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     Research Journal of Applied Sciences, Engineering and Technology


The Research of the Lane Detection Algorithm Base on Vision Sensor

Li Sha Sha
College of Automation, Harbin Engineering University, Harbin, Heilongjiang 150001, China
Research Journal of Applied Sciences, Engineering and Technology  2013  4:642-646
http://dx.doi.org/10.19026/rjaset.6.4175  |  © The Author(s) 2013
Received: September 03, 2012  |  Accepted: October 09, 2012  |  Published: June 20, 2013

Abstract

The intelligent vehicle is an important area country in recent years of painstaking research in Intelligent Transportation System, which become the focus of the study, based on the visual structure of the road environment recognition. Aiming at the robust and real time problems of lane detection in the visual navigation system of intelligent vehicles, a robust lane detection method is proposed for the structured road. It can provide for intelligent vehicle automatically to maintain lane and changing lanes traveling lane information necessary to make smart vehicle to achieve a smooth, safe driving. Due to the complexity of the road itself, the complexity of the road image, Therefore, the pre-road established certain assumptions and these assumptions and the detection algorithm is combined to further improve the algorithm efficiency. Simulation test of the collected road images results show that the lane detection method designed in this study is stable enough to show the lane Position for engineering application not matter in good or poor illumination road condition.

Keywords:

Hough Transform, lane detection, lane tracking,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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