PILLIONPAL – Smart Ride Sharing Platform

This paper introduces a dynamic pricing-based public bike pooling platform tailored for college student transportation. Unlike existing ride-sharing platforms, which rely on static pricing models, our system adjusts pricing dynamically based on demand, supply, and time of day, ensuring equitable access and optimized resource distribution. The platform addresses the unique needs of students navigating campus environments, offering affordable and flexible ride options. Our approach integrates user behavior analysis and historical trip patterns to predict demand fluctuations. This predictive capability allows the system to encourage pooling at peak times and ensures bike availability during off-peak periods. By doing so, our platform not only enhances student mobility but also reduces operational inefficiencies. To validate our model, we conducted a study using simulated campus trip data. Results demonstrate improved cost-efficiency and increased bike utilization compared to static pricing models. In summary, this dynamic platform fills a gap in current bike-sharing services, providing a flexible and fair solution for college campuses. Our work sets the foundation for smarter, demand-responsive transportation in student communities.