Ride Hailing Service

Ride-hailing services are a rapidly evolving transportation paradigm, with research primarily focused on optimizing operational efficiency and equity. Current efforts leverage machine learning, particularly deep learning models like convolutional neural networks and transformers, to improve demand prediction, driver-passenger matching, and dynamic pricing strategies, often incorporating spatiotemporal factors and multi-task learning approaches. These advancements aim to enhance platform revenue, order fulfillment rates, and resource utilization while addressing challenges like equitable access to service for underserved populations. The resulting improvements in efficiency and accessibility have significant implications for urban planning, transportation policy, and the broader societal impact of on-demand mobility.