Abstract
To improve the real-time performance and detection rate of a Lane Detection and Reconstruction (LDR) system, an extended-search-based lane detection method and a Bézier curve-based lane reconstruction algorithm are proposed in this paper. The extended-search-based lane detection method is designed to search boundary blocks from the initial position, in an upwards direction and along the lane, with small search areas including continuous search, discontinuous search and bending search in order to detect different lane boundaries. The Bézier curve-based lane reconstruction algorithm is employed to describe a wide range of lane boundary forms with comparatively simple expressions. In addition, two Bézier curves are adopted to reconstruct the lanes' outer boundaries with large curvature variation. The lane detection and reconstruction algorithm - including initial-blocks' determining, extended search, binarization processing and lane boundaries' fitting in different scenarios - is verified in road tests. The results show that this algorithm is robust against different shadows and illumination variations; the average processing time per frame is 13 ms. Significantly, it presents an 88.6% high-detection rate on curved lanes with large or variable curvatures, where the accident rate is higher than that of straight lanes.
| Original language | English |
|---|---|
| Article number | 132 |
| Journal | International Journal of Advanced Robotic Systems |
| Volume | 12 |
| Issue number | 9 |
| DOIs | |
| State | Published - 28 Sep 2015 |
Keywords
- Bézier Curve
- Extended Search
- Intelligent Vehicle
- Lane Detection
- Lane Reconstruction
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