Taxi Coordination Service

Taxi coordination services aim to optimize urban transportation by intelligently matching passengers with available taxis, minimizing wait times and improving overall efficiency. Current research focuses on developing sophisticated algorithms, including deep reinforcement learning and heuristic approaches, to address the dynamic nature of this problem and incorporate factors like driver compensation and real-time traffic conditions. Furthermore, research emphasizes privacy-preserving techniques like federated learning to leverage large datasets while protecting sensitive information. These advancements hold significant potential for improving urban mobility and informing transportation planning.