A certain amount of delay in work zones is typically assumed to be unavoidable and often considered a cost of doing business when roadway improvements are in progress. Therefore, developing a method to predict delay, such that appropriate countermeasures to minimize delay can be implemented, is critical to successful work zone management. Predicting work zone delay in an effective and efficient manner should not require extensive data collection or long, complex coding efforts. The procedure should be customizable for local data availability, easy to use, and, for practitioners, easy to interpret. To this end, the Work Zone Capacity Analysis Tool (WZCAT) analytical software program was developed to predict delays and queues for short-term (daily) work zone closures. WZCAT queue-length predictions are based on a simple input-output model, with capacity of the work zone controlling the throughput. The purpose of this study was to evaluate and enhance WZCAT with field data as well as summarize various aspects of traffic flow and queuing patterns during work zone operations on selected urban freeways. Findings from field observations were significant traffic volume changes on exit and entrance terminals upstream of work zones and the stabilization of vehicle queue after initial queue development. A demand-adjust factor was developed and applied to WZCAT-R for effectiveness and efficiency. WZCAT-R produces effective results for queue prediction. It can be an effective and reliable tool in predicting work zone delay and queue development. The tool can also help engineers proactively plan work phasing, lane restrictions, and potential detour routes to move traffic more efficiently.


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    Title :

    Development of Traffic Delay Assessment Tool for Short-Term Closures on Urban Freeways


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2008-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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