Dispatch Strategy for Multimodal Online Ride-Hailing Services System Considering Walking Incentive

The increasing popularity of online ride-hailing services can significantly improve trip efficiency and cost savings. This paper explores a multimodal service system that integrates individual services with ride-sharing services. The impact of passengers’ walking distance and detour acceptability on matching efficiency is analyzed in depth. A walking incentive is introduced, and the travel trajectories are reconfigured. Trajectory similarity and matching probability are quantified as indicators for identifying the sharing probability. Focused on a multimodal service system, the travel costs of passengers and vehicles are studied following the introduction of a walking incentive. With matching efficiency as the primary objective, a dispatch strategy optimization model for the multimodal service system is established, and the Kuhn-Munkres algorithm is applied to solve the model. The actual travel demand for Xi’an, Shaanxi Province, China, is taken as an example, and the model conclusions are validated using simulation methods. The findings reveal that the introduction of a walking incentive can enhance overall efficiency and passengers’ satisfaction by reducing operational costs and improving resource allocation. Numerical experiments on a real case study reveal that introducing a walking incentive can increase passengers’ matching rate by 9% and drivers’ matching rate by 3%, reduce passengers’ waiting time by 13% and average detour distance by 7%, and save travel costs by 30% per passenger. When a walking incentive is introduced, the probabilities of ride-sharing for two-, three-, and four-passenger vehicles increase by 3%, 4%, and 4%, respectively. Sensitivity analysis results for different scenarios demonstrate that higher acceptable walking distance increases matching success rates for drivers and passengers, and suggests trade-offs between average waiting time and detour distances. This paper further highlights the importance of flexibility in the ride-sharing mechanism, emphasizing the adaptability of order dispatch optimizing for the ride-hailing platform.