Title: Lidar-based road terrain recognition for passenger vehicles

Authors: Shifeng Wang; Sarath Kodagoda; Lei Shi; Ning Xu

Addresses: National Demonstration Center for Experimental Opto-Electronic Engineering Education, School of Opto-Electronic Engineering, Changchun University of Science and Technology, Changchun, 130022, China ' Centre for Autonomous Systems, University of Technology Sydney, Ultimo 2007, Australia ' Centre for Autonomous Systems, University of Technology Sydney, Ultimo 2007, Australia ' School of Opto-Electronic Engineering, Changchun University of Science and Technology, Changchun 130022, China

Abstract: The road terrain type is important information about a passenger vehicle's surroundings. It suggests an appropriate control algorithm and driving strategy. In this paper, a Lidar sensor is employed to reconstruct the road surface and extract features for terrain classification. The experiment vehicle was driven on four specific road terrains at a variety of speeds. The speed dependency and the effect of using principal component analysis were investigated. The simulation experimental results show that this Lidar sensor-based approach is feasible and robust for passenger vehicles in a range of outdoor scenarios.

Keywords: terrain recognition; feature extraction; classification; machine learning; passenger vehicles.

DOI: 10.1504/IJVD.2017.085455

International Journal of Vehicle Design, 2017 Vol.74 No.2, pp.153 - 165

Accepted: 15 Mar 2017
Published online: 26 Jul 2017 *

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