Skip to main content

The Effect of Congestion Frequency and Saturation on Coordinated Traffic Routing

  • Conference paper
  • 1052 Accesses

Part of the Lecture Notes in Computer Science book series (LNAI,volume 7047)

Abstract

Traffic congestion is a widespread epidemic that continually wreaks havoc in urban areas. Traffic jams, car wrecks, construction delays, and other causes of congestion, can turn even the biggest highways into a parking lot. Several congestion mitigation strategies are being studied, many focusing on micro-simulation of traffic to determine how modifying road structures will affect the flow of traffic and the networking perspective of vehicle-to-vehicle communication. Vehicle routing on a network of roads and intersections can be modeled as a distributed constraint optimization problem and solved using a range of centralized to decentralized techniques. In this paper, we present a constraint optimization model of a traffic routing problem. We produce congestion data using a sinusoidal wave pattern and vary its amplitude (saturation) and frequency (vehicle waves through a given intersection). Through empirical evaluation, we show how a centralized and decentralized solution each react to unknown congestion information that occurs after the initial route planning period.

Keywords

  • routing
  • coordination
  • constraint optimization

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-642-25044-6_16
  • Chapter length: 15 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   79.99
Price excludes VAT (USA)
  • ISBN: 978-3-642-25044-6
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   99.99
Price excludes VAT (USA)

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Administration, F.H.: Traffic analysis toolbox volume iii: Guidelines for applying traffic microsimulation modeling software. Tech. Rep. FHWA-HRT-04-040, USDoT (2004)

    Google Scholar 

  2. Balbo, F., Pinson, S.: An agent oriented approach to transportation regulation support systems. In: Proceedings of the 5th Workshop in Agent in Traffic and Transport (2008), http://www.lamsade.dauphine.fr/FILES/publi931.pdf

  3. Bazzan, A.L.C.: Opportunities for multiagent systems and multiagent reinforcement learning in traffic control. AAMAS 18(3), 342–375 (2009), http://www.inf.ufrgs.br/~bazzan/%23pub

    Google Scholar 

  4. Ben-Akiva, M.: Development of a deployable real-time dynamic traffic assignment system, task d interim report: analytical developments for dta system. Tech. rep., MIT ITS Program, Cambridge, MA (1996)

    Google Scholar 

  5. Cambridge Systematics Inc.: Traffic congestion and reliability: Trends and advanced strategies for congestion mitigation pp. 1–140 (September 2005)

    Google Scholar 

  6. Conceição, H., Damas, L., Ferreira, M., Barros, J.: The divert project: Development of inter-vehicular reliable telematics. OSGeo Journal 3, 51–56 (2007), http://www.dcc.fc.up.pt/~michel/homepage/publications/2007-OSGeo-2.html

    Google Scholar 

  7. Conceição, H., Ferreira, M., Barros, J.: On the Urban Connectivity of Vehicular Sensor Networks. In: Nikoletseas, S.E., Chlebus, B.S., Johnson, D.B., Krishnamachari, B. (eds.) DCOSS 2008. LNCS, vol. 5067, pp. 112–125. Springer, Heidelberg (2008), http://www.dcc.fc.up.pt/~michel/homepage/publications/2008-DCOSS.html

    CrossRef  Google Scholar 

  8. Hart, P.E., Nilsson, N.J., Raphael, B.: A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions of Systems Science and Cybernetics 4(2), 100–108 (1968)

    CrossRef  Google Scholar 

  9. Horling, B., Mailler, R., Lesser, V.: Farm: A Scalable Environment for Multi-Agent Development and Evaluation. In: Lucena, C., Garcia, A., Romanovsky, A., Castro, J., Alencar, P.S.C. (eds.) SELMAS 2003. LNCS, vol. 2940, pp. 225–242. Springer, Heidelberg (2004)

    CrossRef  Google Scholar 

  10. Otto, J.S., Bustamante, F.E.: Distributed or centralized traffic advisory systems - the application’s take. In: SECON, pp. 1–10 (September 2009)

    Google Scholar 

  11. Wahle, J., Schreckenberg, M.: A multi-agent system for online simulations based on real-world traffic data. In: 34th Hawaii Int’l Conf. on System Sciences (2001), http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=926332

  12. Wunderlich, K.E., Kaufman, D.E., Smith, R.L.: Link travel time prediction for decentralized route guidance architectures. IEEE Transactions on Intelligent Transportation Systems, 4–14 (March 2000)

    Google Scholar 

  13. Yamashita, T., Kurumatani, K.: New approach to smooth traffic flow with route information sharing. In: Bazzan, A., Klugl, F. (eds.) Multi-Agent Systems for Traffic and Transportation Engineering, pp. 291–306. IGI Global (2009)

    Google Scholar 

  14. Yokoo, M., Durfee, E.H.: Distributed constraint optimization as a formal model of partially adversarial cooperation. Tech. Rep. CSE-TR-101-91, University of Michigan, Ann Arbor, MI 48109 (1991)

    Google Scholar 

  15. Zhang, W., Wang, G., Wittenburg, L.: Distributed stochastic search for constraint satisfaction and optimization: Parallelism, phase transitions and performance. In: Proceedings of the AAAI Workshop on Probabilistic Approaches in Search (2002)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Smith, M., Mailler, R. (2011). The Effect of Congestion Frequency and Saturation on Coordinated Traffic Routing. In: Kinny, D., Hsu, J.Yj., Governatori, G., Ghose, A.K. (eds) Agents in Principle, Agents in Practice. PRIMA 2011. Lecture Notes in Computer Science(), vol 7047. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25044-6_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-25044-6_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25043-9

  • Online ISBN: 978-3-642-25044-6

  • eBook Packages: Computer ScienceComputer Science (R0)