This report describes the development of operational surveillance data processing algorithms and software for application to urban freeway systems, conforming to a framework in which data processing is performed in stages: sensor malfunction detection, data repair, calibration, qualitative modeling of traffic conditions, and, finally, discrimination of incidents from recurrent congestion. Development and testing used real data obtained from freeway systems in Oakland, CA, San Diego, CA and the Twin Cities in Minnesota. Statistical pattern recognition techniques. including optimal decisions trees and neural nets were used. The algorithms and software produced are designed for integration into real-time traffic management systems. This Executive Summary provides an overview of these developments. This document is intended for local traffic management authorities responsible for operating and/or planning freeway incident and response capabilities. at locations where such capabilities are in place or are being considered for deployment.


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    Title :

    Development and Testing of Operational Incident Detection Algorithms: Executive Summary


    Contributors:
    H. J. Payne (author)

    Publication date :

    1997


    Size :

    23 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English






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