Performance of pheromone model for predicting traffic congestion

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

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

    45 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 realizing intelligent transportation systems (ITS). Many of the current traffic management approaches require central processing with the usual risks of overload, bottlenecks and delay. Our work points towards a more decentralized approach that may overcome those risks. We use new category of the ITS infrastructure called the probe-car system. The probe-car system is an emerging data collection method, in which a number of vehicles are used as moving sensors to detect actual traffic situations. In this paper, a car is regarded as a social insect that deposits multi-semantics of (digital) pheromone on the basis of sensed traffic information. We have developed a basic model for predicting traffic congestion in the immediate future using pheromone. In the course of our experimentation, we have identified the need to properly tune the model to achieve acceptable performance. Therefore, we refined the model for practical use. We evaluate our method using real-world traffic data and results indicate applicability to prediction. Furthermore, we describe the practical implications of this method in the real world.

    Original languageEnglish
    Title of host publicationProceedings of the International Conference on Autonomous Agents
    Pages73-80
    Number of pages8
    Volume2006
    DOIs
    Publication statusPublished - 2006
    EventFifth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS - Hakodate
    Duration: 2006 May 82006 May 12

    Other

    OtherFifth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
    CityHakodate
    Period06/5/806/5/12

    Fingerprint

    Traffic congestion
    Railroad cars
    Deposits
    Semantics
    Sensors
    Processing

    Keywords

    • Pheromone
    • Traffic congestion prediction

    ASJC Scopus subject areas

    • Engineering(all)

    Cite this

    Ando, Y., Fukazawa, Y., Masutani, O., Iwasaki, H., & Honiden, S. (2006). Performance of pheromone model for predicting traffic congestion. In Proceedings of the International Conference on Autonomous Agents (Vol. 2006, pp. 73-80) https://doi.org/10.1145/1160633.1160642

    Performance of pheromone model for predicting traffic congestion. / Ando, Yasushi; Fukazawa, Yoshiaki; Masutani, Osamu; Iwasaki, Hirotoshi; Honiden, Shinichi.

    Proceedings of the International Conference on Autonomous Agents. Vol. 2006 2006. p. 73-80.

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

    Ando, Y, Fukazawa, Y, Masutani, O, Iwasaki, H & Honiden, S 2006, Performance of pheromone model for predicting traffic congestion. in Proceedings of the International Conference on Autonomous Agents. vol. 2006, pp. 73-80, Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, Hakodate, 06/5/8. https://doi.org/10.1145/1160633.1160642
    Ando Y, Fukazawa Y, Masutani O, Iwasaki H, Honiden S. Performance of pheromone model for predicting traffic congestion. In Proceedings of the International Conference on Autonomous Agents. Vol. 2006. 2006. p. 73-80 https://doi.org/10.1145/1160633.1160642
    Ando, Yasushi ; Fukazawa, Yoshiaki ; Masutani, Osamu ; Iwasaki, Hirotoshi ; Honiden, Shinichi. / Performance of pheromone model for predicting traffic congestion. Proceedings of the International Conference on Autonomous Agents. Vol. 2006 2006. pp. 73-80
    @inproceedings{70e210842c984d64918da2f3e8ba175c,
    title = "Performance of pheromone model for predicting traffic congestion",
    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 realizing intelligent transportation systems (ITS). Many of the current traffic management approaches require central processing with the usual risks of overload, bottlenecks and delay. Our work points towards a more decentralized approach that may overcome those risks. We use new category of the ITS infrastructure called the probe-car system. The probe-car system is an emerging data collection method, in which a number of vehicles are used as moving sensors to detect actual traffic situations. In this paper, a car is regarded as a social insect that deposits multi-semantics of (digital) pheromone on the basis of sensed traffic information. We have developed a basic model for predicting traffic congestion in the immediate future using pheromone. In the course of our experimentation, we have identified the need to properly tune the model to achieve acceptable performance. Therefore, we refined the model for practical use. We evaluate our method using real-world traffic data and results indicate applicability to prediction. Furthermore, we describe the practical implications of this method in the real world.",
    keywords = "Pheromone, Traffic congestion prediction",
    author = "Yasushi Ando and Yoshiaki Fukazawa and Osamu Masutani and Hirotoshi Iwasaki and Shinichi Honiden",
    year = "2006",
    doi = "10.1145/1160633.1160642",
    language = "English",
    isbn = "1595933034",
    volume = "2006",
    pages = "73--80",
    booktitle = "Proceedings of the International Conference on Autonomous Agents",

    }

    TY - GEN

    T1 - Performance of pheromone model for predicting traffic congestion

    AU - Ando, Yasushi

    AU - Fukazawa, Yoshiaki

    AU - Masutani, Osamu

    AU - Iwasaki, Hirotoshi

    AU - Honiden, Shinichi

    PY - 2006

    Y1 - 2006

    N2 - 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 realizing intelligent transportation systems (ITS). Many of the current traffic management approaches require central processing with the usual risks of overload, bottlenecks and delay. Our work points towards a more decentralized approach that may overcome those risks. We use new category of the ITS infrastructure called the probe-car system. The probe-car system is an emerging data collection method, in which a number of vehicles are used as moving sensors to detect actual traffic situations. In this paper, a car is regarded as a social insect that deposits multi-semantics of (digital) pheromone on the basis of sensed traffic information. We have developed a basic model for predicting traffic congestion in the immediate future using pheromone. In the course of our experimentation, we have identified the need to properly tune the model to achieve acceptable performance. Therefore, we refined the model for practical use. We evaluate our method using real-world traffic data and results indicate applicability to prediction. Furthermore, we describe the practical implications of this method in the real world.

    AB - 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 realizing intelligent transportation systems (ITS). Many of the current traffic management approaches require central processing with the usual risks of overload, bottlenecks and delay. Our work points towards a more decentralized approach that may overcome those risks. We use new category of the ITS infrastructure called the probe-car system. The probe-car system is an emerging data collection method, in which a number of vehicles are used as moving sensors to detect actual traffic situations. In this paper, a car is regarded as a social insect that deposits multi-semantics of (digital) pheromone on the basis of sensed traffic information. We have developed a basic model for predicting traffic congestion in the immediate future using pheromone. In the course of our experimentation, we have identified the need to properly tune the model to achieve acceptable performance. Therefore, we refined the model for practical use. We evaluate our method using real-world traffic data and results indicate applicability to prediction. Furthermore, we describe the practical implications of this method in the real world.

    KW - Pheromone

    KW - Traffic congestion prediction

    UR - http://www.scopus.com/inward/record.url?scp=34247241149&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=34247241149&partnerID=8YFLogxK

    U2 - 10.1145/1160633.1160642

    DO - 10.1145/1160633.1160642

    M3 - Conference contribution

    AN - SCOPUS:34247241149

    SN - 1595933034

    SN - 9781595933034

    VL - 2006

    SP - 73

    EP - 80

    BT - Proceedings of the International Conference on Autonomous Agents

    ER -