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

Authors: Qinghe Liu; Lijun Zhao; Zhibin Tan; Wen Chen

Addresses: School of Automotive Engineering, Harbin Institute of Technology, Weihai, Shandong, China ' School of Automotive Engineering, Harbin Institute of Technology, Weihai, Shandong, China ' Division of Engineering and Technology, Wayne State University, Detroit, MI, USA ' Division of Engineering and Technology, Wayne State University, Detroit, MI, USA

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.

Keywords: A-star algorithms; path planning; autonomous vehicles; DEM.

DOI: 10.1504/IJVAS.2017.10008214

International Journal of Vehicle Autonomous Systems, 2017 Vol.13 No.4, pp.330 - 339

Received: 02 May 2016
Accepted: 05 Mar 2017

Published online: 03 Oct 2017 *

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