Advances in lane marking detection algorithms for all-weather conditions
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 advance...
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| Veröffentlicht in: | International journal of electrical and computer engineering (Malacca, Malacca) Jg. 11; H. 4; S. 3365 |
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| Hauptverfasser: | , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Yogyakarta
IAES Institute of Advanced Engineering and Science
01.08.2021
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| Schlagworte: | |
| ISSN: | 2088-8708, 2722-2578, 2088-8708 |
| Online-Zugang: | Volltext |
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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. |
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| AbstractList | 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. |
| Author | Besar, Rosli Md Sani, Zamani Syahali, Syabeela Daud, Atiqullah Mohamed Ab Ghani, Hadhrami Kamaruddin, Mohd Nazeri Martin, Aerun |
| Author_xml | – sequence: 1 givenname: Hadhrami surname: Ab Ghani fullname: Ab Ghani, Hadhrami – sequence: 2 givenname: Rosli surname: Besar fullname: Besar, Rosli – sequence: 3 givenname: Zamani surname: Md Sani fullname: Md Sani, Zamani – sequence: 4 givenname: Mohd Nazeri surname: Kamaruddin fullname: Kamaruddin, Mohd Nazeri – sequence: 5 givenname: Syabeela surname: Syahali fullname: Syahali, Syabeela – sequence: 6 givenname: Atiqullah Mohamed surname: Daud fullname: Daud, Atiqullah Mohamed – sequence: 7 givenname: Aerun surname: Martin fullname: Martin, Aerun |
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| Copyright | Copyright IAES Institute of Advanced Engineering and Science Aug 2021 |
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| DOI | 10.11591/ijece.v11i4.pp3365-3373 |
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| Snippet | 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... |
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| StartPage | 3365 |
| SubjectTerms | Advanced driver assistance systems Algorithms Fog Haze Intelligent transportation systems Markers Marking Traffic congestion Weather |
| Title | Advances in lane marking detection algorithms for all-weather conditions |
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