. Android-developers-guide, Recognizing the User's Current Activity, 2013.

D. Ashbrook and T. Starner, Using GPS to learn significant locations and predict movement across multiple users, English. In: Personal and Ubiquitous Computing, pp.275-286, 2003.
DOI : 10.1007/s00779-003-0240-0

L. Bao and S. Intille, Activity Recognition from User-Annotated Acceleration Data, Lecture Notes in Computer Science, vol.3001, pp.1-17, 2004.
DOI : 10.1007/978-3-540-24646-6_1

J. Biagioni, T. Gerlich, T. Merrifield, and J. Eriksson, EasyTracker, Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems, SenSys '11, pp.68-81, 2011.
DOI : 10.1145/2070942.2070950

H. H. Bui, S. Venkatesh, and G. West, Policy Recognition in the Abstract Hidden Markov Model, In: J. Artif. Int. Res, vol.17, issue.1, pp.451-499, 2002.

J. Chen and M. Bierlaire, Probabilistic Multimodal Map Matching With Rich Smartphone Data, Journal of Intelligent Transportation Systems: Technology, Planning and Operations, 2013.
DOI : 10.1145/1409635.1409677

. Ios-developer and . Library, CMMotionActivity Class Reference . 2013. url: https://developer.apple.com/ library, Reference.html, vol.16, 2014.

A. Doucet, N. De-freitas, K. Murphy, and S. Russell, Rao-blackwellised Particle Filtering for Dynamic Bayesian Networks, Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence. UAI'00, pp.176-183, 2000.

A. Doucet, N. Freitas, and N. G. English, An Introduction to Sequential Monte Carlo Methods, Statistics for Engineering and Information Science, pp.3-14, 2001.
DOI : 10.1007/978-1-4757-3437-9_1

G. Flötteröd and M. Bierlaire, Metropolis???Hastings sampling of paths, Transportation Research Part B: Methodological, vol.48, pp.53-66, 2013.
DOI : 10.1016/j.trb.2012.11.002

D. Fox, J. Hightower, L. Liao, D. Schulz, and G. Borriello, Bayesian filtering for location estimation, IEEE Pervasive Computing, vol.2, issue.3, pp.24-33, 2003.
DOI : 10.1109/MPRV.2003.1228524

E. Foxlin, Pedestrian Tracking with Shoe-Mounted Inertial Sensors, Computer Graphics and Applications, pp.38-46, 2005.
DOI : 10.1109/MCG.2005.140

S. Hemminki, P. Nurmi, and S. Tarkoma, Accelerometerbased Transportation Mode Detection on Smartphones, Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems. SenSys '13, pp.1-1314, 2013.

J. R. Kwapisz, G. M. Weiss, and S. A. Moore, Activity recognition using cell phone accelerometers, ACM SIGKDD Explorations Newsletter, vol.12, issue.2, pp.74-82, 2011.
DOI : 10.1145/1964897.1964918

L. Liao, D. J. Patterson, D. Fox, and H. Kautz, Learning and inferring transportation routines, Artificial Intelligence, vol.171, issue.5-6, pp.311-331, 2007.
DOI : 10.1016/j.artint.2007.01.006
URL : http://doi.org/10.1016/j.artint.2007.01.006

Y. Lou, C. Zhang, Y. Zheng, X. Xie, W. Wang et al., Map-matching for low-sampling-rate GPS trajectories, Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS '09, pp.352-361, 2009.
DOI : 10.1145/1653771.1653820

V. Manzoni, D. Maniloff, K. Kloeckl, and C. Ratti, Transportation mode identification and real-time CO2 emission estimation using smartphones, 2010.

U. Maurer, A. Smailagic, D. P. Siewiorek, and M. Deisher, Activity Recognition and Monitoring Using Multiple Sensors on Different Body Positions, International Workshop on Wearable and Implantable Body Sensor Networks (BSN'06), p.4, 2006.
DOI : 10.1109/BSN.2006.6

K. P. Murphy, Dynamic bayesian networks: representation , inference and learning, 2002.

P. Newson and J. Krumm, Hidden Markov map matching through noise and sparseness, Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS '09, pp.336-343, 2009.
DOI : 10.1145/1653771.1653818
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.187.5145

J. Parkka, M. Ermes, P. Korpipaa, J. Mantyjarvi, J. Peltola et al., Activity Classification Using Realistic Data From Wearable Sensors, IEEE Transactions on Information Technology in Biomedicine, vol.10, issue.1, pp.119-128, 2006.
DOI : 10.1109/TITB.2005.856863

M. A. Quddus, W. Y. Ochieng, and R. B. Noland, Current map-matching algorithms for transport applications: State-of-the art and future research directions, Transportation Research Part C: Emerging Technologies, vol.15, issue.5, pp.312-328, 2007.
DOI : 10.1016/j.trc.2007.05.002

N. Ravi, N. Dandekar, P. Mysore, and M. L. Littman, Activity recognition from accelerometer data, In: AAAI, vol.5, pp.1541-1546, 2005.

S. Reddy, M. Mun, J. Burke, D. Estrin, M. Hansen et al., Using mobile phones to determine transportation modes, ACM Transactions on Sensor Networks, vol.6, issue.2, p.13, 2010.
DOI : 10.1145/1689239.1689243
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.180.3547

A. Thiagarajan, J. Biagioni, T. Gerlich, and J. Eriksson, Cooperative transit tracking using smart-phones, Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems, SenSys '10, pp.85-98, 2010.
DOI : 10.1145/1869983.1869993

A. Thiagarajan, L. Ravindranath, K. Lacurts, S. Madden, H. Balakrishnan et al., VTrack, Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems, SenSys '09, pp.85-98, 2009.
DOI : 10.1145/1644038.1644048

S. Wang, C. Chen, and J. Ma, Accelerometer Based Transportation Mode Recognition on Mobile Phones, 2010 Asia-Pacific Conference on Wearable Computing Systems, pp.44-46, 2010.
DOI : 10.1109/APWCS.2010.18

Y. Zheng, Y. Chen, Q. Li, X. Xie, and W. Ma, Understanding transportation modes based on GPS data for web applications, ACM Transactions on the Web, vol.4, issue.1, p.1, 2010.
DOI : 10.1145/1658373.1658374