A. Polychronopoulos, M. Tsogas, A. Amditis, and L. Andreone, Sensor Fusion for Predicting Vehicles' Path for Collision Avoidance Systems, IEEE Transactions on Intelligent Transportation Systems, vol.8, issue.3, pp.549-562, 2007.
DOI : 10.1109/TITS.2007.903439

R. Miller and Q. Huang, An adaptive peer-to-peer collision warning system, Vehicular Technology Conference. IEEE 55th Vehicular Technology Conference. VTC Spring 2002 (Cat. No.02CH37367), pp.317-321, 2002.
DOI : 10.1109/VTC.2002.1002718

A. Barth and U. Franke, Where will the oncoming vehicle be the next second?, 2008 IEEE Intelligent Vehicles Symposium, pp.1068-1073, 2008.
DOI : 10.1109/IVS.2008.4621210

H. Tan and J. Huang, DGPS-Based Vehicle-to-Vehicle Cooperative Collision Warning: Engineering Feasibility Viewpoints, IEEE Transactions on Intelligent Transportation Systems, vol.7, issue.4, pp.415-428, 2006.
DOI : 10.1109/TITS.2006.883938

T. Batz, K. Watson, and J. Beyerer, Recognition of dangerous situations within a cooperative group of vehicles, 2009 IEEE Intelligent Vehicles Symposium, pp.907-912, 2009.
DOI : 10.1109/IVS.2009.5164400

P. Lytrivis, G. Thomaidis, and A. Amditis, Cooperative Path Prediction in Vehicular Environments, 2008 11th International IEEE Conference on Intelligent Transportation Systems, pp.803-808, 2008.
DOI : 10.1109/ITSC.2008.4732629

K. Murphy, H. Veeraraghavan, N. Papanikolopoulos, and P. Schrater, Dynamic Bayesian networks: representation, inference and learning University of California at Berkeley, USA 19 Deterministic sampling-based switching Kalman filtering for vehicle tracking, Proc. IEEE intelligent transportation systems conference, pp.1340-1345, 2002.

H. Dyckmanns, R. Matthaei, M. Maurer, B. Lichte, J. Effertz et al., Object tracking in urban intersections based on active use of a priori knowledge: Active interacting multi model filter, 2011 IEEE Intelligent Vehicles Symposium (IV), pp.625-630, 2011.
DOI : 10.1109/IVS.2011.5940443

A. Broadhurst, S. Baker, and T. Kanade, Monte Carlo road safety reasoning, IEEE Proceedings. Intelligent Vehicles Symposium, 2005., pp.319-324, 2005.
DOI : 10.1109/IVS.2005.1505122

M. Althoff and A. Mergel, Comparison of Markov Chain Abstraction and Monte Carlo Simulation for the Safety Assessment of Autonomous Cars, IEEE Transactions on Intelligent Transportation Systems, vol.12, issue.4, pp.1237-1247, 2011.
DOI : 10.1109/TITS.2011.2157342

W. Definition, Available at www.oxforddictionaries. com/us/definition/american_english/maneuver, 2012.

G. Aoude, V. Desaraju, L. Stephens, and J. How, Driver Behavior Classification at Intersections and Validation on Large Naturalistic Data Set, IEEE Transactions on Intelligent Transportation Systems, vol.13, issue.2, pp.724-736, 2012.
DOI : 10.1109/TITS.2011.2179537

C. Tay, Analysis of dynamic scenes: application to driving assistance, 2009.

T. Gindele, S. Brechtel, and R. Dillmann, A probabilistic model for estimating driver behaviors and vehicle trajectories in traffic environments, 13th International IEEE Conference on Intelligent Transportation Systems, pp.1625-1631, 2010.
DOI : 10.1109/ITSC.2010.5625262

I. Dagli and D. Reichardt, Motivation-based approach to behavior prediction, Intelligent Vehicle Symposium, 2002. IEEE, pp.227-233, 2002.
DOI : 10.1109/IVS.2002.1187956

