  This paper introduces a novel approach employing extreme value theory to
analyze queue lengths within a corridor controlled by adaptive controllers. We
consider the maximum queue lengths of a signalized corridor consisting of nine
intersections every two minutes, roughly equivalent to the cycle length. Our
research shows that maximum queue lengths at all the intersections follow the
extreme value distributions. To the best knowledge of the authors, this is the
first attempt to characterize queue length time series using extreme value
analysis. These findings are significant as they offer a mechanism to assess
the extremity of queue lengths, thereby aiding in evaluating the effectiveness
of the adaptive signal controllers and corridor management. Given that extreme
queue lengths often precipitate spillover effects, this insight can be
instrumental in preempting such scenarios.
