The goal of an Advanced Traffic Management System (ATMS) is to efficiently manage transportation resources in response to dynamic traffic conditions. The utility of an ATMS will greatly depend upon its ability to adaptively respond to traffic demands, patterns and permutations. Traffic management systems have historically been limited to addressing the control of street signal lights. Algorithmic solutions to this problem have proved to be very restrictive, while expert system solutions have only shown valid results with small signal networks. None of these approaches has addressed the need for management of the overall transportation system of surface streets, interstate highways, public transportation, and emergency vehicle coordination. The volume of traffic combined with the number of streets and intersections an operator control station must monitor clearly dictates the need for computer support. The application of knowledge-based systems and neural networks provides an ATMS with the technology required to control traffic in an intelligent manner. Integrating these technologies with existing transportation methodologies produces a semi-autonomous system capable of reducing operator workloads while maintaining high levels of safety. This paper describes an intelligent traffic management control system called TERMINUS developed to adaptively respond to real-time traffic management problems.


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    Titel :

    TERMINUS: A KNOWLEDGE-BASED TRAFFIC MANAGEMENT SYSTEM


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    1995-01-01


    Format / Umfang :

    27 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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