Average annual daily traffic (AADT) is perhaps the most fundamental measure of traffic flow. The data used to produce AADT estimates are typically collected by in-highway traffic counters operated by state Department of Transportation (DOT) traffic monitoring crews who must cover thousands of highway segments in their statewide systems on a continual basis. In-highway traffic counters can be dangerous to traffic crews and disruptive to traffic. In addition, the availability of limited resources, coupled with the large number of highway segments spread across the expansive geographic regions of the state, requires that the state DOTs can only collect short-term, sample volumes for the majority of the highway segments. Moreover, not all segments can be sampled every year, and some traffic counts will have been collected several years before the AADT of the segment is estimated. In a first year project, results of empirical studies demonstrated more accurate AADT estimation when using a proposed method to combine older, traditionally collected traffic count data with traffic information contained in more recently obtained air photos. Software components were also developed to allow many of the calculations to be performed automatically. Additional empirical studies were conducted this year, a refinement to the estimation of an important input value using image-based traffic information was developed, and proof-of-concept software was installed and used at the Ohio Department of Transportation.


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    Title :

    Incorporating Image-Based Traffic Information for AADT Estimation: Operational Developments for Agency Implementation and Theoretical Extensions to Classified AADT Estimation


    Contributors:
    M. R. McCord (author) / P. Goel (author)

    Publication date :

    2011


    Size :

    24 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English





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