Vehicle Relocation

Vehicle relocation, crucial for optimizing ride-hailing services and other transportation systems, aims to strategically reposition idle vehicles to better meet anticipated demand and improve overall efficiency. Current research focuses on developing sophisticated algorithms, including model-based modular approaches and deep reinforcement learning, to personalize relocation strategies, considering driver preferences and optimizing for both supply-demand balance and revenue maximization. These advancements are improving service quality and driver satisfaction while addressing computational challenges inherent in real-time decision-making for large-scale systems. Furthermore, research extends beyond ride-hailing to applications like visual localization in challenging environments such as parking lots, where vehicle relocation impacts the accuracy of image-based positioning systems.