Optimizing Bus Rapid Transit Systems: A Simulation Approach to Scheduling

Driven by increasing urbanization and traffic congestion challenges, efficient and cost‐effective public transportation solutions have become essential, positioning bus rapid transit (BRT) systems as an attractive alternative to conventional modes. This study presents a comprehensive discrete‐event simulation (DES) model developed to optimize scheduling in BRT systems, focusing on the recently implemented BRT line in Amman, Jordan. The model integrates real‐world operational constraints—including dynamic passenger arrivals modeled as Poisson processes, boarding and alighting behaviors, and signaling for departures—with detailed representations of both peak and off‐peak conditions. By generating multiple what‐if scenarios, the simulation investigates critical trade‐offs between minimizing passenger waiting times and maximizing fleet utilization, demonstrating that under the current publicly funded model, reducing the number of buses during off‐peak hours effectively lowers operational costs while maintaining service quality. Furthermore, the flexibility of the simulation framework permits adaptation to alternative funding models, where increased off‐peak frequencies may be prioritized to enhance ridership. Validated against empirical operational data, the model serves as a robust decision‐support tool that provides valuable insights for urban planners and transit operators seeking to improve resource allocation and service design in modern urban transit systems.