Citation

Wong, Man Kiat and Connie, Tee and Goh, Michael Kah Ong and Wong, Li Pei and Teh, Pin Shen and Choo, Ai Ling (2022) A visual approach towards forward collision warning for autonomous vehicles on Malaysian public roads. F1000Research, 10. p. 928. ISSN 2046-1402

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Abstract

Autonomous vehicles are important in smart transportation. Although exciting progress has been made, it remains challenging to design a safety mechanism for autonomous vehicles despite uncertainties and obstacles that occur dynamically on the road. Collision detection and avoidance are indispensable for a reliable decision-making module in autonomous driving. Methods: This study presents a robust approach for forward collision warning using vision data for autonomous vehicles on Malaysian public roads. The proposed architecture combines environment perception and lane localization to define a safe driving region for the ego vehicle. If potential risks are detected in the safe driving region, a warning will be triggered. The early warning is important to help avoid rear-end collision. Besides, an adaptive lane localization method that considers geometrical structure of the road is presented to deal with different road types. Results: Precision scores of mean average precision (mAP) 0.5, mAP 0.95 and recall of 0.14, 0.06979 and 0.6356 were found in this study. Conclusions: Experimental results have validated the effectiveness of the proposed approach under different lighting and environmental conditions.

Item Type:	Article
Uncontrolled Keywords:	Object recognition, Forward Collision Warning, Lane detection, Autonomous vehicles, Computer Vision
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	06 Apr 2022 01:43
Last Modified:	06 Apr 2022 01:43
URII:	http://shdl.mmu.edu.my/id/eprint/10035

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