J. Ramsay and B. Silverman, Functional Data Analysis URL https, 2005.

C. Bouveyron and J. Jacques, Model-based clustering of time series in group-specific functional subspaces, Advances in Data Analysis and Classification, vol.38, issue.2, pp.281-300, 2011.
DOI : 10.1016/j.patcog.2005.01.025
URL : https://hal.archives-ouvertes.fr/hal-00707054

F. Ferraty and P. Vieu, Nonparametric Functional Data Analysis: Theory and Practice

A. Delaigle and P. Hall, Defining probability density for a distribution of random functions, The Annals of Statistics, vol.38, issue.2, pp.1171-1193, 2010.
DOI : 10.1214/09-AOS741
URL : http://doi.org/10.1214/09-aos741

M. Boullé, R. Guigourès, and F. Rossi, Advances in Knowledge Discovery and Management Nonparametric Hierarchical Clustering of Functional Data, pp.15-35

P. W. Michor and D. Mumford, Vanishing geodesic distance on spaces of submanifolds and diffeomorphisms, Documenta Mathematica, vol.10, pp.217-245, 2005.

D. Mumford and C. De-giorgi, The geometry and curvature of shape spaces, pp.43-53, 2009.
DOI : 10.1007/978-88-7642-387-1_4

L. Kaufman and P. Rousseeuw, Clustering by Means of Medoids, Delft University of Technology : reports of the Faculty of Technical Mathematics and Informatics, Faculty of Mathematics and Informatics, 1987. URL https

L. Kaufman and P. Rousseeuw, Finding Groups in Data: an introduction to cluster analysis, 1990.
DOI : 10.1002/9780470316801

V. L. Popov, Contact Mechanics and Friction: Physical Principles and Applications

R. Rajamani, Vehicle Dynamics and Control, Mechanical Engineering Series URL https, 2011.

D. C. Liu and J. , On the limited memory BFGS method for large scale optimization, Mathematical Programming, vol.32, issue.2, pp.503-528, 1989.
DOI : 10.1007/BF01589116
URL : http://www.ece.northwestern.edu/~nocedal/PDFfiles/limited-memory.pdf

J. Macqueen, Some methods for classification and analysis of multivariate observations, Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, pp.281-297, 1967.

T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning, 2001.

P. J. Rousseeuw, Silhouettes: A graphical aid to the interpretation and validation of cluster analysis, Journal of Computational and Applied Mathematics, vol.20, pp.53-650377, 1987.
DOI : 10.1016/0377-0427(87)90125-7

L. Jones, Modélisation des forces de contact entre le pneu d'un avion et la piste, thèse de doctorat dirigée par Bes, Christian et Boiffier, Jean-Luc Mathématiques appliquées et systèmes industriels Toulouse, p.2012, 2012.

P. C. Besse, B. Guillouet, J. Loubes, and F. Royer, Review and Perspective for Distance-Based Clustering of Vehicle Trajectories, IEEE Transactions on Intelligent Transportation Systems, vol.17, issue.11, pp.3306-3317, 2016.
DOI : 10.1109/TITS.2016.2547641

D. Berndt and J. Clifford, Using dynamic time warping to find patterns in time series, pp.359-370, 1994.

M. Vlachos, D. Gunopoulos, and G. Kollios, Discovering similar multidimensional trajectories, Proceedings 18th International Conference on Data Engineering, p.673, 2002.
DOI : 10.1109/ICDE.2002.994784
URL : http://infolab.usc.edu/csci599/Fall2003/Time Series/Discovering similar multidimensional trajectories.pdf

L. Chen, M. Ozsu, and V. Oria, Robust and fast similarity search for moving object trajectories, Proceedings of the 2005 ACM SIGMOD international conference on Management of data , SIGMOD '05, pp.491-502, 2005.
DOI : 10.1145/1066157.1066213
URL : http://www.cs.uiuc.edu/class/fa05/cs591han/sigmodpods05/sigmod/pdf/p491-chen.pdf

L. Chen and R. Ng, On The Marriage of Lp-norms and Edit Distance, Proceedings of the Thirtieth International Conference on Very Large Data Bases, pp.792-803, 2004.
DOI : 10.1016/B978-012088469-8.50070-X

F. Hausdorff, Grundz uge der mengenlehre