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In order to solve the limitation problems of traditional artificial potential field algorithm in lane changing trajectory planning of driverless vehicle, a lane changing trajectory planning algorithm is proposed based on potential energy reconstruction and artificial potential field (PER-APF) algorithm. Firstly, the road boundary constraints with repulsive force differentiation and lane changing trajectory planning model with multiple constraints are established. By judging the distance between obstacle vehicles and road edges, to ensure the safety and effectiveness of vehicle lane changing process. In addition, with constructed virtual circular area and reconstructed physical potential energy field, the PER-APF algorithm can solve the problem of unreachable target and local optimization effectively. The simulation results show that the PER-APF algorithm can plan a reasonable lane change trajectory for driverless vehicle quickly and effectively.