A unified learning approach for large-scale ride-hailing is described, the approach includes obtaining an offline state value network for predicting a value of a vehicle state, the offline state value network being trained based on a plurality of historical vehicle trajectories; initializing an online state value network and dispatching a plurality of vehicles according to the online state value network for a period of time; training the online state value network based on vehicle states of the plurality of vehicles before and after the dispatching and rewards associated with the dispatching; ensembling the trained online state value network and the offline state value network to obtain an ensembled online state value network; and dispatching the plurality of vehicles according to the ensembled online state value network.