Mustavee, Shakib (University of Central Florida), Agarwal, Shaurya (University of Central Florida)

Self-Similar Characteristics in Queue Length Dynamics: Insights from Adaptive Signalized Corridor

Scheduled for presentation during the Regular Session "Traffic Theory for ITS" (FrBT12), Friday, September 27, 2024, 14:10−14:30, 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 October 14, 2024

Abstract

Self-similarity, a fractal characteristic of traffic flow dynamics, is widely recognized in transportation engineering and physics. However, its practical application in real-world traffic scenarios remains limited. Conversely, the traffic flow dynamics at adaptive signalized intersections still need to be fully understood. This paper addresses this gap by analyzing the queue length time series from an adaptive signalized corridor and characterizing its self-similarity. The findings uncover a 1/f structure in the power spectrum of queue lengths, indicative of self-similarity. Furthermore, the paper estimates local scaling exponents (α), a measure of self-similarity computed via detrended fluctuation analysis (DFA), and identifies a positive correlation with congestion patterns. Additionally, the study examines the fractal dynamics of queue length through the evolution of scaling exponent. As a result, the paper offers new insights into the queue length dynamics of signalized intersections, which might help better understand the impact of adaptivity within the system.