Abstract
With the Hough transform and region of interest, how to improve the processing time of high-speed driving is being actively investigated. This study proposes a road lane detection algorithm based on expressway driving videos through a computer vision-based image processing system without using sensors. The proposed method detects straight lines that are estimated to be lanes using the Hough transform. When lanes are detected from actual images, the scope of left and right lanes is limited to reduce computational load. Extensive simulation results are given to show the effects of Hough transform method for high speed driving and region of interest for processing time on actual expressways.
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Acknowledgements
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2017R1C1B5017556).
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Park, H. (2019). Robust Road Lane Detection for High Speed Driving of Autonomous Vehicles. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds) Web, Artificial Intelligence and Network Applications. WAINA 2019. Advances in Intelligent Systems and Computing, vol 927. Springer, Cham. https://doi.org/10.1007/978-3-030-15035-8_24
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DOI: https://doi.org/10.1007/978-3-030-15035-8_24
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