Unmanned Vehicle Trajectory Tracking by Neural Networks

Samira Chouraqui and Boumediene Selma

Department of Computer Sciences, University of Sciences and Technologies of Oran USTO’MB, Algeria

Abstract: This paper, deals with a path planning and intelligent control of an autonomous vehicle which should move safely in its road partially structured. This road, involves a number of obstacles like donkey, traffic lights and other vehicles. In this paper, the Neural Networks (NN)-based technique Artificial Neural Network (ANN) is described to solve the motion-planning problem in Unmanned Vehicle (UV) control. This is accomplished by choosing the appropriate inputs/outputs and by carefully training the ANN. The network is supplied with distances of the closest obstacles around the vehicle to imitate what a human driver would see. The output is the acceleration and steering of the vehicle. The network has been trained with a set of strategic input-output. The results show the effectiveness of the technique used, the UV drives around avoiding obstacles.

Keywords: UV, NN, control.

Received March 22, 2013; accepted March 19, 2014