Maintaining efficient transportion systems has become a key goal for government-based transportation agencies in this age of serious energy shortages, rising costs and competing recipients of public funds. The emphasis has shifted to optimizing traffic movement on the existing surface street network rather than to provide more freeways. As described by Schnabel and Lohse (1997), the network capacity is limited by intersections. In this paper, the authors present an approach to automated optimization of traffic signal operation. They present a problem decomposition end encording for the use of different traffic models as well as a variety of optimization tools. First experimental results show that an automated design and optimization of intersection signal operations is not only possible but yields good results. This paves the way for on-line self-adapting signal operation: combined with a traffic observation system it is not only possible to react to short-term variations in traffic flow but also to adapt to long-term changes of the situation.


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    Titel :

    Evolutionary algorithms for optimizing traffic signal operation


    Weitere Titelangaben:

    Genetische Algorithmen zur Optimierung der Arbeit von Verkehrssignalen


    Beteiligte:
    Vogel, A. (Autor:in) / Goerick, C. (Autor:in) / Seelen, W. von (Autor:in)


    Erscheinungsdatum :

    2000


    Format / Umfang :

    9 Seiten, 6 Bilder, 9 Quellen


    Anmerkungen:

    (nicht pagniniert)



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Datenträger


    Sprache :

    Englisch




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