M. Garcia-ortiz, J. Fritsch, F. Kummert, and A. Gepperth, Behavior prediction at multiple time-scales in inner-city scenarios, 2011 IEEE Intelligent Vehicles Symposium (IV), pp.1068-1073, 2011.
DOI : 10.1109/IVS.2011.5940524

S. Atev, G. Miller, and N. Papanikolopoulos, Clustering of Vehicle Trajectories, IEEE Transactions on Intelligent Transportation Systems, vol.11, issue.3, pp.647-657, 2010.
DOI : 10.1109/TITS.2010.2048101

D. Vasquez and T. Fraichard, Motion prediction for moving objects: a statistical approach, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004, pp.3931-3936, 2004.
DOI : 10.1109/ROBOT.2004.1308883

URL : https://hal.archives-ouvertes.fr/inria-00182066

C. Hermes, C. Wohler, K. Schenk, and F. Kummert, Long-term vehicle motion prediction, 2009 IEEE Intelligent Vehicles Symposium, pp.652-657, 2009.
DOI : 10.1109/IVS.2009.5164354

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.157.9014

D. Vasquez, T. Fraichard, and C. Laugier, Growing Hidden Markov Models: An Incremental Tool for Learning and Predicting Human and Vehicle Motion, The International Journal of Robotics Research, vol.13, issue.8, pp.11-121486, 2009.
DOI : 10.1177/0278364909342118

URL : https://hal.archives-ouvertes.fr/inria-00430582

J. Joseph, F. Doshi-velez, and N. Roy, A Bayesian nonparametric approach to modeling mobility patterns, Proc. AAAI conference on artificial intelligence, 2010.

G. Aoude, J. Joseph, N. Roy, and J. How, Mobile Agent Trajectory Prediction using Bayesian Nonparametric Reachability Trees, Infotech@Aerospace 2011, pp.1587-1593, 2011.
DOI : 10.2514/6.2011-1512

URL : http://acl.mit.edu/papers/Infotech11_Aoude_Joseph_Roy_How.pdf

Q. Tran and J. Firl, Online maneuver recognition and multimodal trajectory prediction for intersection assistance using non-parametric regression, 2014 IEEE Intelligent Vehicles Symposium Proceedings, pp.918-923, 2014.
DOI : 10.1109/IVS.2014.6856480

W. Hu, X. Xiao, Z. Fu, D. Xie, T. Tan et al., A system for learning statistical motion patterns, IEEE Trans on Pattern Anal Mach Intell, vol.28, issue.9, pp.1450-1464, 2006.

D. Buzan, S. Sclaroff, and G. Kollios, Extraction and clustering of motion trajectories in video, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004., pp.521-524, 2004.
DOI : 10.1109/ICPR.2004.1334287

J. Wiest, F. Kunz, U. Kressel, and K. Dietmayer, Incorporating Categorical Information for Enhanced Probabilistic Trajectory Prediction, 2013 12th International Conference on Machine Learning and Applications, pp.402-407, 2013.
DOI : 10.1109/ICMLA.2013.82

D. Greene, J. Liu, J. Reich, Y. Hirokawa, A. Shinagawa et al., An Efficient Computational Architecture for a Collision Early-Warning System for Vehicles, Pedestrians, and Bicyclists, IEEE Transactions on Intelligent Transportation Systems, vol.12, issue.4, pp.1-12, 2010.
DOI : 10.1109/TITS.2010.2097594

S. Klingelschmitt, M. Platho, H. Gross, V. Willert, and J. Eggert, Combining behavior and situation information for reliably estimating multiple intentions, 2014 IEEE Intelligent Vehicles Symposium Proceedings, pp.388-393, 2014.
DOI : 10.1109/IVS.2014.6856552

B. Morris, A. Doshi, and M. Trivedi, Lane change intent prediction for driver assistance: On-road design and evaluation, 2011 IEEE Intelligent Vehicles Symposium (IV), pp.895-901, 2011.
DOI : 10.1109/IVS.2011.5940538

P. Kumar, M. Perrollaz, S. Lef-`-'lef-`-lef-`-'evre, and C. Laugier, Learning-based approach for online lane change intention prediction, 2013 IEEE Intelligent Vehicles Symposium (IV), pp.797-802, 2013.
DOI : 10.1109/IVS.2013.6629564

URL : https://hal.archives-ouvertes.fr/hal-00821309

H. Mandalia and D. Salvucci, Using support vector machines for lane change detection, Proc. of the Human Factors and Ergonomics Society 49th Annual Meeting, 2005.

