International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064

Downloads: 103 | Views: 172

Research Paper | Computer Science & Engineering | India | Volume 3 Issue 6, June 2014

Video Analysis to Detect and Track Road Ahead for Safety

Laxmi [117] | Dr. Neelam Srivastava [2]

Abstract: Detecting the road area and ego-lane ahead of a vehicle is central to modern driver assistance systems. While lane-detection on well-marked roads is already available in modern vehicles; finding the boundaries of unmarked or weakly marked roads and lanes as they appear in inner-city and rural environments remains an unsolved problem due to the high variability in scene layout and illumination conditions; amongst others. While recent years have witnessed great interest in this subject; to date no commonly agreed upon benchmark exists; rendering a fair comparison amongst methods difficult. In this paper; we introduce a novel open-access dataset and benchmark for road area and ego-lane. detection. Autonomous vehicles (AV) are not a new concept. They have been proposed for the longterm goal of having vehicles driving autonomously in an unknown environment for the purpose of human safety; convenience; and ease of life; both in civilian and military applications. In day-to-day life; humans take such navigational capabilities for granted. The human brain achieves all this simultaneously using mostly the sense of vision. That being one of the strong motivation behind vision based control; it is also desirable to use computer vision systems to achieve low cost; low maintenance autonomous vehicle navigation. Proposed is a vision solution based on accumulator based parametric transforms to detect navigable regions in the urban environment. The novel accumulator voting scheme is called Parametric Transform for Lanes (PTL) ; which enables detection of multiple lanes and variations of lanes such as exits and intersections possible concurrently. Other than being robust to shadows; invariant to color; width and texture of the road; this PTL is based on a control-motivated philosophy. Thus; this dissertation proposes a novel total image-based control solution to the autonomous vehicle control problem; called Predictive Control in Image Plane (PCIP). PTL and PCIP together inherently support control for multiple operations; such as lane following; lane changing; turning at intersections; etc.

Keywords: Road, traffic, vision, cmarea, lane parameters, parametric transform

Edition: Volume 3 Issue 6, June 2014,

Pages: 1295 - 1299

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