Advances in lane marking detection algorithms for all-weather conditions

Ab. Ghani, Hadhrami and Besar, Rosli and Md. Sani, Zamani and Kamaruddin, Mohd Nazeri and Syahali, Syabeela and Mohamed Daud, Atiqullah and Martin, Aerun (2021) Advances in lane marking detection algorithms for all-weather conditions. International Journal of Electrical and Computer Engineering, 11 (4). pp. 3365-3373. ISSN 2088-8708

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Abstract

Driving vehicles in all-weather conditions is challenging as the lane markers tend to be unclear to the drivers for detecting the lanes. Moreover, the vehicles will move slower hence increasing the road traffic congestion which causes difficulties in detecting the lane markers especially for advanced driving assistance systems (ADAS). Therefore, this paper conducts a thorough review on vision-based lane marking detection algorithms developed for all-weather conditions. The review methodology consists of two major areas, which are a review on the general system models employed in the lane marking detection algorithms and a review on the types of weather conditions considered for the algorithms. Throughout the review process, it is observed that the lane marking detection algorithms in literature have mostly considered weather conditions such as fog, rain, haze and snow. A new contour-angle method has also been proposed for lane marker detection. Most of the research work focus on lane detection, but the classification of the types of lane markers remains a significant research gap that is worth to be addressed for ADAS and intelligent transport systems.

Item Type: Article
Uncontrolled Keywords: All-weather conditions, Image pre-processing, Lane detection, Lane marking
Divisions: Faculty of Electrical Engineering
Depositing User: Sabariah Ismail
Date Deposited: 11 Apr 2022 11:58
Last Modified: 11 Apr 2022 11:58
URI: http://eprints.utem.edu.my/id/eprint/25810
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