Simulation-Based Optimisation of University Shuttle Bus Systems: A Case Study on Redundancy-Aware Route Planning and Energy Utilisation

Optimising university shuttle bus services can improve efficiency, sustainability and cost-effectiveness. This study combines discrete event simulation in Arena® with a path reduction procedure to consolidate two existing shuttle routes at Rajamangala University of Technology Thanyaburi (RMUTT), Thailand, into a single route (Route P). The existing routes were first simulated using observed stop-level boarding data. Their road segments were then merged into one directed network, and the stop sequence with the lowest weighted sum of distance and simulation-derived waiting cost was found exactly using Held–Karp dynamic programming. Route P was evaluated against the existing routes over 50 simulation replications. In the simulation, Route P served 801 passenger trips per week, 6.2–7.5% more than either existing route, with a shorter average trip time (16.27 min, compared with 18.58–18.80 min) and fewer buses in the system. Estimated energy consumption fell to 1.15 kWh per trip, 10.2–11.4% lower than on the existing routes, and the electricity cost per passenger trip fell to 0.0567 USD, 17.3–33.4% lower. Because the energy model is simplified, these estimates are best interpreted as a comparison between routes. The results show that data-driven route consolidation can reduce the operating effort and energy use of a low-demand campus shuttle. The procedure can be reused by other universities and operators of small electric shuttle fleets to screen route consolidation options before implementation, and it could be extended with real-time demand data and adaptive scheduling.