Abstract
Lane detection is a fundamental aspect of most current advanced driver assistance systems (ADASs). A large number of existing results focus on the study of vision-based lane detection methods due to the extensive knowledge background and the low-cost of camera devices. In this paper, previous vision based lane detection studies are reviewed in terms of three aspects, which are lane detection algorithms, integration, and evaluation methods. Next, considering the inevitable limitations that exist in the camera-based lane detection system, the system integration methodologies for constructing more robust detection systems are reviewed and analyzed. Road markings embody the rules of the road whilst capturing the upcoming road layout. These rules are diligently studied and applied to driving situations by human drivers who have read Highway Traffic driving manuals (road marking interpretation). An autonomous vehicle must however be taught to read the road, as a human might. This paper addresses the problem of automatically detecting lane line marking.
Metadata
Item Type: | Thesis (Masters) |
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Creators: | Creators Email / ID Num. Baldeh, Mamadou 2017719515 |
Contributors: | Contribution Name Email / ID Num. Thesis advisor Mohamad Zain, Jasni UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Computer software > Application software |
Divisions: | Universiti Teknologi MARA, Shah Alam > Faculty of Computer and Mathematical Sciences |
Programme: | Master of Science |
Keywords: | Advanced driver assistance systems (ADASs), traffic driving manuals (road marking interpretation), detecting lane line marking |
Date: | 2020 |
URI: | https://ir.uitm.edu.my/id/eprint/109505 |
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