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International Conference on Principles and Practice of Multi-Agent Systems

PRIMA 2009: Principles of Practice in Multi-Agent Systems pp 487–499Cite as

Interpolation System of Traffic Condition by Estimation/Learning Agents

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5925))

Abstract

Interpolation system of traffic condition is proposed, which consists of estimation and learning agents. To evaluate the interpolation accuracy, coefficient of determination (CD) and mean square error (MSE) are used. The interpolation accuracy can be improved by the alternate use of estimation and learning agents, and the iterative uses of the same probe data. The standard deviation of the normalized velocity can be improved to 0.1353, and that of the velocity is 6.77 km/h in the mid velocity region. Furthermore, the CD and MSE could be improved by the additional repetition of estimation and learning.

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References

  1. Ando, Y., Fukazawa, Y., Masutani, O., Iwasaki, H., Honiden, S.: Performance of Pheromone Model for Predicting Traffic Congestion. In: Proc. of the fifth international joint conference on Autonomous agents and multiagent systems, pp. 73–80 (2006)

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  3. Kumagai, M., Fushiki, T., Kimita, K., Yokota, T.: Spatial Interpolation of Real-time Floating Car Data Based on Multiple Link Correlation in Feature Space. In: Proc. of 13th World Congress of ITS, London, CD-ROM (October 2006)

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Author information

Authors and Affiliations

  1. Information & Communication Laboratories, Sumitomo Electric Industries, Ltd., 1-1-3, Shimaya, Konohana-ku, Osaka, 554-0024, Japan

    Tetsuo Morita, Junji Yano & Kouji Kagawa

Authors
  1. Tetsuo Morita
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  2. Junji Yano
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  3. Kouji Kagawa
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Editor information

Editors and Affiliations

  1. School of Computer Science and Information Engineering, The Catholic University of Korea, Bucheon, South Korea

    Jung-Jin Yang

  2. Faculty of Information Science and Electrical Engineering, Department of Informatics, Kyushu University, 744 Motooka, Nishi-ku, 819-0395, Fukuoka, Japan

    Makoto Yokoo

  3. School of Techno-Business Administration, Dept. of Computer Science, Nagoya Institute of Technology, Gokiso, Showa-ku, 466-8555, Nagoya, Japan

    Takayuki Ito

  4. School of Electronic Engineering and Computer Science, Peking University, No. 5 Yiheyuan Road, 100871, Beijing, China

    Zhi Jin

  5. Robotics Institute, Carnegie Mellon University, 5000 Forbes Avenue, 15213, Pittsburgh, PA, USA

    Paul Scerri

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© 2009 Springer-Verlag Berlin Heidelberg

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Cite this paper

Morita, T., Yano, J., Kagawa, K. (2009). Interpolation System of Traffic Condition by Estimation/Learning Agents. In: Yang, JJ., Yokoo, M., Ito, T., Jin, Z., Scerri, P. (eds) Principles of Practice in Multi-Agent Systems. PRIMA 2009. Lecture Notes in Computer Science(), vol 5925. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11161-7_34

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  • DOI: https://doi.org/10.1007/978-3-642-11161-7_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11160-0

  • Online ISBN: 978-3-642-11161-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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