Global path planning for autonomous vehicles in off-road environment via an A-star algorithm

Abstract

In order to solve the problem of global path planning for autonomous vehicles in off-road environment, an improved A-star path-searching algorithm considering the vehicle powertrain and fuel economy performance is proposed in this paper. First, we discuss the digital elevation model (DEM) map adopted to describe off-road earth surface generally. Then, we define three important concepts regarding path planners on the basis of the DEM map. Second, we design a novel comprehensive cost function for A-star algorithm with shorter Euclidean distance and less fuel consumption. At last, the algorithm is simulated on a DEM map through several different missions. The simulation results show that the proposed algorithm is effective and robust in finding global path in complex terrains.