Vehicle Assignment

Vehicle assignment in mobility-on-demand (MoD) systems focuses on optimizing the allocation of passengers to vehicles to minimize operational costs and improve service quality, such as reducing travel times and distances. Current research emphasizes developing and evaluating large-scale algorithms, including optimal assignment methods and reinforcement learning approaches for fleet repositioning, often using real-world datasets to benchmark performance against simpler heuristics like insertion methods. These advancements are crucial for improving the efficiency and scalability of ridesharing services and autonomous mobility systems, impacting both the design of transportation networks and the user experience.