M. Aly, Real time detection of lane markers in urban streets, IEEE Intelligent Vehicles Symposium, p.12, 2008.

C. Andrieu, Methodes mcmc pour l'analyse bayesienne de modeles de regression parametrique non lineaire. application a l'analyse de raies et a la deconvolution impulsionnelle, 1998.

D. Antolovic, Review of the hough transform method, with an implementation of the fast hough variant for line detection, IEEE Sensors Journal, vol.18, issue.6, pp.2555-2567, 2008.

. Arcos-garcíaá, J. A. Álvarez-garcía, and L. M. Soria-morillo, Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods, Neural Networks, vol.99, pp.158-165, 2018.

N. P. Botekar and M. Mahalakshmi, Development of road sign recognition for adas using opencv, 2017 International Conference on Intelligent Computing and Control (I2C2), pp.1-4, 2017.

V. S. Bottazzi, P. V. Borges, B. Stantic, and J. J. , Adaptive regions of interest based on hsv histograms for lane marks detection, Robot Intelligence Technology and Applications, vol.2, pp.677-687, 2014.

J. Y. Bouguet, Pyramidal implementation of the affine lucas kanade feature tracker description of the algorithm, Intel Corporation, vol.5, p.4, 2001.

G. Bresson, Z. Alsayed, L. Yu, and S. Glaser, Simultaneous localization and mapping: A survey of current trends in autonomous driving, IEEE Transactions on Intelligent Vehicles, vol.2, issue.3, pp.194-220, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01615897

A. Broggi, P. Cerri, P. Medici, P. P. Porta, and G. Ghisio, Real time road signs recognition, IEEE Intelligent Vehicles Symposium, pp.981-986, 2007.

A. F. Cela, L. M. Bergasa, F. L. Sanchez, and M. A. Herrera, Lanes detection based on unsupervised and adaptive classifier, 2013 Fifth International Conference on Computational Intelligence, Communication Systems and Networks, pp.228-233, 2013.

G. Che, L. Liu, and Z. Yu, An improved ant colony optimization algorithm based on particle swarm optimization algorithm for path planning of autonomous underwater vehicle, Journal of Ambient Intelligence and Humanized Computing pp, pp.1-6, 2019.

Q. Chen and H. Wang, A real-time lane detection algorithm based on a hyperbola-pair model, IEEE Intelligent Vehicles Symposium, pp.510-515, 2006.

Y. Chen and M. He, Sharp curve lane boundaries projective model and detection, IEEE 10th International Conference on Industrial Informatics, pp.1188-1193, 2012.

Y. Chengping, S. Lincheng, Z. Dianle, Z. Daibing, and Z. Zhiwei, A new calibration method for vision system using differential gps, 13th International Conference on Control Automation Robotics & Vision (ICARCV), pp.1514-1517, 2014.

S. H. Chiu, C. Y. Wen, J. H. Lee, K. H. Lin, and H. M. Chen, A fast randomized generalized hough transform for arbitrary shape detection, International Journal of Innovative Computing, Information and Control, vol.8, issue.2, 2012.

R. Cimurs, J. Hwang, and I. H. Suh, Bezier curve-based smoothing for path planner with curvature constraint, 2017 First IEEE International Conference on Robotic Computing (IRC), pp.241-248, 2017.

M. K. Cowles and B. P. Carlin, Markov chain monte carlo convergence diagnostics: a comparative review, Journal of the American Statistical Association, vol.91, issue.434, pp.883-904, 1996.

C. Dagnino, P. Lamberti, and S. Remogna, Curve network interpolation by c1 quadratic b-spline surfaces, Computer Aided Geometric Design, vol.40, pp.26-39, 2015.

E. Faizal and H. Mansor, Virtual mid-line detection on curve road for user guidance using simulation model, 2009 International Conference on Computer Technology and Development, vol.1, pp.24-27, 2009.

M. Fakhfakh, N. Fakhfakh, and L. Chaari, Robust lane extraction using twodimension declivity, International Conference on Artificial Intelligence and Soft Computing, pp.14-24, 2018.
URL : https://hal.archives-ouvertes.fr/hal-02938620

C. Fan, X. Jb, and S. Di, Lane detection based on machine learning algorithm, Telkomnika Indonesian Journal of Electrical Engineering, vol.12, issue.2, pp.1403-1409, 2013.

