skip to main content
10.1145/1080754.1080761acmconferencesArticle/Chapter ViewAbstractPublication PagesmobicomConference Proceedingsconference-collections
Article

Assignment of dynamic transmission range based on estimation of vehicle density

Published:02 September 2005Publication History

ABSTRACT

Vehicular Ad Hoc Networks (VANET) have several characteristics that distinguish them from other ad hoc networks. Among those is the rapid change in topology due to traffic jams, which also disturbs the homogenous distribution of vehicles on the road. For this reason, a dynamic transmission range is more effective in maintaining connectivity while minimizing the adverse effects of a high transmission power.We provide a relationship that allows vehicles to estimate the local density and distinguish between two phases of traffic, free-flow and congested traffic. The density estimate is used to develop an algorithm that sets a vehicle transmission range dynamically according to local traffic conditions.Simulations of various road configurations show that the algorithm is successful in maintaining connectivity in highly dynamic networks.

References

  1. Ardekani, S. and Herman, R. 1987. Urban network-wide traffic variables and their relations. Transportation Science, 21, 1, 1--16.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Artimy, M. M., Robertson, W. and Phillips, W. J. 2004. Vehicle traffic microsimulator for ad hoc networks research. In Proceedings of International Workshop on Wireless Ad-Hoc Networks 2004. IEEE, Oulu, Finland.Google ScholarGoogle Scholar
  3. Arvelo, E. C. 2003. Open-loop power control based on estimations of packet error rate in a bluetooth radio. In Proceedings of Wireless Communications and Networking 2003, vol.3. 1465--1469.Google ScholarGoogle ScholarCross RefCross Ref
  4. Ashton, W. D. 1966. The theory of road traffic flow. London, New York, Methuen, Wiley.Google ScholarGoogle Scholar
  5. Chen, Z. D., Kung, H. T. and Vlah, D. 2001. Ad hoc relay wireless networks over moving vehicles on highways. In Proceedings of the 2nd ACM International Symposium on Mobile Ad Hoc Networking & Computing, Long Beach, CA, USA, 247--250. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Cheng, Y. -. and Robertazzi, T. G. 1989. Critical connectivity phenomena in multihop radio models. IEEE Transactions on Communications, 37, 7, 770--777.Google ScholarGoogle ScholarCross RefCross Ref
  7. Desai, M. and Manjunath, D. 2002. On the connectivity in finite ad hoc networks. IEEE Communications Letters, 6, 10, 437--439.Google ScholarGoogle ScholarCross RefCross Ref
  8. Dousse, O., Thiran, P. and Hasler, M. 2002. Connectivity in ad-hoc and hybrid networks. In Proceedings of Twenty-First Annual Joint Conference of IEEE Computer and Communications Societies, vol.2, 1079--1088.Google ScholarGoogle Scholar
  9. Füβler, H., Mauve, M., Hartenstein, H., Vollmer, D. and Käsemann, M. 2002. A comparison of routing strategies in vehicular ad-hoc networks. {Electronic version}. Reihe informatik. Retrieved July 22, 2005 from http://www.cn.uni-duesseldorf.de/publications/library/Fuessler2002b.pdfGoogle ScholarGoogle Scholar
  10. Gomez, J. and Campbell, A. T. 2004. A case for variable-range transmission power control in wireless multihop networks. In Proceedings of the Twenty-Third Annual Joint Conference of IEEE Computer and Communications Societies, vol.2. 1425--1436 vol.2.Google ScholarGoogle Scholar
  11. Haberman, R. 1977. Mathematical models : Mechanical vibrations, population dynamics, and traffic flow : An introduction to applied mathematics. Englewood Cliffs, N.J., Prentice-Hall.Google ScholarGoogle Scholar
  12. Hall, F. L. 1997. Traffic stream characteristics. In Traffic flow theory: A state of the art report - revised monograph on traffic flow theory, N. H. Gartner, C. Messer and A. K. Rathi, Eds., Oak Ridge, Tennessee, Oak Ridge National Laboratory.Google ScholarGoogle Scholar
