A novel approach for obstacle detection to navigate driverless car in static and dynamic environment using learning technique

Abstract

An intelligent vehicle can detect road obstacle by knowing its environment. In fact, an intelligent vehicle must be able to detect vehicles and the potential obstacles on its path. Advanced driver-assistance systems intend to understand the environment of the vehicle contributing to traffic safety. It has been considered important that intelligent vehicles identify obstacles around a host vehicle and estimate their positions and velocities precisely. In this context, many systems have been designed to deal with obstacle detection in various environments. Radars Huttenlocher (2005), Laser Range Finder Gavrila (1999), Philomin (1999) Stereovision Forsyth (2001), Lowe (2004), Mikolajczyk (2004), Poggio (2000), Porikli (2005), Puzicha (2002) and multisensory fusion are used on structured roads. Several approaches to obstacle detection based on the localization of specific patterns (features such as shape, symmetry, or edges). newlineIn Smola (2002) the stereo matching is used in many applications, like obstacle detection, 3D-reconstruction, autonomous vehicles and augmented reality. The vision-based obstacle detection for the outdoor provides a brief review of the state of the art in vision-based obstacle detection.