Congestion in cities causes fuel consumption to rise sharply, partly because of the longer time it takes to reach a destination, partly because the rate of consumption is much higher at low speeds. Existing traffic control systems do not cope well with heavily congested situations; essentially they were designed to respond to changes in moving traffic, not to the buildup of stopped traffic; and they assume that the supply of road space remains fixed, whereas congestion brings about a reduction in supply. This paper reports on a project which is evaluating the effectiveness of an artificial intelligence based supervisor for urban traffic control systems which aims to reduce congestion and hence fuel consumption.


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    Titel :

    Using artificial intelligence to reduce high fuel consumption in congested cities


    Beteiligte:
    Scemama, G. (Autor:in) / Fox, K. (Autor:in) / Walker, A. (Autor:in) / Bell, M.C. (Autor:in)

    Erscheinungsdatum :

    01.01.1996


    Format / Umfang :

    5 pages



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch




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