"IDUTC: An intelligent decision-making system for urban traffic-control applications.
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Article : [ART156]

Info : REPONSE 4, le 04/02/2002.

Titre : IDUTC: An intelligent decision-making system for urban traffic-control applications.

Cité dans : [DIV313]  Recherche sur l'auteur Narayanaswani RANGANATHAN, février 2002.
Auteur : Patel, M. (HSSCSD, Clearwater, FL 33764, United States)
Auteur : Ranganathan, N.

Source : IEEE Transactions on Vehicular Technology v 50 n 3 May 2001 2001.p 816-829
ISSN : 0018-9545
Année : 2001
Document_Type : Journal
Treatment_Code : Theoretical
Language : English
Stockage :

Abstract :
The design of systems for intelligent control of urban traffic is important in providing a safe environment for
pedestrians and motorists. Artificial neural networks (ANNs) (learning systems) and expert systems
(knowledge-based systems) have been extensively explored as approaches for decision making. While the
ANNs compute decisions by learning from successfully solved examples, the expert systems rely on a
knowledge base developed by human reasoning for decision making. It is possible to integrate the learning
abilities of an ANN and the knowledge-based decision-making ability of the expert system. This paper
presents a real-time intelligent decision making system, IDUTC, for urban traffic control applications. The
system integrates a backpropagation-based ANN that can learn and adapt to the dynamically changing
environment and a fuzzy expert system for decision making. The performance of the proposed intelligent
decision-making system is evaluated by mapping the the adaptable traffic light control problem. The
application is implemented using the ANN approach, the FES approach, and the proposed integrated system
approach. The results of extensive simulations using the three approaches indicate that the integrated system
provides better performance and leads to a more efficient implementation than the other two approaches. 29

Accession_Number : 2001(38):163 COMPENDEX

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