Skip to main content
SpringerLink
Log in

Fuzzy Logic-Based Adaptive Decision Support in Autonomous Vehicular Networks

  • Chapter
  • First Online:
Computational Intelligence for Decision Support in Cyber-Physical Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 540))

Abstract

The area of intelligent autonomous vehicles and systems poses new challenges in providing mechanisms for efficient communication and control between vehicles, as well as developing robust, adaptive techniques to support intelligent transportation system applications. In this chapter, we show the need for providing an intelligent controller offering decision support in autonomous vehicular networks in terms of broadcast communication channel access. Specifically, we exploit fuzzy logic control, derived from its reported strength of using linguistic information to control nonlinear systems, to build an adaptive, intelligent controller, based on the traffic density, to aid vehicles in deciding when to access the broadcast communication channel. It is demonstrated, by means of enriched simulative evaluation that the fuzzy logic-based controller offers inbuilt robustness with effective control of the system under dense conditions, in contrast with the conventional—IEEE 802.11p standard—solution we compared against.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. G. Karagiannis, O. Altintas, E. Ekici, G. Heijenk, B. Jarupan, K. Lin, T. Weil, Vehicular networking: a survey and tutorial on requirements, architectures, challenges, standards and solutions. IEEE Commun. Surv. Tutorials 13(4), 1–33 (2011)

    Article  Google Scholar 

  2. IEEE Std P1609.1, Trial-use standard for wireless access in vehicular environments (WAVE)—resource manager, (2006) doi:10.1109/IEEESTD.2006.246485

  3. IEEE Std P1609.2, Trial-use standard for wireless access in vehicular environments (WAVE)—security services for applications and management messages (2006), doi: 10.1109/IEEESTD.2006.243731

  4. IEEE Std P1609.3, Trial-use standard for wireless access in vehicular environments (WAVE)—networking services (2007), doi: 10.1109/IEEESTD.2007.353212

  5. IEEE Std P1609.4, Trial-use standard for wireless access in vehicular environments (WAVE)—multi-channel operation (2006), doi: 10.1109/IEEESTD.2006.254109

  6. IEEE Std 802.11p, IEEE standard for information technology-telecommunications and information exchange between systems—local and metropolitan area networks—specific requirements Part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) specifications—Amendment 6: Wireless access in vehicular environments 2010, Doi: 10.1109/IEEESTD.2010.5514475

  7. D, Jiang, L. Delgrossi, IEEE 802.11p: towards an international standard for wireless access in vehicular environments. Paper presented at the 67th IEEE vehicular technology conference, VTC Spring 2008, Singapore, pp. 2036–2040, 11–14 May 2008

    Google Scholar 

  8. USA ITS Standards advisory, Dedicated Short Range Communications (DSRC). http://www.standards.its.dot.gov

  9. D. Jiang, V. Taliwal, A. Meier, W. Holfelder, R. Herrtwich, Design of 5.9 GHz DSRC-based vehicular safety communication. IEEE Wireless Commun. 13(5), 36–43 (2006)

    Article  Google Scholar 

  10. R.A. Uzcategui, WAVE: a tutorial. IEEE Commun. Mag. 47(5), 126–133 (2009)

    Article  Google Scholar 

  11. A. Senart, M. Bouroche, V. Cahill, S. Weber, Vehicular networks and applications, in Middleware for network eccentric and mobile applications, ed. by B. Garbinato, H. Miranda, L. Rodriques (Springer, Heidelberg, 2009), pp. 369–381

    Chapter  Google Scholar 

  12. E.M. van Eenennaam, K. Wolterink, G. Karagiannis, G.J. Heijenk, Exploring the solution space of beaconing in VANETs. Paper presented at the 1st IEEE vehicular networking conference (VNC2009), Tokyo, pp. 1–8, 28–30 Oct 2009

