Ride-sharing across university campuses: Matching user demands and reducing the carbon footprint

Universities with geographically dispersed campuses face significant commuting-related carbon emissions due to reliance on single-occupancy vehicles. To address this challenge, this study develops a route-similarity–based ride-sharing system tailored for university staff, designed to optimize inter-campus travel while supporting institutional sustainability goals. The proposed mobile platform employs a route-matching algorithm that calculates spatial proximity between driver and passenger trajectories using the Haversine formula, thereby identifying highly compatible travel pairs and generating shared itineraries to minimize redundant trips. Implemented through a client–server architecture with an Android interface, a Spring Boot backend, and a MySQL geospatial database, the prototype demonstrates efficient route pairing within milliseconds. Beyond its environmental impact, the system also promotes informal social interaction among academic staff, fostering collegial engagement and community building within the university. This work contributes a scalable socio-technical framework that integrates spatial computation with sustainable mobility management, offering a replicable model for reducing emissions and enhancing social connectivity in academic environments.