In order to improve the safety of the point-to-point operation of unmanned aerial vehicles(UAV), this paper proposes a low risk path planning strategy. Low risk path planning strategy includes risk assessment and path planning. In the part of risk assessment, the risk value assessment model and risk grade assessment model are established by taking the risk of UAV to pedestrians on the ground as the assessment index, and the risk map is taken as the result to represent the safety degree of UAV operation. In the path planning part, combined with the unique background and characteristics of the risk model, an improved rapidly-exploring random tree* algorithm is proposed. This algorithm uses the strategies of improved collision detection and priority exploration to explore the low-risk path more effectively. Finally, the simulation results show that the low-risk path planning strategy can effectively plan the operation path to avoid the high-risk area. The risk value is reduced by 13.16% compared with the straight-line flight, and the planning time is reduced by 60.63% and 12.20% compared with the contrast algorithm. Therefore, this planning strategy has practical value and can improve the safety of UAV operations.