UniRides: A Secure Multi-College Carpooling Platform using Microservices and Privacy-Aware Location Matching

Significant barriers to urban college-centered transportation systems are budget challenges of students commuting daily with associated high transportation costs, congested traffic, personal safety concerns and negative environmental impacts. Current ride share services do not have verification processes, thus leading to substantial reliance on continuous (or real-time) global positioning system (GPS) location-based tracking, resulting in privacy threats, decreased user trust, and therefore reduced ridership. Thus, this paper proposes UniRides, a university-focused, multi-university carpool service; through which users authenticate their identity by verification using their university email address (through the university) as well as a one-time password (OTP) when signing into UniRides. Furthermore, UniRides introduces a microservices architecture allowing the system to be implemented with scalability, modularity, and fault isolation. In addition, UniRides actively seeks to promote a privacy-focused paradigm – by limiting the use of location data to pick-up and drop-off, and not utilizing real-time tracking. The experimental analysis and evaluation of the system using simulated data demonstrates high ride-matching rates, low ride-match response times, and increased user trust. As shown through the analysis and evaluation of this study, UniRides has the potential to provide a scalable, privacy conscious transportation solution for college-bound students.