Predictive virtual lane method using relative motions between a vehicle and lanes
- 168 Downloads
We propose a new approach for virtual lane prediction. The main contribution of the proposed method is that the predicted virtual lane can be substituted for lane detection using a camera sensor when the camera image processing fails to detect the lane. The proposed method generates the predicted virtual lane using the relative movement between a vehicle and a lane. To predict the lane, a third-order polynomial function of the longitudinal distance is used as a lane model. Each coefficient of the lane polynomial function at the next sampling time is geometrically calculated using the relative movement of a vehicle, the lanes, the longitudinal velocity and the yaw of the vehicle at the present time. Then, the predictive virtual lane at the next sampling time is obtained without the lane information from the camera sensor at the next sampling time. The proposed method is simple enough that it is suitable for real implementation. The performance of the proposed method was evaluated via experiments with a test vehicle.
KeywordsDriver assistance system kinematics lane detection virtual lane
Unable to display preview. Download preview PDF.
- Y. Wang, E. K. Teoh, and D. Shen, “Lane detection using B-snake,” Proc. Int. Conf. Inf. Intell. Syst., pp. 438–443, 1999.Google Scholar
- S. Zhou, Y. Jiang, J. Xi, J. Gong, G. Xiong, and H. Chen, “A novel lane detection based on geometrical model and Gabor filter,” Proc. IEEE Intell. Vehicles Sysp., pp. 59–64, 2010.Google Scholar
- A. B. Hillel, R. Lerner, D. Levi, and G. Raz, “Recent progress in road and lane detection: a survey,” Mach. Vis. Appl., pp. 1–19, February 2012.Google Scholar
- R. K. Satzoda, S. Suchitra, and T. Srikanthan, “Robust extraction of lane markings using gradient angle histograms and directional signed edges,” Proc. IEEE Intell. Vehicles Sysp., pp. 754–759, 2012.Google Scholar
- H. Yoo, U. Yang, and K. Sohn, “Gradientenhancing conversion for illumination-robust lane detection,” IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, pp. 188–200, 2006.Google Scholar
- S.-H. Lee, Y. O. Lee, B.-A. Kim, and C. C. Chung, “Proximate model predictive control strategy for autonomous vehicle lateral control,” Proc. Amer. Control Conf., pp. 3605–3610, 2012.Google Scholar
- F. Ibrahim, “Geometric based path prediction method using moving and stop objects,” US Patent 6,643,588, November 2003.Google Scholar
- H. W. Eves, Mathematical Circles Squared: A Third Collection of Mathematical Stories and Anecdotes, 3rd ed., Prindle Weber & Schmidt, 1972.Google Scholar