H. Berndt, J. Emmert, and K. Dietmayer, Continuous Driver Intention Recognition with Hidden Markov Models, 2008 11th International IEEE Conference on Intelligent Transportation Systems, pp.1189-1194, 2008.
DOI : 10.1109/ITSC.2008.4732630

T. Streubel and K. Hoffmann, Prediction of driver intended path at intersections, 2014 IEEE Intelligent Vehicles Symposium Proceedings, pp.134-139, 2014.
DOI : 10.1109/IVS.2014.6856508

S. Lef-`-'lef-`-lef-`-'evre, Y. Gao, D. Vasquez, E. Tseng, R. Bajcsy et al., Lane keeping assistance with learning-based driver model and model predictive control, Proc. 12th International Symposium on Advanced Vehicle Control, 2014.

A. Tamke, T. Dang, and G. Breuel, A flexible method for criticality assessment in driver assistance systems, 2011 IEEE Intelligent Vehicles Symposium (IV), pp.697-702, 2011.
DOI : 10.1109/IVS.2011.5940482

C. Laugier, I. Paromtchik, M. Perrollaz, M. Yong, J. Yoder et al., Probabilistic Analysis of Dynamic Scenes and Collision Risks Assessment to Improve Driving Safety, IEEE Intelligent Transportation Systems Magazine, vol.3, issue.4, pp.4-19, 2011.
DOI : 10.1109/MITS.2011.942779

M. Althoff, O. Stursberg, and M. Buss, Model-Based Probabilistic Collision Detection in Autonomous Driving, IEEE Transactions on Intelligent Transportation Systems, vol.10, issue.2, pp.299-310, 2009.
DOI : 10.1109/TITS.2009.2018966

E. Kaefer, C. Hermes, C. Woehler, H. Ritter, and F. Kummert, Recognition of situation classes at road intersections, 2010 IEEE International Conference on Robotics and Automation, pp.3960-3965, 2010.
DOI : 10.1109/ROBOT.2010.5509919

A. Lawitzky, D. Althoff, C. Passenberg, G. Tanzmeister, D. Wollherr et al., Interactive scene prediction for automotive applications, 2013 IEEE Intelligent Vehicles Symposium (IV), pp.1028-1033, 2013.
DOI : 10.1109/IVS.2013.6629601

M. Brand, N. Oliver, and A. Pentland, Coupled hidden Markov models for complex action recognition, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.994-999, 1997.
DOI : 10.1109/CVPR.1997.609450

N. Oliver and A. Pentland, Graphical models for driver behavior recognition in a SmartCar, Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511), pp.7-12, 2000.
DOI : 10.1109/IVS.2000.898310

M. Liebner, M. Baumann, F. Klanner, and C. Stiller, Driver intent inference at urban intersections using the intelligent driver model, 2012 IEEE Intelligent Vehicles Symposium, pp.1162-1167, 2012.
DOI : 10.1109/IVS.2012.6232131

G. Agamennoni, J. Nieto, and E. Nebot, A bayesian approach for driving behavior inference, 2011 IEEE Intelligent Vehicles Symposium (IV), pp.595-600, 2011.
DOI : 10.1109/IVS.2011.5940407

G. Agamennoni, J. Nieto, and E. Nebot, Estimation of Multivehicle Dynamics by Considering Contextual Information, IEEE Transactions on Robotics, vol.28, issue.4, pp.855-870, 2012.
DOI : 10.1109/TRO.2012.2195829

S. Lefèvre, C. Laugier, and J. Ibañez-guzmán, Risk assessment at road intersections: Comparing intention and expectation, 2012 IEEE Intelligent Vehicles Symposium, pp.165-171, 2012.
DOI : 10.1109/IVS.2012.6232198

S. Lefèvre, C. Laugier, and J. Ibañez-guzmán, Evaluating risk at road intersections by detecting conflicting intentions, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.4841-4846, 2012.
DOI : 10.1109/IROS.2012.6385491

S. Lefèvre, C. Laugier, and J. Ibañez-guzmán, Intention-aware risk estimation for general traffic situations: application to intersection safety, Inria Research Report, vol.8379, 2013.

