DESIGN AND SIMULATION OF A LOCATION-AWARE INTELLIGENT TRANSPORT SYSTEM FOR CAMPUS PASSENGER PICKUP: A CASE STUDY OF FUTA, NIGERIA

Transportation inefficiencies within semi-urban academic environments often result in delays, poor route coordination, and underutilization of available vehicles. These challenges are particularly evident in campus communities where passenger demand varies significantly throughout the day. This study presents the design and simulation of a location-aware intelligent transportation system (ITS) for passenger pickup, using the Federal University of Technology, Akure (FUTA), Nigeria, as a case study. The proposed system leverages real-time location intelligence to automate passenger–driver matching based on route proximity, vehicle seat availability, and estimated time of arrival (ETA). The system was implemented as a responsive web-based application integrating the Google Maps API for route visualization, movement tracking, and ETA computation. A modular architecture comprising user, driver, and administrator dashboards supports role-based access, automated booking, and transport oversight. Simulation-based evaluation shows that the proposed system achieves over 95% shuttle assignment accuracy, improves booking success for group passengers, and reduces average passenger waiting time by approximately 25–35% when compared with a baseline manual dispatch model. Prototype testing further indicates high usability, scalability, and operational efficiency. The study concludes that location-aware intelligent transportation systems can significantly enhance campus mobility and provides a foundation for future integration of live GPS feeds, mobile payments, and predictive analytics.