Study of Expressway Lane Departure Warning and Navigation System under Different Visibility Conditions

Abstract:

In order to improve the safety of driving under different visibility meteorological conditions on the expressway, this paper analyses the composition and operation principle of the expressway lane departure warning and navigation system based on machine vision. And an effective lane mark identification algorithm suiting for different visibility situations is proposed. Firstly the image contrast between the expressway lane and its background is increased by using histogram equalization technology, improving detecting range of lanes and accuracy. Secondly the edges in the lane directions are detected by utilizing specific Sobel operator. In order to suit for different visibility situations and improve detecting efficiency, the method of maximum classes square error is applied to threshold segmentation. Finally, lane is abstracted according to expressway lane features after image Hough transform. Based on lanes identification, this paper designs a navigation algorithm of driving direction. This algorithm performs driving direction navigation decisions according to two characteristic parameters which are deviation angle and deviation distance. The experimental results indicate that the developed system exhibits good detection performances in recognition reliability and navigation decision. It has proved that this system has high accuracy, large detection range and high practicability.

• Periodical: Applied Mechanics and Materials (Volumes 135-136)
• Pages: 938-943
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.135-136.938
• Online since: October 2011
• Authors: Yong Mei Yang, Nai Quan Sun, Hong Ke Xu
• Keywords: Driving Direction Navigation, Expressway, Lane Mark Identification, Machine Vision, Visibility

References

[1] Han Jiuqiang. Machine vision technology and applications, Higher Education Press. Bei jing, 2009. (in Chinese).

[2] HUANG S S, CHEN C J , HSIAO P Y, et al. On board vision system for lane recognition and front vehicle detection to enhance driver's awareness, IEEE International Conference on Robotics & Automation. New Orleans, LA, USA, 2004, pp.2456-2459.

DOI: 10.1109/robot.2004.1307429

[3] Rafael C. Gonzalez, Richard E. Woods. Digital Image Processing, Publishing House of Electronics Industry. Bei jing, 2003(in Chinese).

[4] Jung C láudio Rosito, Kelber Christian Roberto. A lane departure warning system using lateral offset with uncalibrated camera, IEEE Conference on Intelligent Transportation Systems. Vienna, Austria, 2005, pp.102-107.

DOI: 10.1109/itsc.2005.1520073

[5] CLAUD IO R J , CHR ISTIAN R K. A lane departure warning system based on a linear parabolic lane model, IEEE Intelligent Vehicles Symposium, Parma, Italy, 2004, pp.891-895.

DOI: 10.1109/ivs.2004.1336503

[6] Li Xu, Zhang Weigong. Research on lane departure warning system based on machine vision, Chinese Journal of Scientific Instrument, vol. 29, NO. 7 2008, , pp.1554-1558. (in Chinese).

[7] Zhang Rong, Wang Yong, Yang Rong. Researches on road recognition in landsat TM images, Journal of Remote Sensing, vol9, NO. 2, 2005, pp.220-224. (in Chinese).

[8] Jing xiaojun. Image processing technology and Application, National Defense Industry Press. Bei jing, 2005 (in Chinese).