Document Type
Journal Article
Publisher
Hindawi Publishing Corporation
Faculty
Faculty of Computing, Health and Science
School
School of Engineering / Centre for Communications Engineering Research
RAS ID
14784
Abstract
A novel lane detection technique using adaptive line segment and river flow method is proposed in this paper to estimate driving lane edges. A Kalman filtering-based B-spline tracking model is also presented to quickly predict lane boundaries in consecutive frames. Firstly, sky region and road shadows are removed by applying a regional dividing method and road region analysis, respectively. Next, the change of lane orientation is monitored in order to define an adaptive line segment separating the region into near and far fields. In the near field, a 1D Hough transform is used to approximate a pair of lane boundaries. Subsequently, river flow method is applied to obtain lane curvature in the far field. Once the lane boundaries are detected, a B-spline mathematical model is updated using a Kalman filter to continuously track the road edges. Simulation results show that the proposed lane detection and tracking method has good performance with low complexity.
DOI
10.1155/2012/465819
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.
Comments
Lim, K., Seng, K., & Ang, L. K. (2012). River flow lane detection and Kalman filtering-based B-spline lane tracking. International Journal of Vehicular Technology, 2012(1), art. no. 465819 . Available here