Enhancing shared mobility via connected vehicle-driven dispatch and dynamic pricing

The rapid advancement of connected vehicle technology has revolutionized the landscape of shared mobility systems, significantly enhancing road capacity, operational efficiency, and service levels in regional traffic. This evolution addresses critical societal challenges, including traffic congestion, environmental pollution, and energy consumption. The integration of connected vehicle technology into the shared mobility domain offers unprecedented opportunities for improving dispatching accuracy and reducing both labor costs and uncertainties associated with human factors. This study presents a pioneering model for connected mobility-on-demand services, emphasizing dynamic ride-sharing dispatch and pricing strategies. In the first step, we introduce a supply-demand function to delineate the interplay between service pricing and user demand, alongside the incentivization for shared vehicle participation. Subsequently, a novel model is developed to synergize platform-based pricing with dynamic regional vehicle dispatching, incorporating the supply-demand dynamics and real-time dispatch optimization. An innovative optimization algorithm, grounded in approximate dynamic programming, underpins our model, showcasing its efficacy in balancing regional supply-demand discrepancies and elevating vehicle-passenger matching rates. The findings underscore the transformative potential of connected vehicles in refining transportation systems through smart, connected solutions for sustainable and efficient urban mobility.