A New Roadside Detection Method Based on Obstacle Detection


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In order to provide road information for outdoor mobile robot in a complicated environment, a new roadside detection method is proposed based on obstacle detection by applying a four-layer laser radar LD_ML. Because roadside obstacles distribute alone a road, theirs fitting straight lines are parallel to the road. The roadsides detection algorithm includes four steps: first, judge if there are obstacles along roadside or not; second, extract obstacles which belong to roadsides; third, build fitting straight lines through the roadside obstacles; at last, in order to obtain steady and precise roadsides, a EKF method is performed to track the roadsides. The results of experiment have testified the road roadsides detection algorithm has high stability and reliability.



Edited by:

Gary Yang




C. H. Yu et al., "A New Roadside Detection Method Based on Obstacle Detection", Advanced Materials Research, Vol. 429, pp. 324-328, 2012

Online since:

January 2012




[1] J. C. McCall and M. M. Trivedi, Video based lane estimation and tracking for driver assistance: Survey, system, and evaluation, IEEE Trans. on Intelligent Transportation Systems, p.20–37, 2006. 1.

DOI: https://doi.org/10.1109/tits.2006.869595

[2] T. Y. Sun, S. J. Tsai, and V Chan, Hsi color model based lane-marking detection, IEEE Intelligent Transportation Systems Conference, p.1168–1172, 2006. 1.

DOI: https://doi.org/10.1109/itsc.2006.1707380

[3] K. Y. Chiu and S. F. Lin, Lane detection using color-based segmentation, IEEE Intelligent Vehicles Symposium, 2005. 1.

DOI: https://doi.org/10.1109/ivs.2005.1505186

[4] A. Lookingbill, J. Rogers, and D. Lieb, etc., Reverse optical flow for self-supervised adaptive autonomous robot navigation, IJCV, 2007 74 (3), p.287–302.

DOI: https://doi.org/10.1007/s11263-006-0024-x

[5] A. Broggi, C. Caraffi, and R. I. Fedriga, etc., "Obstacle detection with stereo vision for off-road vehicle.

DOI: https://doi.org/10.1109/cvpr.2005.503

[6] navigation, " IEEE International Workshop on Machine Vision for Intelligent Vehicles, 2005. 2.

[7] M. Q. Brendan, A derivative-free implementation of the extended Kalman filter, Automatica, 2006 42 (11), p.1927-(1934).

DOI: https://doi.org/10.1016/j.automatica.2006.06.013

[8] T. M. Rafae, Z. I. Miguel, and U. M. Benito, etc., High-integrity IMM-EKF-based road vehicle navigation with low-cost GPS/SBAS/INS, IEEE Transactions on intelligent transportation systems, 2007, 8(3), pp.491-511.

DOI: https://doi.org/10.1109/tits.2007.902642