J. Guo, Z. Wei, and D. Miao, Lane detection method based on improved ransac algorithm, 2015 IEEE Twelfth International Symposium on Autonomous Decentralized Systems, pp.285-288, 2015.

S. Y. Guo, Y. G. Kong, Q. Tang, and F. Zhang, Probabilistic hough transform for line detection utilizing surround suppression, International Conference on Machine Learning and Cybernetics, IEEE, vol.5, pp.2993-2998, 2008.

A. S. Hassanein, S. Mohammad, M. Sameer, and M. E. Ragab, A survey on hough transform, theory, techniques and applications, 2015.

S. S. Ieng, J. Vrignon, D. Gruyer, and A. D. , A new multi-lanes detection using multi-camera for robust vehicle location, IEEE Proceedings. Intelligent Vehicles Symposium, pp.700-705, 2005.

H. Izadinia, F. Sadeghi, and M. M. Ebadzadeh, Fuzzy generalized hough transform invariant to rotation and scale in noisy environment, 2009 IEEE International Conference on Fuzzy Systems, pp.153-158, 2009.

H. J. Jang, S. H. Baek, and S. Y. Park, Curved lane detection using robust feature extraction, The 2014 2nd International Conference on Systems and Informatics, pp.109-112, 2014.

C. R. Jung and C. R. Kelber, Lane following and lane departure using a linearparabolic model, Image and Vision Computing, vol.23, pp.1192-1202, 2005.

O. O. Khalifa, I. M. Khan, A. A. Assidiq, A. H. Abdulla, and S. Khan, A hyperbolapair based lane detection system for vehicle guidance, Proceedings of the World Congress on Engineering and Computer Science, vol.1, pp.978-988, 2010.

H. Kim, Multiple vehicle tracking and classification system with a convolutional neural network, Journal of Ambient Intelligence and Humanized Computing pp 1-12, 2019.

J. Kim and M. Lee, Robust lane detection based on convolutional neural network and random sample consensus, International Conference on Neural Information Processing, pp.454-461, 2014.

J. Kim and C. Park, End-to-end ego lane estimation based on sequential transfer learning for self-driving cars, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.30-38, 2017.

J. Kim, J. Kim, G. J. Jang, and M. Lee, Fast learning method for convolutional neural networks using extreme learning machine and its application to lane detection, Neural Networks, vol.87, pp.109-121, 2017.

T. Kim and T. Park, Calibration method between dual 3d lidar sensors for autonomous vehicles, 2017 56th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE), pp.1075-1081, 2017.

P. Kultanen, L. Xu, and E. Oja, Randomized hough transform (rht), Proceedings. 10th International Conference on Pattern Recognition, vol.1, pp.631-635, 1990.

M. Lee, K. Y. Han, J. Yu, and Y. S. Lee, A new lane following method based on deep learning for automated vehicles using surround view images, Journal of Ambient Intelligence and Humanized Computing, pp.1-14, 2019.

J. Li, X. Mei, D. Prokhorov, and D. Tao, Deep neural network for structural prediction and lane detection in traffic scene, IEEE transactions on neural networks and learning systems, vol.28, issue.3, pp.690-703, 2017.

M. Li, Y. Li, and M. Jiang, Lane detection based on connection of various feature extraction methods, Advances in Multimedia, 2018.

S. Li, J. Xu, W. Wei, and H. Qi, Curve lane detection based on the binary particle swarm optimization, 2017 29th Chinese Control And Decision Conference (CCDC), pp.75-80, 2017.

K. H. Lim, K. P. Seng, and L. M. Ang, River flow lane detection and kalman filtering-based b-spline lane tracking, International Journal of Vehicular Technology, 2012.

Q. Lin, Y. Han, and H. Hahn, Real-time lane departure detection based on extended edge-linking algorithm, 2010 Second International Conference on Computer Research and Development, pp.725-730, 2010.

J. Liu, L. Lou, D. Huang, Y. Zheng, and W. Xia, Lane detection based on straight line model and k-means clustering, 2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS), pp.527-532, 2018.

X. Liu, G. Wang, J. Liao, B. Li, Q. He et al., Detection of geometric shape for traffic lane and mark, 2012 IEEE International Conference on Information and Automation, pp.395-399, 2012.

J. Lopez-krahe and P. Pousset, Transformée de hough discrete et bornée, applicationa la detection de droites paralleles et du réseau routier, Traitement du signal, vol.5, issue.4, pp.281-290, 1988.

