Optimizing Campus Bus Operations: A Case Study in Sustainable Transport Automation

Abstract

This paper presents a data-driven approach to optimize campus bus operations at Universiti Teknologi MARA (UiTM) Shah Alam in support of its green campus initiative. The study evaluates and compares three operational scenarios: the original 35-bus system (Scenario A), a downsized 10-bus system (Scenario B) and a proposed optimized configuration using the same 10-bus fleet. Real-case data including route structures, stop locations and timetables were collected and simulated in MATLAB. Then using geospatial mapping and route modeling techniques integrated with the Haversine distance formula to design network of eight optimized routes. The performance of each scenario was assessed based on metrics such as passenger capacity, wait time, fuel consumption and total travel distance. Results show that the optimized route configuration achieves a 67.5% reduction in both fuel use and travel distance and a 64.4% reduction in bus operating hours compared to Scenario A. It also improves passenger capacity by 80.4% compared to Scenario B (from 11,049 to 20,280 passengers per day), showing the effectiveness of strategic route restructuring. From the study, it highlights the potential of automated route planning and simulation tools in achieving more sustainable and efficient institutional transport systems.