Anticipatory Traffic Forecast Using Multi-Agent Techniques

J. Wahle, A. L. C. Bazzan, F. Klügl and M. Schreckenberg
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J. Wahle: Gerhard-Mercator-Universität, Physik von Transport und Verkehr
A. L. C. Bazzan: Universidade do Rio Grande do Sul, Instituto de Informática
F. Klügl: Universität Würzburg, Künstliche Intelligenz
M. Schreckenberg: Gerhard-Mercator-Universität, Physik von Transport und Verkehr

A chapter in Traffic and Granular Flow ’99, 2000, pp 87-92 from Springer

Abstract: Abstract In this contribution, intelligent transportation systems (ITS) and their impact on traffic systems are discussed. Although traffic forecast offers the possibility to rearrange the temporal distribution of traffic patterns, it suffers from a fundamental problem because the reaction of the driver to the forecast is a priori unknown. On the other hand the behaviour of drivers can have a serious impact on the quality of a traffic forecast since it can result in a feedback - an anticipatory forecast is needed. To include such effects we propose a two-layered agent architecture for modelling drivers’ behaviour in more detail. The layers distinguish different tasks of road users.

Keywords: MultiAgent System; Intelligent Transportation System; Road User; Route Guidance; Minority Game (search for similar items in EconPapers)
Date: 2000
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DOI: 10.1007/978-3-642-59751-0_8

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