    Google Scholar 

  13. R. Reinders, M. van Eenennaam, G. Karagiannis, G. Heijenk, Contention window analysis for beaconing in VANETs. Paper presented at the 7th IEEE international wireless communications and mobile computing conference (IWCMC 2011), Istanbul, pp. 1481–1487, 4–8 July 2011

    Google Scholar 

  14. S. Eichler, Performance evaluation of the IEEE 802.11pWAVE communication standard. Paper presented at the 66th IEEE international vehicular technology conference (VTC-2007 Fall), Maryland, pp. 2199–2203, 30 Sept–3 Oct 2007

    Google Scholar 

  15. Y. Wang, A. Ahmed, B. Krishnamachari, K. Psounis, IEEE 802.11p performance evaluation and protocol enhancement. Paper presented at the IEEE international conference on vehicular electronics and safety, Columbus, Ohio, pp. 317–322, 22–24 Sept 2008

    Google Scholar 

  16. K. Bilstrub, E. Uhlemann, E.G. Strom, U. Bilstrup, On the ability of the 802.11p MAC method and STDMA to support real-time vehicle-to-vehicle communication. EURASIP J. Wireless Commun. Network. 2009, 902414 (2009). doi:10.1155/2009/902414

    Google Scholar 

  17. C. Chrysostomou, C. Djouvas, L. Lambrinos, Applying adaptive, QoS-aware medium access control in priority-based vehicular ad hoc networks. Paper presented at the 16th IEEE symposium on computers and communications (IEEE ISCC 2011), Corfu, pp. 741–747, 28 June–1 July 2011

    Google Scholar 

  18. C. Chrysostomou, C. Djouvas, L. Lambrinos, Dynamically adjusting the min-max contention window for providing quality of service in vehicular networks. Paper presented at the 11th annual mediterranean ad hoc networking workshop (Med-Hoc-Net’12), Ayia Napa, pp. 16–23, 19–22 June 2012

    Google Scholar 

  19. L.A. Zadeh, Fuzzy Sets. Inf. control 8, 338–353 (1965)

    Article  MATH  MathSciNet  Google Scholar 

  20. K. Passino, M. Yurkovich, Fuzzy Control, (Prentice Hall, USA, 1998) ISBN 0-201-18074-X

    Google Scholar 

  21. L.A. Zadeh, Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans. Syst. Man Cybernetics. 3(1), 28–44 (1973)

    Article  MATH  MathSciNet  Google Scholar 

  22. E.H. Mamdani, Applications of fuzzy algorithms for control of simple dynamic plant. Proc. IEE 121(12), 1585–1588 (1974)

    Google Scholar 

  23. A. Pitsillides, A. Sekercioglu, Congestion control, in Computational intelligence in telecommunications networks, ed. by W. Pedrycz, A.V. Vasilakos (CRC Press, Boca Raton, 2000), pp. 109–158. ISBN 0-8493-1075-X

    Google Scholar 

  24. A. Sekercioglu, A. Pitsillides, A. Vasilakos, Computational intelligence in management of ATM networks. J.Soft Comput. 5(4), 257–263 (2001)

    Article  MATH  Google Scholar 

  25. B. Azvine, A. Vasilakos, Application of soft computing techniques to the telecommunication domain, ed. by G. Tselentis (ERUDIT Roadmap, 2000), pp. 89–110

    Google Scholar 

  26. E. Morales, M. Polycarpou, N. Hemasilpin, J. Bissler, Hierarchical adaptive and supervisory control of continuous venovenous hemofiltration. IEEE Trans. Control Syst. Technol. 9(3), 445–457 (2001)

    Article  Google Scholar 

  27. A. Sekercioglou, A. Pitsillides, G.K. Egan, Study of an adaptive fuzzy controller based on the adaptation of relative rule weights. Paper presented at the 2nd ANZIIS, Brisbane, pp. 204–208, 29 Nov–2 Dec 1994

    Google Scholar 

  28. A. Pitsillides, A. Sekercioglou, G. Ramamurthy, Effective control of traffic flow in ATM networks using fuzzy explicit rate marking (FERM). IEEE J. Sel. Areas Commun. 15(2), 209–225 (1997)

