The invention provides a method and device for implementing personalized path planning through reinforcement learning. The method and device correspond to the personalized optimal strategy of the target driver, and the personalized optimal strategy is obtained by adjusting the public optimal strategy established based on the public criteria of automatic driving. The method includes steps of: a learning device performing a process of instructing an adjustment reward network to generate first adjustment rewards, by referring to the information on actual actions and actual circumstance vectors indriving trajectories, a process of instructing a common reward module to generate first common rewards by referring to the actual actions and the actual circumstance vectors, and a process of instructing an estimation network to generate actual prospective values by referring to the actual circumstance vectors; and the learning device instructing a first loss layer to generate an adjustment reward and to perform back propagation to learn parameters of the adjustment reward network.
METHOD AND DEVICE for implementing personalized path planning through reinforcement learning