Int. J. of Vehicle Autonomous Systems   »   2017 Vol.13, No.4

 

 

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

 

Int. J. of Vehicle Autonomous Systems, 2017 Vol.13, No.4, pp.330 - 339

 

Date of acceptance: 05 Mar 2017
Available online: 03 Oct 2017

 

 

Editors Full text accessAccess for SubscribersPurchase this articleComment on this article