    Article  Google Scholar 

  29. C. Douligeris, G. Develekos, A fuzzy logic approach to congestion control in ATM networks. Paper presented at the of IEEE ICC’95, Seattle, pp. 1969–1973, 18–22 June 1995

    Google Scholar 

  30. L. Rossides, A. Sekercioglu, S. Kohler, A. Pitsillides, T.G. Phuoc, A. Vassilakos, Fuzzy logic controlled RED: congestion control for TCP/IP diff-serv architecture. Paper presented at the 8th European congress on intelligent techniques and soft computing (ESIT2000), Aachen, pp. 263–269, 14–15 Sept 2000

    Google Scholar 

  31. L. Rossides, C. Chrysostomou, A. Pitsillides, A. Sekercioglu, Overview of Fuzzy-RED in Diff-Serv Networks, in Proceedings of Soft-Ware 2002, vol. 2311, Lecture notes in computer science, ed. by D. Bustard, W. Liu, R. Sterritt (Springer, Heidelberg, 2002), pp. 1–13

    Google Scholar 

  32. C. Chrysostomou, A. Pitsillides, L. Rossides, M. Polycarpou, A. Sekercioglu, Congestion control in differentiated services networks using Fuzzy-RED. Special issue on control methods for telecommunication networks, IFAC Control Eng. Pract. J. 11(10), 1153–1170 (2003)

    Google Scholar 

  33. C. Chrysostomou, A. Pitsillides, A. Sekercioglu, Fuzzy explicit marking: a unified congestion controller for best-effort and diff-serv networks. Elsevier Comput. Netw. J. 53(5), 650–667 (2009)

    Article  MATH  Google Scholar 

  34. C. Chrysostomou, Fuzzy logic based AQM congestion control in TCP/IP networks. PhD thesis, University of Cyprus (2006), http://www.netrl.cs.ucy.ac.cy/images/thesis/chrysostomou-phd-thesis-sep06.pdf

  35. E.H. Mamdani, S. Assilian, An experiment in linguistic synthesis with a fuzzy logic controller. Int. J. Man Mach. Stud. 7(1), 1–13 (1975)

    Article  MATH  Google Scholar 

  36. OMNeT++ discrete event-based simulation framework. http://www.omnetpp.org

  37. C. Sommer, R. German, F. Dressler, Bidirectionally coupled network and road traffic simulation for improved IVC analysis. IEEE Trans. Mob. Comput. 10(1), 3–15 (2011)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Frederick University, Nicosia, Cyprus

    Chrysostomos Chrysostomou

  2. Department of Communication and Internet Studies, Cyprus University of Technology, Limassol, Cyprus

    Constantinos Djouvas & Lambros Lambrinos

Authors
  1. Chrysostomos Chrysostomou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Constantinos Djouvas
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lambros Lambrinos
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chrysostomos Chrysostomou .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, National University of Science and Technology (NUST), Islamabad, Pakistan

    Zeashan H Khan

  2. School of Engineering and Technology, CQ University, North Rockhampton, Queensland, Australia

    A. B. M. Shawkat Ali

  3. Fraunhofer Institute, Bonn, Germany

    Zahid Riaz

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media Singapore

About this chapter

Cite this chapter

Chrysostomou, C., Djouvas, C., Lambrinos, L. (2014). Fuzzy Logic-Based Adaptive Decision Support in Autonomous Vehicular Networks. In: Khan, Z., Ali, A., Riaz, Z. (eds) Computational Intelligence for Decision Support in Cyber-Physical Systems. Studies in Computational Intelligence, vol 540. Springer, Singapore. https://doi.org/10.1007/978-981-4585-36-1_7

Download citation

  • DOI: https://doi.org/10.1007/978-981-4585-36-1_7

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-4585-35-4

  • Online ISBN: 978-981-4585-36-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation