Uma Nova Metodologia para formação de Grupos em VANETs
This work proposes a new methodology to create groups in intervehicular networks as a basis for complex applications involving smart vehicles. We proposed a distributed protocol whose purpose is to build a higher number of groups in less time, keeping the vehicles grouped for most of their journey. We implement our proposal in two versions. The first one considers only the interaction among vehicles. The second includes a group merge functionality. We validate both versions of our protocol using simulation with real traffic data. We evaluate the amount of created groups and their persistence and size.
L. L. Bello, S. Mubeen, S. Saponara, R. Mariani, and U. D. Bordoloi, “Guest editorial embedded and networked systems for intelligent vehicles and robots,” IEEE Transactions on Industrial Informatics, vol. 15, no. 2, pp. 1035–1037, 2019.
V. D. Sagar and T. Nanjundeswaraswamy, “Artificial intelligence in autonomous vehicles-a literature review,” i-Manager’s Journal on Future Engineering and Technology, vol. 14, no. 3, p. 56, 2019.
O. Kayis and T. Acarman, “Clustering formation for inter-vehicle communication,” in 2007 IEEE Intelligent Transportation Systems Conference, Sep. 2007, pp. 636–641.
C. Frese, T. Batz, M. Wieser, and J. Beyerer, “Life cycle management for cooperative groups of cognitive automobiles in a distributed environment,” in 2008 IEEE Intelligent Vehicles Symposium, June 2008, pp.1125–1130.
A. Marjovi, M. Vasic, J. Lemaitre, and A. Martinoli, “Distributed graph-based convoy control for networked intelligent vehicles,” in 2015 IEEE Intelligent Vehicles Symposium (IV), June 2015, pp. 138–143.
W. Ni, W. Wu, and K. Li, “A message efficient intersection control algorithm for intelligent transportation in smart cities,” Future Generation Computer Systems, vol. 76, pp. 339 – 349, 2017. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S0167739X16304794
J. Cheng, W. Wu, J. Cao, and K. Li, “Fuzzy group-based intersection control via vehicular networks for smart transportations,” IEEE Transactions on Industrial Informatics, vol. 13, no. 2, pp. 751–758, April 2017.
C. Cooper, D. Franklin, M. Ros, F. Safaei, and M. Abolhasan, “A comparative survey of vanet clustering techniques,” IEEE Communications Surveys & Tutorials, vol. PP, pp. 1–1, 09 2016.
H. Nishiyama, T. Ngo, S. Oiyama, and N. Kato, “Relay by smart device: Innovative communications for efficient information sharing among vehicles and pedestrians,” IEEE Vehicular Technology Magazine, vol. 10, no. 4, pp. 54–62, Dec 2015.
B. Bloessl and A. O’Driscoll, “A case for good defaults: Pitfalls in vanet physical layer simulations,” in 2019 Wireless Days (WD). IEEE, 2019, pp. 1–6.
B. Hilt, M. Berbineau, A. Vinel, and A. Pirovano, Simulation of Convergent Networks for Intelligent Transport Systems with VSimRTI. Wiley, 2017, ch. 1, pp. 1–28. [Online]. Available: https://ieeexplore.ieee.org/document/8045560
CET-RJ, “SINFRERJ estatı́sticas de volume de tráfego,”https://www.sinfrerj.org.br/site/index.php/textos/pagina/152/Estatisticas-de-volume-de-trafego, 2019, accessed: 2019-12-06.
Taek Jin Kwon, M. Gerla, V. K. Varma, M. Barton, and T. R. Hsing, “Efficient flooding with passive clustering-an overhead-free selective forward mechanism for ad hoc/sensor networks,” Proceedings of the IEEE, vol. 91, no. 8, pp. 1210–1220, 2003.
S. Vodopivec, J. Bester, and A. Kos, “A multihoming clustering algorithm for vehicular ad hoc networks,” International Journal of Distributed Sensor Networks, vol. 2014, pp. 1–8, 03 2014.
D. Krajzewicz, J. Erdmann, M. Behrisch, and L. Bieker, “Recent development and applications of SUMO - Simulation of Urban MObility,” International Journal On Advances in Systems and Measurements, vol. 5, no. 3&4, pp. 128–138, December 2012. [Online]. Available: http://elib.dlr.de/80483/
R. S. Rose-Redwood, “Rationalizing the landscape: superimposing the grid upon the island of manhattan,” Ph.D. dissertation, Pennsylvania State University, 2002.