Multi-rider ridesharing stable matching optimization

Abstract

The rapid growth of private car ownership has led to significant issues such as traffic congestion and environmental pollution. Ridesharing has emerged as a promising solution to alleviate the negative impacts associated with private car usage. This paper focuses on the stability of ridesharing systems and establishes a single-driver multiple-rider ridesharing matching model. To solve this model, a filtering algorithm for the pre-matching set and a fast-solving algorithm for stable matching scheme are proposed. Furthermore, we introduce the concept of subsidy distance upper limit into the ridesharing system. Remarkably, our findings indicate that with a limit of 0.1km, the distance saved generated by the subsidy amounts to 560.5% of the total subsidy. To validate our approach, we simulate ridesharing demand data using real taxi data, and design computational experiments to prove the computational efficiency of the filtering algorithm and fast-solving algorithm. The impact of various parameters on ridesharing systems is also explored.