Sensors & Transducers Journal
(ISSN 1726- 5479)
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205.767 |
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(ISSN 1726- 5479) |
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Sensors & Transducers Journal 2010 Sensors & Transducers Journal 2009 Sensors & Transducers Journal 2008 Sensors & Transducers Journal 2007 2000-2002 S&T e-Digest Contents
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Vol. 132, Issue 9, September 2011, pp.122-135
Computer Vision Based Smart Lane Departure Warning System for Vehicle Dynamics ControlAmbarish G. Mohapatra Applied Electronics and Instrumentation Department, Silicon Institute of Technology, Silicon Hills, Patia, Bhubaneswar-751024, Orissa-India Tel.: 9776015060 / 9658043690 E-mail: ambarish.mohapatra@silicon.ac.in
Received: 20 July 2011 /Accepted: 19 September 2011 /Published: 27 September 2011 |
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Abstract: Collision Avoidance System solves many problems caused by traffic congestion worldwide and a synergy of new information technologies for simulation, real-time control and communications networks. The above system is characterized as an intelligent vehicle system. Traffic congestion has been increasing world-wide as a result of increased motorization, urbanization, population growth and changes in population density. Congestion reduces utilization of the transportation infrastructure and increases travel time, air pollution, fuel consumption and most importantly traffic accidents. The main objective of this work is to develop a machine vision system for lane departure detection and warning to measure the lane related parameters such as heading angle, lateral deviation, yaw rate and sideslip angle from the road scene image using standard image processing technique that can be used for automation of steering a motor vehicle. The exact position of the steering wheel can be monitored using a steering wheel sensor. This core part of this work is based on Hough transformation based edge detection technique for the detection of lane departure parameters. The prototype designed for this work has been tested in a running vehicle for the monitoring of real-time lane related parameters.
Keywords: Collision avoidance system, Machine vision, Image processing, Hough transformation, Yaw rate, Heading angle, Sideslip angle, Steering wheel sensor
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