Traffic Congestion Re-Routing Control System Using Fuzzy Logic

  • Spoorty S. PatilEmail author
  • Shridevi Soma
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 26)


Centralized solution for traffic in vehicular re-routing to increase congestion are affected by two inherent issues: scalability, the main server needs to achieve wide calculation and communication all along the vehicles in real-time; and personal privacy, as the drivers are required to share their precise location as well as the start and destination of their trip with the server. A central RSU is formed to avoid congestion. This paper addresses a system that uses the fuzzy logic rules which are based on road volume criteria, to select a certain path for the vehicle to avoid the congestion. Also, there is a privacy enhancement protocol to be used for the protection of users’ privacy.


Road side unit (RSU) VANET Fuzzy rules 


  1. 1.
    Pan, J.(S.), Khan, M.A., Popa, I.S., Borcea, K.Z.C.: Proactive vehicle re-routing strategies for congestion avoidance. In: 2012 8th IEEE International Conference on Distributed Computing in Sensor Systems, pp. 265–266 (2012)Google Scholar
  2. 2.
    Divya, R., Suganthi, V., Jayachitra, J.: Modified Congestion Re-routing scheme usingRoadside Unit. ISO 9001:2008, © 2017Google Scholar
  3. 3.
    Wang, S., Djahel, S., McManis, J.: A multi-agent based vehicles re-routing system for unexpected traffic congestion avoidance. In: 2014 IEEE 17th International Conference on Intelligent Transportation Systems (ITSC) October 8–11, pp. 2541–2542 (2014)Google Scholar
  4. 4.
    de Souza, A.M., Boukerche, A., Maia, G., Cerqueira, E., Loureiro, A.A.F., Villas, L.A.: SPARTAN: A Solution to Prevent Traffic Jam with Real-Time Alert and Re-routing for Smart City. 978-1-5090-1701-0/16/$31.00 ©2016 IEEEGoogle Scholar
  5. 5.
    Gruteser, M., Hoh, B.: On the anonymity of periodic location samples. In: SPC 2005, LNCS 3450, pp. 179–192, 2005._c Springer-Verlag Berlin Heidelberg (2005)CrossRefGoogle Scholar
  6. 6.
    Kamijo, S., Koo, H., Liu, X., Fujihira, K., Sakauchi, M.: Development and evaluation of real-time video surveillance system on highway based on semantic hierarchy and decision surface. In: IEEE International Conference on Systems, Man, and Cybernetics, 10–12 October 2005 pp. 840–846 (2005)Google Scholar
  7. 7.
    Kim, K.-H., Lee, J.-H., Lee, B.G.: Congestion data acquisition using high-resolution satellite imagery and frequency analysis techniques. In: IEEE International Geoscience and Remote Sensing. IGARSS 1997. Remote Sensing - A Scientific Vision for Sustainable Development, 3–8 August 1997, pp. 331–334 (1997)Google Scholar
  8. 8.
    Gedik, B., Liu, L.: Protecting location privacy with personalized-anonymity: architecture and algorithms. IEEE Trans. Mob. Comput. 7(1), 1–18 (2008)CrossRefGoogle Scholar
  9. 9.
    Meyerowitz, J., Choudhury, R.R.: Hiding stars with fireworks: location privacy through camouflage. In: MobiCom 2009, September 20–25, 2009, Beijing, China. Copyright 2009 ACM 978-1-60558-702-8/09/09 (2009)Google Scholar
  10. 10.
    Gi Young, L., Kang, J., Hong, Y.: The optimization of traffic signal light using artificial intelligence. In: Proceedings of the 10th IEEE International Conference on Fuzzy Systems, Brisbane Australia (2001)Google Scholar
  11. 11.
    Osigwe, U.C., Oladipo, F.O., Onibere, E.A.: Design, and Simulation of an Intelligent Traffic Control System. Int. J. Adv. Eng. Technol. 1(5), 47–57 (2011)Google Scholar
  12. 12.
    Tan, K., Khalid, M., Yusof, R.: Intelligent traffic lights control by fuzzy logic. Malays. J. Comput. Sci. 9(2), 29–35 (1996)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringPoojya Dodappa Appa College of EngineeringKalaburagiIndia

Personalised recommendations