An adaptive traffic control system, the Sydney Coordinated Adaptive Traffic System (SCATS), was installed in Park City, Utah, to improve traffic performance at its network of signalized intersections. A field evaluation of the previous time-of-day actuated–coordinated signal timings was conducted before SCATS installation to compare the two systems. However, the post-SCATS field evaluation could not occur until two additional signals were installed and several other changes were made to the network. Two years after the original pre-SCATS field evaluation, the network was reevaluated with an off–on technique analogous to a before–after study. The signal timings and parameters in the off condition forced SCATS to use time-of-day actuated–coordinated control, similar to the before study but with timings readjusted for the additional signals and changed traffic conditions. The performance gains with SCATS on were measurably greater than those with SCATS off for travel time and number of stops and greater overall for stopped delay. These data provided the transportation agency with results anticipated by its traffic engineers. However, the original field evaluation data from 2 years earlier provided a less distinct conclusion. A methodology is presented to determine the relevance of an off–on study in place of a before–after study. The results show that “before” and “off ” data sets behave consistently 62.5% of the time. This value provides a basis of support for using off data, which better represent before signal timings on an after network. It also quantifies sensitivity to changes in the network, which are substantial in this case.


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    Title :

    Comparison of Before–After versus Off–On Adaptive Traffic Control Evaluations


    Subtitle :

    Park City, Utah, Case Study


    Additional title:

    Transportation Research Record


    Contributors:


    Publication date :

    2009-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English