Information Sharing for Smooth Traffic in Road Networks

  • Tomohisa Yamashita
  • Kiyoshi Izumi
  • Koichi Kurumatani
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4012)


With maturation of ubiquitous computing technology, it has become feasible to design new systems to improve our urban life. In this paper, we introduce a new application for car navigation in a city. Every car navigation system in operation today has the current position of the vehicle, the destination, and the currently chosen route to the destination. If vehicles in a city could share this information, they could use traffic information to globally plan semi-optimal routes for each vehicle. Thus, we propose a cooperative car navigation system with route information sharing (RIS). In the RIS system, each vehicle transmits route information (current position, destination, and route to the destination) to a route information server, which estimates future traffic congestion using this information and feeds its estimate back to each vehicle. Each vehicle uses the estimation to re-plan their route. This cycle is then repeated. Our multiagent simulation confirmed the effectiveness of the proposed RIS system. The average travel time of drivers using the RIS system is substantially shorter than the time of drivers who chose shortest distance or simple shortest time estimates. Moreover, as the number of RIS users increases, the total amount of traffic congestion in the city decreases.


Travel Time Road Network Multiagent System Lattice Network Social Acceptability 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bazzan, A., Boffo, F., Klugl, F.: Avoiding the Braess Paradox with Information Manipulation. In: Proceedings of Workshop on Agents In Traffic And Transportation in Third International Joint Conference on Autonomous Agents and Multiagent Systems (ATT 2004), pp. 1–7 (2004)Google Scholar
  2. 2.
    Horiguchi, R., Kuwahara, M., Nishikawa, I.: The Model Validation of Traffic Simulation System for Urban Road Networks: ‘AVENUE’. In: Proceedings of the Second World Congress on Intelligent Transport Systems 1995, vol. (IV), pp. 1977–1982 (1995)Google Scholar
  3. 3.
    Inoue, M.: Current Overview of ITS in Japan. In: Proceedings of the 11th World Congress on Intelligent Transport Systems (CD-ROM) (2004)Google Scholar
  4. 4.
    Klugl, F., Bazzan, A.L.C., Wahle, J.: Selection of Information Types Based on Personal Utility: A Testbed for Traffic Information Markets. In: Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent systems, pp. 377–384 (2003)Google Scholar
  5. 5.
    Kurumatani, K.: Mass User Support by Social Coordination Among Citizens in a Real Environment. In: Kurumatani, K., Chen, S.-H., Ohuchi, A. (eds.) IJCAI-WS 2003 and MAMUS 2003. LNCS (LNAI), vol. 3012, pp. 1–19. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  6. 6.
    Kurumatani, K.: Social Coordination with Architecture for Ubiquitous Agents: CONSORTS. In: Proceedings of International Conference on Intelligent Agents, Web Technologies and Internet Commerce 2003 (CD-ROM) (2003)Google Scholar
  7. 7.
    Mahmassani, H.S., Jayakrishnan, R.: System Performance and User Response Under Real-Time Information in a Congested Traffic Corridor. Transportation Research 25A(5), 293–307 (1991)Google Scholar
  8. 8.
    Nakashima, H.: Grounding to the Real World – Architecture for Ubiquitous Computing. In: Zhong, N., Raś, Z.W., Tsumoto, S., Suzuki, E. (eds.) ISMIS 2003. LNCS (LNAI), vol. 2871, pp. 7–11. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  9. 9.
    Shiose, T., Onitsuka, T., Taura, T.: Effective Information Provision for Relieving Traffic Congestion. In: Proceedings of the 4th International Conference on Intelligence and Multimedia Applications, pp. 138–142 (2001)Google Scholar
  10. 10.
    Tanahashi, I., Kitaoka, H., Baba, M.H., Mori, H., Terada, S., Teramoto, E.: NETSTREAM, a Traffic Simulator for Large-scale Road Networks, R & D Review of Toyota CRDL, vol. 37(2), pp. 47–53 (2002) (in Japanese)Google Scholar
  11. 11.
    Teramoto, E., Baba, M., Mori, H., Asano, Y., Morita, H.: NETSTREAM: Traffic Simulator for Evaluating Traffic Information Systems. In: Proceedings of the IEEE International Conference on Intelligent Transportation Systems 1997 (CD-ROM) (1997)Google Scholar
  12. 12.
    Yoshii, T., Akahane, H., Kuwahara, M.: Impacts of the Accuracy of Traffic Information in Dynamic Route Guidance Systems. In: Proceedings of The 3rd Annual World Congress on Intelligent Transport Systems (CD-ROM) (1996)Google Scholar
  13. 13.
    Workshop on Ubiquitous Agents on embedded, wearable, and mobile devices, University of Bologna (July 16, 2002),
  14. 14.
  15. 15.

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Tomohisa Yamashita
    • 1
  • Kiyoshi Izumi
    • 1
  • Koichi Kurumatani
    • 1
  1. 1.Information Technology Research Institute (ITRI)National Institute of Advanced Industrial Science and Technology (AIST)TokyoJapan

Personalised recommendations