R. S. Merali and T. D. Barfoot, Occupancy grid mapping with markov chain monte carlo gibbs sampling, 2013 IEEE International Conference on Robotics and Automation, pp.3183-3189, 2013.

P. Mukhopadhyay and B. B. Chaudhuri, A survey of hough transform, Pattern Recognition, vol.48, issue.3, pp.993-1010, 2015.

T. T. Nguyen, J. Spehr, T. Lin, and D. Lipinski, Fused raised pavement marker detection using 2d-lidar and mono camera, IEEE 18th International Conference on Intelligent Transportation Systems, pp.2346-2351, 2015.

A. Parajuli, M. Celenk, and H. B. Riley, Robust lane detection in shadows and low illumination conditions using local gradient features, Open Journal of Applied Sciences, vol.3, issue.01, p.68, 2013.

S. I. Roumeliotis and G. A. Bekey, Bayesian estimation and kalman filtering: A unified framework for mobile robot localization, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No. 00CH37065), vol.3, pp.2985-2992, 2000.

D. Santana, C. M. Furukawa, and N. Maruyama, Sensor fusion with lowgrade inertial sensors and odometer to estimate geodetic coordinates in environments without gps signal, IEEE Latin America Transactions, vol.11, issue.4, pp.1015-1021, 2013.

P. Saxena, N. Gupta, S. Y. Laskar, and P. P. Borah, A study on automatic detection and recognition techniques for road signs, Int J Comput Eng Res, vol.5, issue.12, pp.24-28, 2015.

M. V. Shenoy, A. Karuppiah, and N. Manjarekar, A lightweight ann based robust localization technique for rapid deployment of autonomous systems, Journal of Ambient Intelligence and Humanized Computing, pp.1-16, 2019.

R. M. Shiffrin, M. D. Lee, W. Kim, and E. J. Wagenmakers, A survey of model evaluation approaches with a tutorial on hierarchical bayesian methods, Cognitive Science, vol.32, issue.8, pp.1248-1284, 2008.

W. Song, Y. Yang, M. Fu, Y. Li, and M. Wang, Lane detection and classification for forward collision warning system based on stereo vision, IEEE Sensors Journal, vol.18, issue.12, pp.5151-5163, 2018.

H. Tan, Y. Zhou, Y. Zhu, D. Yao, and K. Li, A novel curve lane detection based on improved river flow and ransa, 17th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp.133-138, 2014.

H. Tan, Y. Zhou, Y. Zhu, D. Yao, and J. Wang, Improved river flow and random sample consensus for curve lane detection, Advances in Mechanical Engineering, vol.7, issue.7, p.1687814015593866, 2015.

A. D. Thomas, Compressing the parameter space of the generalised hough transform, Pattern Recognition Letters, vol.13, issue.2, pp.107-112, 1992.

Y. Timar and F. Alagoz, Lane detection for intelligent vehicles in challenging scenarios, 2010 2nd International Conference on Computational Intelligence, Communication Systems and Networks, pp.37-43, 2010.

T. Veit, J. P. Tarel, P. Nicolle, and P. Charbonnier, Evaluation of road marking feature extraction, 11th International IEEE Conference on Intelligent Transportation Systems, pp.174-181, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00402945

J. Wang and X. An, A multi-step curved lane detection algorithm based on hyperbola-pair model, 2010 IEEE International Conference on Automation and Logistics, pp.132-137, 2010.

Y. Wang, E. K. Teoh, and D. Shen, Lane detection using b-snake, Proceedings 1999 International Conference on Information Intelligence and Systems (Cat. No. PR00446), pp.438-443, 1999.

Y. Wang, L. Bai, and M. Fairhurst, Robust road modeling and tracking using condensation, IEEE Transactions on Intelligent Transportation Systems, vol.9, issue.4, p.570, 2008.

Y. Wu and Z. Chen, A detection method of road traffic sign based on inverse perspective transform, 2016 IEEE International Conference of Online Analysis and Computing Science (ICOACS), pp.293-296, 2016.

L. Xu, E. Oja, and P. Kultanen, A new curve detection method: randomized hough transform (rht), Pattern recognition letters, vol.11, issue.5, pp.331-338, 1990.

Y. Zhou and Z. Dong, A vision-based autonomous detection scheme for obstacles on the runway, pp.832-838, 2017.