Abstract
This paper presents a robust road perception algorithm aimed to detect multiple lanes with temporal integration, one of the most important tasks in Advanced Driver Assistance Systems (ADAS). A new vision-based system is proposed, consisting on three parts: a line marker detection algorithm, a road line classification and a lane tracking integration. The goal is to detect the position, type and number of road lanes. The developed approach is characterized by the use of the bird’s eye view, road marks filtering based on gradient space algorithms, robust features descriptor for line classification, and road tracking based on time of life for each detected lane. The road detection is done according to the Spanish standard IC 8.2. The system was tested on the test platform IvvI 2.0.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bertozzi, M., Broggi, A.: Gold: a parallel real-time stereo vision system for generic obstacle and lane detection. IEEE Trans. Image Process. 7(1), 62–81 (1998)
de Carreteras, I.: 8.2 ic marcas viales. (1987)
Crisman, J.D., Thorpe, C.E.: Scarf: a color vision system that tracks roads and intersections. IEEE Trans. Robot. Autom. 9(1), 49–58 (1993)
Felisa, M., Zani, P.: Robust monocular lane detection in urban environments. In: 2010 IEEE Intelligent Vehicles Symposium (IV), pp. 591–596. IEEE (2010)
Liu, G., Worgotter, F., Markelic, I.: Combining statistical hough transform and particle filter for robust lane detection and tracking. In: 2010 IEEE Intelligent Vehicles Symposium (IV), pp. 993–997. IEEE (2010)
Martín, D., García, F., Musleh, B., Olmeda, D., Peláez, G., Marín, P., Ponz, A., Rodríguez, C., Al-Kaff, A., De La Escalera, A., et al.: Ivvi 2.0: an intelligent vehicle based on computational perception. Expert Syst. Appl. 41(17), 7927–7944 (2014)
Muad, A.M., Hussain, A., Samad, S.A., Mustaffa, M.M., Majlis, B.Y.: Implementation of inverse perspective mapping algorithm for the development of an automatic lane tracking system. In: 2004 IEEE Region 10 Conference TENCON 2004, pp. 207–210. IEEE (2004)
Rodríguez-Garavito, C., Ponz, A., García, F., Martín, D., de la Escalera, A., Armingol, J.: Automatic laser and camera extrinsic calibration for data fusion using road plane. In: 2014 17th International Conference on Information Fusion (FUSION), pp. 1–6. IEEE (2014)
Torr, P.H., Zisserman, A.: Mlesac: a new robust estimator with application to estimating image geometry. Comput. Vis. Image Underst. 78(1), 138–156 (2000)
Acknowledgments
This work was supported by automation engineering department from de La Salle University, Bogotá-Colombia; Administrative Department of Science, Technology and Innovation (COLCIENCIAS), Bogotá-Colombia and the Spanish Government through the CICYT projects (TRA2013-48314-C3-1-R) and (TRA2011-29454-C03-02) and Comunidad de Madrid through SEGVAUTO_TRIES \((S2013/MIT-2713)\).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Rodríguez-Garavito, C.H., Carmona-Fernández, J., de la Escalera, A., Armingol, J.M. (2015). Stereo Road Detection Based on Ground Plane. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2015. EUROCAST 2015. Lecture Notes in Computer Science(), vol 9520. Springer, Cham. https://doi.org/10.1007/978-3-319-27340-2_92
Download citation
DOI: https://doi.org/10.1007/978-3-319-27340-2_92
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-27339-6
Online ISBN: 978-3-319-27340-2
eBook Packages: Computer ScienceComputer Science (R0)