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    Intelligent traffic control decision support system

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    Publication date
    2007
    Author
    Almejalli, Khaled A.
    Dahal, Keshav P.
    Hossain, M. Alamgir
    Keyword
    Traffic management
    Decision support systems
    Fuzzy logic
    Rights
    © 2007 Springer-Verlag. Reproduced in accordance with the publisher's self-archiving policy.
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    When non-recurrent road traffic congestion happens, the operator of the traffic control centre has to select the most appropriate traffic control measure or combination of measures in a short time to manage the traffic network. This is a complex task, which requires expert knowledge, much experience and fast reaction. There are a large number of factors related to a traffic state as well as a large number of possible control measures that need to be considered during the decision making process. The identification of suitable control measures for a given non-recurrent traffic congestion can be tough even for experienced operators. Therefore, simulation models are used in many cases. However, simulating different traffic scenarios for a number of control measures in a complicated situation is very time-consuming. In this paper we propose an intelligent traffic control decision support system (ITC-DSS) to assist the human operator of the traffic control centre to manage online the current traffic state. The proposed system combines three soft-computing approaches, namely fuzzy logic, neural network, and genetic algorithm. These approaches form a fuzzy-neural network tool with self-organization algorithm for initializing the membership functions, a GA algorithm for identifying fuzzy rules, and the back-propagation neural network algorithm for fine tuning the system parameters. The proposed system has been tested for a case-study of a small section of the ring-road around Riyadh city. The results obtained for the case study are promising and show that the proposed approach can provide an effective support for online traffic control.
    URI
    http://hdl.handle.net/10454/2554
    Version
    Accepted Manuscript
    Citation
    Almejalli, K. A., Dahal, K. P. and Hossain, M. A. (2007) Intelligent traffic control decision support system. In: Applications of evolutionary computing. Proceedings of the EvoWorkshops 2007 (EvoTransLog Workshop), Valencia, Spain, April 11-13, 2007. Heidelberg: Springer. pp. 688-701.
    Link to publisher’s version
    http://www.springerlink.com/
    Type
    Conference paper
    Collections
    Engineering and Informatics Publications

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