  13. Jost, D. and Nagel, K. 2003. Probabilistic traffic flow breakdown in stochastic car following models. Transportation Research Record, 1852, 152--158.Google ScholarGoogle ScholarCross RefCross Ref
  14. Kosch, T., Schwingenschlogl, C. and Li Ai. 2002. Information dissemination in multihop inter-vehicle networks. In Proceedings of IEEE 5th International Conference on Intelligent Transportation Systems. 685--690.Google ScholarGoogle Scholar
  15. Krunz, M., Muqattash, A. and Sung-Ju Lee. 2004. Transmission power control in wireless ad hoc networks: Challenges, solutions and open issues. IEEE Network, 18, 5, 8--14. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Kuhne, R. and Michalopoulos, P. 1997. Continuum flow models. In Traffic flow theory: A state of the art report - revised monograph on traffic flow theory, N. H. Gartner, C. Messer and A. K. Rathi, Eds., Oak Ridge, Tennessee, Oak Ridge National Laboratory.Google ScholarGoogle Scholar
  17. Li, N., Hou, J. C. and Sha, L. 2003. Design and analysis of an MST-based topology control algorithm. In Proceedings of IEEE Twenty-Second Annual Joint Conference of the IEEE Computer and Communications Societies, vol.3. 1702--1712.Google ScholarGoogle Scholar
  18. Nagatani, T. 2002. The physics of traffic jams. Reports on Progress in Physics, 65, 9, 1331--1386.Google ScholarGoogle ScholarCross RefCross Ref
  19. Nagel, K., Wagner, P. and Woesler, R. 2003. Still flowing: Approaches to traffic flow and traffic jam modeling. Operations Research, 51, 5, 681--710. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Penrose, M. D. 1997. The longest edge of the random minimal spanning tree. The Annals of Applied Probability, 7, 2, 340--361.Google ScholarGoogle ScholarCross RefCross Ref
  21. Pipes, L. A. 1953. An operational analysis of traffic dynamics. Journal of Applied Physics, 24, 3, 274--281.Google ScholarGoogle ScholarCross RefCross Ref
  22. Pivovarov, E. Traffic jams. Retrieved March 22, 2005 from http://physics.ucsd.edu/~epivovar/traffic.htmGoogle ScholarGoogle Scholar
  23. Ramanathan, R. and Rosales-Hain, R. 2000. Topology control of multihop wireless networks using transmit power adjustment. In Proceedings of IEEE Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies, vol.2, 404--413.Google ScholarGoogle Scholar
  24. Rothery, R. W. 1997. Car-following models. In Traffic flow theory: A state of the art report - revised monograph on traffic flow theory, N. H. Gartner, C. Messer and A. K. Rathi, Eds., Oak Ridge, Tennessee, Oak Ridge National Laboratory.Google ScholarGoogle Scholar
  25. Rudack, M., Meincke, M. and Lott, M. 2002. On the dynamics of ad hoc networks for inter vehicles communications (IVC). In Proceedings of the 2002 International Conference on Wireless Networks. Las Vegas, USA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Rudack, M., Meincke, M., Jobmann, K. and Lott, M. 2003. On traffic dynamical aspects of inter vehicle communications (IVC). In Proceedings of IEEE 58th Vehicular Technology Conference, vol.5. 3368--3372.Google ScholarGoogle Scholar
  27. Santi, P. and Blough, D. M. 2002. An evaluation of connectivity in mobile wireless ad hoc networks. In Proceedings of International Conference on Dependable Systems and Networks. 89--98. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Assignment of dynamic transmission range based on estimation of vehicle density

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        VANET '05: Proceedings of the 2nd ACM international workshop on Vehicular ad hoc networks
        September 2005
        106 pages
        ISBN:1595931414
        DOI:10.1145/1080754

        Copyright © 2005 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 2 September 2005

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • Article

        Acceptance Rates

        Overall Acceptance Rate26of64submissions,41%

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader