A Real-Time Robust Lane Detection Approach for Autonomous Vehicle Environment

B.-F. Wu, C.-J. Chen, C.-C. Chiu, and T.-C. Lai (Taiwan)


Lane detection, night, inclination, TAIWAN iTS-1, ITS


This paper proposes a real-time lane detection algorithm which provides adaptive region of interesting to reduce computational load and is robust for real road environment, e.g., road inclination, road width calibration. Compared to previous approaches, the flat road assumption is released in our approach so that the result is more close to real road environment. This work has been successfully verified on highway and urban with different velocities 110km/h and 50km/h, respectively, in the real vehicle, TAIWAN iTS-1, which is an experimental car of Taiwan ITS project. The algorithm is also demonstrated on the lanes which are with shadows, texts, crooks, or sheltered by other vehicles for sunny and night environment.

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