References: [1] CAR Communication Consortium Manifesto (2007) [Online], ver. 1.1 Overview of the C2C-CC System. elib.dlr.de/48380/1/ C2C-CC_manifesto_v1.1.pdf. [2] Sivasakthi, S. (2013) [Online] Suresh ‘Research on vehicular ad-hoc networks (VANETs): an overview’. Journal of Applied Science and Engineering, (Research). [Online]: http://www.ijaser.com/articles/vol2issue12013/lpages/jaser02010003.html. [3] Harri, J., Filali, F. & Bonnet, C. (2009) [Online] Mobility models for vehicular ad hoc networks: A survey and taxonomy. IEEE Communications Surveys and Tutorials, 11, 19–41. [Online]: http://dx.doi.org/10.1109/SURV.2009.090403, [DOI: 10.1109/ SURV.2009.090403]. [4] Institut Eurecom (2006) [Online] Mobility models for vehicular ad hoc networks: A survey and taxonomy Research Report RR-06. http://www.eurecom.fr/en/publication/1951/download/cmhaerje-060320.pdf, Volume 168, pp. 3–7. [5] Seredynski, M. & Bouvry, P. A survey of vehicular-based cooperative traffic information systems 14th International IEEE Conference ITSC 2011, pp. 163–168 [Online]: http://dx.doi.org/10.1109/ITSC.2011.6083055. [6] Uppoor, S. & Fiore, M. (2011) [Online] Large-scale urban vehicular mobility for networking research IEEE Vehicular Networking Conference (VNC), pp. 62–69. http://dx.doi.org/10.1109/VNC.2011.6117125 [7] Beyer, H.G. (1997) [Online] An analternative explanation for the manner in which genetic algorithms operate. Elsevier Biosystems, 41, 1–15 [DOI: 10.1016/S0303]- 2647(96)01657-7. [Online]: http://dx.doi.org/10.1016/S0303-2647(96)01657-7 [8] Holland, J.H. (1975). Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. University of Michigan Press: Ann Arbor, USA. [9] Fogel, L.J., Owens, A.J. & Walsh, M. J. (1966). Artificial Intelligence Through Simulated Evolution, Vol. 10. John Wiley: New York, USA. [10] Danoy, G., Bouvry, P. & Tabatabaei, M. (2012) [Online] Generation of realistic mobility for VANETs using genetic algorithms IEEE Congress on Evolutionary Computation, pp. 1–8 [DOI: 10.1109/CEC.2012.6252987]. [11] Grzybek, A., Danoy, G. & Bouvry, P. (2012) [Online] Generation of realistic traces for vehicular mobility simulations. DIVAnet’12, pp. 131–138 [Online]: http://dx.doi.org/10.1145/2386958.2386978. [12] Danoy, G. & Bouvry, P. (2011) [Online] A vehicular mobility model based on real traffic counting data 3rd International Conference on Communication Technologies for Vehicles. http://link.springer.com/chapter/10.1007%2F978-3-642-19786-4_12 [13] OpenStreetMap [Online]. www.openstreetmap.org. [14] Dorronsoro, B., Ruiz, P., Pigne, Y. & Bouvry, P. (2014) [Online] Evolutionary algorithms for mobile ad hoc networks. [Online] http://eu.wiley.com/WileyCDA/WileyTitle/productCd-1118341139, subjectCd-MA91.html [15] Nielsen, S., Danoy, G. & Bouvry, P. (2013) [Online] Vehicular mobility model optimization using cooperative coevolutionary genetic algorithmas. GECO, Vol. ’13, p 1349–1356 http://dx.doi.org/10.1145/2463372.2463539 [DOI: 10.1145/2463372.2463539]. [16] Gawron, C. (1998) An iterative algorithm to determine the dynamic user equilibrium in a traffic simulation model. International Journal of Modern Physics C, 09, 393–407 [DOI: 10.1142/S0129183198000303]. [17] Krajzewicz, D. & Rossel, C. (2007) [Online] Simulation of urban mobility (SUMO). . German Aerospace Center. http:// www.dlr.de/ts/en/desktopdefault.aspx/tabid-9883/16931_read-41000/ |