J. Ward, G. Agamennoni, S. Worrall, and E. Nebot, Vehicle collision probability calculation for general traffic scenarios under uncertainty, 2014 IEEE Intelligent Vehicles Symposium Proceedings, pp.986-992, 2014.
DOI : 10.1109/IVS.2014.6856430

T. Fraichard and H. Asama, Inevitable collision states ??? a step towards safer robots?, Advanced Robotics, vol.18, issue.10, pp.1001-1024, 2004.
DOI : 10.1163/1568553042674662

URL : https://hal.archives-ouvertes.fr/inria-00182082

A. Berthelot, A. Tamke, T. Dang, and G. Breuel, Handling uncertainties in criticality assessment, 2011 IEEE Intelligent Vehicles Symposium (IV), pp.571-576, 2011.
DOI : 10.1109/IVS.2011.5940483

C. Chan, Defining safety performance measures of driver assistance systems for intersection left-turn conflicts, Proc. IEEE intelligent vehicles symposium, pp.25-30, 2006.

F. Seeliger, G. Weidl, D. Petrich, F. Naujoks, G. Breuel et al., Advisory warnings based on cooperative perception, 2014 IEEE Intelligent Vehicles Symposium Proceedings, pp.246-252, 2014.
DOI : 10.1109/IVS.2014.6856479

R. Labayrade, C. Royere, and A. D. , A collision mitigation system using laser scanner and stereovision fusion and its assessment, IEEE Proceedings. Intelligent Vehicles Symposium, 2005., pp.441-446, 2005.
DOI : 10.1109/IVS.2005.1505143

Y. Liu, O. Ozguner, and E. Ekici, Performance evaluation of intersection warning system using a vehicle traffic and wireless simulator, IEEE Proceedings. Intelligent Vehicles Symposium, 2005., pp.171-176, 2005.
DOI : 10.1109/IVS.2005.1505097

J. Ibañez-guzmán, S. Lefèvre, A. Mokkadem, and S. Rodhain, Vehicle to vehicle communications applied to road intersection safety, Proc. IEEE international conference on intelligent transportation systems, pp.192-197, 2010.

S. Worrall, D. Orchansky, F. Masson, and E. Nebot, Improving vehicle safety using context based detection of risk, 13th International IEEE Conference on Intelligent Transportation Systems, pp.379-385, 2010.
DOI : 10.1109/ITSC.2010.5625185

J. Salas, H. Jimenez, J. Gonzalez, and J. Hurtado, Detecting Unusual Activities at Vehicular Intersections, Proceedings 2007 IEEE International Conference on Robotics and Automation, pp.864-869, 2007.
DOI : 10.1109/ROBOT.2007.363094

N. Saunier and T. Sayed, Clustering Vehicle Trajectories with Hidden Markov Models Application to Automated Traffic Safety Analysis, The 2006 IEEE International Joint Conference on Neural Network Proceedings, pp.4132-4138, 2006.
DOI : 10.1109/IJCNN.2006.246960

A. Kurt, J. Yester, Y. Mochizuki, and Ü. Özgüner, Hybrid-state driver/vehicle modelling, estimation and prediction, 13th International IEEE Conference on Intelligent Transportation Systems, pp.806-811, 2010.
DOI : 10.1109/ITSC.2010.5625201

B. Mourllion, D. Gruyer, A. Lambert, and S. Glaser, Kalman filters predictive steps comparison for vehicle localization, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.565-571, 2005.
DOI : 10.1109/IROS.2005.1545151

B. Morris and M. Trivedi, Learning trajectory patterns by clustering: Experimental studies and comparative evaluation, 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp.312-319, 2009.
DOI : 10.1109/CVPR.2009.5206559