Mustavee, Shakib (University of Central Florida), Kachroo, Pushkin (Transportation Research Center, UNLV), Agarwal, Shaurya (University of Central Florida)

An Extreme Value Theory Approach for Understanding Queue Length Dynamics in Adaptive Corridors

Scheduled for presentation during the Regular Session "Traffic Theory for ITS" (FrBT12), Friday, September 27, 2024, 15:10−15:30, Salon 20

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on December 26, 2024

Abstract

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.