Abstract:

The traditional A* algorithm was modified in terms of environment modeling and cost function to reduce energy consumption and improve lateral driving stability in off-road path planning for autonomous vehicles. The Digital Elevation Model (DEM) data were processed using the Kriging interpolation and the slope calculation. A vehicle travers ability map was generated based on vehicle performances. Pitch and roll influence factors were added into the cost function of the A* algorithm. The proposed algorithm, the traditional A* algorithm, and the HA* algorithm (Height-Aware A* algorithm) were simulated and compared on the real environment maps. The results show that the proposed algorithm increases path length by up to 7.3% but reduces the energy consumption by up to 10.1% compared with the traditional A* and the HA* algorithms in off-road environments. The driving pitch angle is less than 40% for the general-performance vehicles, with being lower than 60% for the high-performance vehicles; And the roll angle of both types of vehicles is lower than 36%. Therefore, the proposed algorithm reduces energy consumption and improves lateral driving stability.

Key words: autonomous vehicles, path planning, off-road environment, improved A* algorithm