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Sensors 2012, 12(12), 17168-17185; doi:10.3390/s121217168
Article

PSO Algorithm Particle Filters for Improving the Performance of Lane Detection and Tracking Systems in Difficult Roads

Received: 9 August 2012; in revised form: 7 December 2012 / Accepted: 10 December 2012 / Published: 12 December 2012
(This article belongs to the Section Physical Sensors)
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Abstract: In this paper we propose a robust lane detection and tracking method by combining particle filters with the particle swarm optimization method. This method mainly uses the particle filters to detect and track the local optimum of the lane model in the input image and then seeks the global optimal solution of the lane model by a particle swarm optimization method. The particle filter can effectively complete lane detection and tracking in complicated or variable lane environments. However, the result obtained is usually a local optimal system status rather than the global optimal system status. Thus, the particle swarm optimization method is used to further refine the global optimal system status in all system statuses. Since the particle swarm optimization method is a global optimization algorithm based on iterative computing, it can find the global optimal lane model by simulating the food finding way of fish school or insects under the mutual cooperation of all particles. In verification testing, the test environments included highways and ordinary roads as well as straight and curved lanes, uphill and downhill lanes, lane changes, etc. Our proposed method can complete the lane detection and tracking more accurately and effectively then existing options.
Keywords: driver assistance system; lane departure warning system; lane following system; lane collision warning system; lane model driver assistance system; lane departure warning system; lane following system; lane collision warning system; lane model
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Cheng, W.-C. PSO Algorithm Particle Filters for Improving the Performance of Lane Detection and Tracking Systems in Difficult Roads. Sensors 2012, 12, 17168-17185.

AMA Style

Cheng W-C. PSO Algorithm Particle Filters for Improving the Performance of Lane Detection and Tracking Systems in Difficult Roads. Sensors. 2012; 12(12):17168-17185.

Chicago/Turabian Style

Cheng, Wen-Chang. 2012. "PSO Algorithm Particle Filters for Improving the Performance of Lane Detection and Tracking Systems in Difficult Roads." Sensors 12, no. 12: 17168-17185.



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