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Sensors 2017, 17(11), 2475; https://doi.org/10.3390/s17112475

Road Lane Detection Robust to Shadows Based on a Fuzzy System Using a Visible Light Camera Sensor

Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea
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Received: 22 August 2017 / Revised: 21 October 2017 / Accepted: 25 October 2017 / Published: 28 October 2017
(This article belongs to the Special Issue Mechatronic Systems for Automatic Vehicles)

Abstract

Recently, autonomous vehicles, particularly self-driving cars, have received significant attention owing to rapid advancements in sensor and computation technologies. In addition to traffic sign recognition, road lane detection is one of the most important factors used in lane departure warning systems and autonomous vehicles for maintaining the safety of semi-autonomous and fully autonomous systems. Unlike traffic signs, road lanes are easily damaged by both internal and external factors such as road quality, occlusion (traffic on the road), weather conditions, and illumination (shadows from objects such as cars, trees, and buildings). Obtaining clear road lane markings for recognition processing is a difficult challenge. Therefore, we propose a method to overcome various illumination problems, particularly severe shadows, by using fuzzy system and line segment detector algorithms to obtain better results for detecting road lanes by a visible light camera sensor. Experimental results from three open databases, Caltech dataset, Santiago Lanes dataset (SLD), and Road Marking dataset, showed that our method outperformed conventional lane detection methods. View Full-Text
Keywords: road lane detection; shadows; fuzzy system; line segment detector road lane detection; shadows; fuzzy system; line segment detector
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Hoang, T.M.; Baek, N.R.; Cho, S.W.; Kim, K.W.; Park, K.R. Road Lane Detection Robust to Shadows Based on a Fuzzy System Using a Visible Light Camera Sensor. Sensors 2017, 17, 2475.

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