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 publicationEngineering Self-Organising Systems - Third International Workshop, ESOA 2005, Revised Selected Papers
Pages182-196
Number of pages15
DOIs
Publication statusPublished - 2006 Jul 14
Event3rd International Workshop on Engineering Self-Organising Applicaions, ESOA 2005 - Utrecht, Netherlands
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)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Workshop on Engineering Self-Organising Applicaions, ESOA 2005
CountryNetherlands
CityUtrecht
Period05/7/2505/7/25

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Ando, Y., Masutani, O., Sasaki, H., Iwasaki, H., Fukazawa, Y., & Honiden, S. (2006). Pheromone model: Application to traffic congestion prediction. In Engineering Self-Organising Systems - Third International Workshop, ESOA 2005, Revised Selected Papers (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