Three dimensional path planning for flying car based on improved A* algorithm and Bezier curve fusion

Abstract

Flying car is a new type of vehicle with high obstacle avoidance ability for urban air traffic and future smart travel. In order to plan feasible paths for flying cars in urban environments, a three dimensional path planning strategy for flying cars based on the fusion of improved A* algorithm and Bezier curves is proposed. Firstly, the search neighborhood of the A* algorithm is improved, and the node expansion is carried out by using the ground mode 9 neighborhood and the low-altitude flight mode 10 neighborhood to quickly obtain feasible path options. Secondly, the energy consumption, time and mode switching loss cost of different motion processes are considered in the heuristic function to achieve unified planning of motion paths and motion modes. Finally, the path is smoothed using piecewise Bezier curves according to the planned path. The results show that in complex maps, compared with traditional vehicles that only consider energy consumption, this strategy effectively reduces the path length by 94.5 m and reduces the weighted cost by 33.1%. Compared with the strategy that comprehensively weighs energy consumption and time, the path length is reduced by 4.31 m and the weighted cost is reduced by 13.6%.