Innovative lane detection method to increase the accuracy of lane departure warning system
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Innovative lane detection method to increase the accuracy of lane departure warning system Ting Yau Teo 1 & Ricky Sutopo 1 & Joanne Mun-Yee Lim 1
& KokSheik Wong
2
Received: 21 October 2019 / Revised: 30 August 2020 / Accepted: 2 September 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
Lane departure warning is one important feature in Advanced Driver Assistance Systems (ADAS), which aims to improve overall safety on the road. However, challenges such as inconsistent shadows and fading lane markings often plague the road surface and cause the lane detection system to produce false warnings. Users are aggravated by the warning and tend to disable this safety feature. This paper proposes an efficient Gabor filteringbased lane detection method to overcome the aforementioned conditions and improves the accuracy of lane departure warning system. Furthermore, it serves as a cost-effective solution to a lane departure warning problem, allowing it to be widely deployed. It is heuristically found that lane marking has a general directional property, which can be further enhanced by Gabor filter while suppressing inconsistent road shadows and road markers. Enhanced lane markings are then subjected to adaptive canny edge detection to extract distinct edge markings. Lastly, Hough transformation is applied to label the correct lane candidates on the road surface. Furthermore, we generate a dataset of Malaysia road with various driving conditions. As a proof of concept, a lane departure warning system is built based on the proposed lane detection method, which is able to achieve an accuracy of 93.67% for lane detection and 95.24% for lane departure warning tested on our challenging dataset. The codes are implemented on Raspberry pi 3B and installed in a vehicle for real-time application. The codes are multithreaded and found to achieve a desirable frame speed of 20 fps at 75% CPU utilization. Keywords Lane departure warning . ADAS . Gabor filter . Hough transformation . Real-time application
* Joanne Mun-Yee Lim [email protected]
1
School of Engineering, Monash University Malaysia, Jalan Lagoon Selatan, Bandar Sunway, 47500 Subang Jaya, Selangor, Malaysia
2
School of Information Technology, Monash University Malaysia, Jalan Lagoon Selatan, Bandar Sunway, 47500 Subang Jaya, Selangor, Malaysia
Multimedia Tools and Applications
1 Introduction One of the major causes of fatal accident on the road is due to the improper operations performed by drivers, which are caused by misjudgement, drowsiness and inattention to the surrounding vehicles. Within Malaysia, which is a relatively small country, 548,598 cases of accident were reported in year 2018, while many are not reported. To ensure better safety and pleasant condition on the road, many innovations are put forward as means to reduce accidents, including lane departure warning system, collision avoidance system, autonomous cruise control system, to name a few. However, these (mostly sensor-based) technologies come at steep prices,
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