The invention discloses an intelligent vehicle GPU parallel acceleration trajectory planning method, and the method comprises the steps of obtaining a real-time perception obstacle grid graph, a global reference path, intelligent vehicle real-time GPS information and an upper layer decision instruction at a CPU end, carrying out the sampling along the reference path, and obtaining a series of target sampling terminals; at the GPU end, obtaining a sampling terminal sequence, the real-time state information of an intelligent vehicle, the perception environment grids and the historical frame planning track parameters, designing a track generation kernel function, generating an intelligent vehicle stable tracking track connected with an initial state and a terminal state for each target sampling terminal, designing a track evaluation kernel function, and evaluating the cost of each track; and returning the track data to the CPU end, selecting an optimal track and matching the optimal trackwith the speed value, obtaining a track planning result and transmitting the track planning result to the control execution mechanism. The method is used for improving the real-time planning efficiency of the track of the intelligent vehicle, achieving the purposes of efficiently generating a large number of tracks in real time and further improving the track planning result.