the study aims to provide valuable insights into the real-time adaptability of TSP systems and their impact on connected transit vehicles within urban environments.