This paper presents a methodology for incorporating freeway reliability analysis in the Highway Capacity Manual on the basis of Strategic Highway Research Program Project L08. The methodology uses a scenario-based approach in which each scenario represents a unique combination of traffic demands and facility (segment) capacities. Demand impacts consider variability in time-of-day, day-of-week, and month-of-year differences, and capacity impacts quantify effects of various nonrecurring congestion sources, such as weather, incidents, work zones, and special events. The method combines three key components: a data repository, a freeway scenario generator (FSG), and a computational software engine, FREEVAL-RL. The FSG determines the number of scenarios for the reliability analysis on the basis of the facility-specific combination of demand, incident, and weather events. For each scenario, it produces a set of inputs and adjustment factors that are passed on to the FREEVAL-RL engine, along with each scenario's probability. The engine is capable of batch-processing many scenarios and estimates the reliability distribution for the facility. At the core, the computational engine and underlying methodology are consistent with the freeway facilities method in the Highway Capacity Manual 2010, which is capable of estimating undersaturated and congested flow conditions in a multi-period analysis. The method is illustrated with a real-world case study freeway facility in North Carolina. The FSG for that facility resulted in 2,508 scenarios. The resulting travel time distribution is presented, and sensitivity analyses are presented to explore the contributing effects of weather and incidents on the overall reliability of the facility.


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    Title :

    Deterministic Framework and Methodology for Evaluating Travel Time Reliability on Freeway Facilities


    Additional title:

    Transportation Research Record




    Publication date :

    2013-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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