Pheromone model

Application to traffic congestion prediction

Yasushi Ando, Osamu Masutani, Hiroshi Sasaki, Hirotoshi Iwasaki, Yoshiaki Fukazawa, Shinichi Honiden

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    15 Citations (Scopus)

    Abstract

    Social insects perform complex tasks without top-down style control, by sensing and depositing chemical markers called "pheromone". We have examined applications of this pheromone paradigm towards intelligent transportation systems (ITS). Many of the current traffic management approaches require central processing with the usual risk for overload, bottlenecks and delays. Our work points towards a more decentralized approach that may overcome those risks. In this paper, a car is regarded as a social insect that deposits (electronic) pheromone on the road network. The pheromone represents density of traffic. We propose a method to predict traffic congestion of the immediate future through a pheromone mechanism without resorting to the use of a traffic control center. We evaluate our method using a simulation based on real-world traffic data and the results indicate applicability to prediction of immediate future traffic congestion. Furthermore, we describe the relationship between pheromone parameters and accuracy of prediction.

    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Pages182-196
    Number of pages15
    Volume3910 LNAI
    DOIs
    Publication statusPublished - 2006
    Event3rd International Workshop on Engineering Self-Organising Applicaions, ESOA 2005 - Utrecht
    Duration: 2005 Jul 252005 Jul 25

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume3910 LNAI
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other3rd International Workshop on Engineering Self-Organising Applicaions, ESOA 2005
    CityUtrecht
    Period05/7/2505/7/25

    Fingerprint

    Traffic Congestion
    Traffic congestion
    Pheromone
    Pheromones
    Prediction
    Traffic control
    Social Insects
    Railroad cars
    Deposits
    Insects
    Processing
    Traffic
    Model
    Intelligent Transportation Systems
    Traffic Management
    Traffic Control
    Road Network
    Overload
    Decentralized
    Sensing

    ASJC Scopus subject areas

    • Computer Science(all)
    • Biochemistry, Genetics and Molecular Biology(all)
    • Theoretical Computer Science

    Cite this

    Ando, Y., Masutani, O., Sasaki, H., Iwasaki, H., Fukazawa, Y., & Honiden, S. (2006). Pheromone model: Application to traffic congestion prediction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3910 LNAI, pp. 182-196). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3910 LNAI). https://doi.org/10.1007/11734697_14

    Pheromone model : Application to traffic congestion prediction. / Ando, Yasushi; Masutani, Osamu; Sasaki, Hiroshi; Iwasaki, Hirotoshi; Fukazawa, Yoshiaki; Honiden, Shinichi.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3910 LNAI 2006. p. 182-196 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3910 LNAI).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Ando, Y, Masutani, O, Sasaki, H, Iwasaki, H, Fukazawa, Y & Honiden, S 2006, Pheromone model: Application to traffic congestion prediction. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 3910 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3910 LNAI, pp. 182-196, 3rd International Workshop on Engineering Self-Organising Applicaions, ESOA 2005, Utrecht, 05/7/25. https://doi.org/10.1007/11734697_14
    Ando Y, Masutani O, Sasaki H, Iwasaki H, Fukazawa Y, Honiden S. Pheromone model: Application to traffic congestion prediction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3910 LNAI. 2006. p. 182-196. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/11734697_14
    Ando, Yasushi ; Masutani, Osamu ; Sasaki, Hiroshi ; Iwasaki, Hirotoshi ; Fukazawa, Yoshiaki ; Honiden, Shinichi. / Pheromone model : Application to traffic congestion prediction. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3910 LNAI 2006. pp. 182-196 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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