J. Zhang, F. Wang, K. Wang, W. Lin, X. Xu et al., Data-Driven Intelligent Transportation Systems: A Survey, IEEE Transactions on Intelligent Transportation Systems, vol.12, issue.4, pp.12-1624, 2011.
DOI : 10.1109/TITS.2011.2158001

J. Park, D. Li, Y. L. Murphey, J. Kristinsson, R. Mcgee et al., Real time vehicle speed prediction using a Neural Network Traffic Model, The 2011 International Joint Conference on Neural Networks, pp.2991-2996, 2011.
DOI : 10.1109/IJCNN.2011.6033614

M. G. Karlaftis and E. I. Vlahogianni, Statistical methods versus neural networks in transportation research: Differences, similarities and some insights. Transportation Research Part C Emerging Technologies, pp.387-399, 2011.
DOI : 10.1016/j.trc.2010.10.004

Q. T. Tran, Z. Ma, H. Li, L. Hao, and Q. K. Trinh, A Multiplicative Seasonal ARIMA/GARCH Model in EVN Traffic Prediction, International Journal of Communications, Network and System Sciences, vol.08, issue.04, pp.8-43, 2015.
DOI : 10.4236/ijcns.2015.84005
URL : https://doi.org/10.4236/ijcns.2015.84005

M. V. Voort, M. Dougherty, and S. Watson, Combining kohonen maps with arima time series models to forecast traffic flow. Transportation Research Part C Emerging Technologies, pp.307-318, 1996.

B. Williams, Multivariate Vehicular Traffic Flow Prediction: Evaluation of ARIMAX Modeling, Transportation Research Record: Journal of the Transportation Research Board, vol.1776, issue.1, pp.1776-194, 2001.
DOI : 10.3141/1776-25

G. A. Davis and N. L. Nihan, Nonparametric Regression and Short???Term Freeway Traffic Forecasting, Journal of Transportation Engineering, vol.117, issue.2, pp.178-188, 1991.
DOI : 10.1061/(ASCE)0733-947X(1991)117:2(178)

C. H. Wu, J. M. Ho, and D. T. Lee, Travel-Time Prediction With Support Vector Regression, IEEE Transactions on Intelligent Transportation Systems, vol.5, issue.4, pp.276-281, 2004.
DOI : 10.1109/TITS.2004.837813

M. Castro-neto, Y. S. Jeong, M. K. Jeong, and L. D. Han, Online-SVR for short-term traffic flow prediction under typical and atypical traffic conditions, Expert Systems with Applications, vol.36, issue.3, pp.36-6164, 2009.
DOI : 10.1016/j.eswa.2008.07.069

W. C. Hong, Traffic flow forecasting by seasonal SVR with chaotic simulated annealing algorithm, Neurocomputing, vol.74, issue.12-13, pp.12-13, 2011.
DOI : 10.1016/j.neucom.2010.12.032

M. T. Asif, J. Dauwels, C. Y. Goh, A. Oran, E. Fathi et al., Spatiotemporal Patterns in Large-Scale Traffic Speed Prediction, IEEE Transactions on Intelligent Transportation Systems, vol.15, issue.2, pp.15-794, 2014.
DOI : 10.1109/TITS.2013.2290285
URL : http://dspace.mit.edu/bitstream/1721.1/100436/1/Jaillet_Spatiotemporal.pdf

S. H. Huang and B. Ran, An Application of Neural Network on Traffic Speed Prediction Under Adverse Weather Condition, 2003.

W. Zheng, D. H. Lee, W. Zheng, and D. H. Lee, Short-Term Freeway Traffic Flow Prediction: Bayesian Combined Neural Network Approach, Journal of Transportation Engineering, vol.132, issue.2, pp.132-114, 2006.
DOI : 10.1061/(ASCE)0733-947X(2006)132:2(114)

F. Moretti, S. Pizzuti, S. Panzieri, and M. Annunziato, Urban traffic flow forecasting through statistical and neural network bagging ensemble hybrid modeling, Neurocomputing, vol.167, pp.3-7, 2015.
DOI : 10.1016/j.neucom.2014.08.100

W. Huang, G. Song, and H. Hong, Deep Architecture for Traffic Flow Prediction: Deep Belief Networks With Multitask Learning, IEEE Transactions on Intelligent Transportation Systems, vol.15, issue.5, pp.152191-2201, 2014.
DOI : 10.1109/TITS.2014.2311123

R. Soua, A. Koesdwiady, and F. Karray, Big-data-generated traffic flow prediction using deep learning and dempster-shafer theory, 2016 International Joint Conference on Neural Networks (IJCNN), pp.3195-3202
DOI : 10.1109/IJCNN.2016.7727607

X. Ma, H. Yu, Y. Wang, and Y. Wang, Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory, PLOS ONE, vol.8, issue.1, pp.10-0119044, 2015.
DOI : 10.1371/journal.pone.0119044.s001
URL : https://doi.org/10.1371/journal.pone.0119044

Y. Lv, Y. Duan, and W. Kang, Traffic Flow Prediction With Big Data: A Deep Learning Approach, IEEE Transactions on Intelligent Transportation Systems, vol.16, issue.2, pp.865-873, 2015.
DOI : 10.1109/TITS.2014.2345663

Y. Duan, Y. Lv, W. Kang, and Y. Zhao, A deep learning based approach for traffic data imputation, pp.912-917, 2014.

Y. Tian and L. Pan, Predicting Short-Term Traffic Flow by Long Short-Term Memory Recurrent Neural Network, 2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity), pp.153-158
DOI : 10.1109/SmartCity.2015.63

J. Zhang, Y. Zheng, and D. Qi, Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction, AAAI, pp.1655-1661

X. Ma, Z. Dai, and Z. He, Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction, Sensors, vol.41, issue.4, pp.17-818, 2017.
DOI : 10.1016/j.trc.2004.07.015
URL : http://www.mdpi.com/1424-8220/17/4/818/pdf