Modeling Spacing Distribution of Queuing Vehicles in Front of a Signalized Junction Using Random-Matrix Theory

TL;DR

This paper introduces a novel model using random-matrix theory to analyze the spacing distribution of queuing vehicles at signalized junctions, revealing that their distribution aligns with the Gaussian symplectic ensemble, differing from free-flow traffic models.

Contribution

It applies random-matrix theory to model queuing vehicle spacing at signalized junctions, a novel approach in traffic flow analysis.

Findings

Spacing distribution fits Gaussian symplectic ensemble (GSE)

Queuing vehicles differ from free-flow vehicles in spacing distribution

Driving patterns influence the type of spacing distribution

Abstract

Modeling of headway/spacing between two consecutive vehicles has many applications in traffic flow theory and transport practice. Most known approaches only study the vehicles running on freeways. In this paper, we propose a model to explain the spacing distribution of queuing vehicles in front of a signalized junction based on random-matrix theory. We show that the recently measured spacing distribution data well fit the spacing distribution of a Gaussian symplectic ensemble (GSE). These results are also compared with the spacing distribution observed for car parking problem. Why vehicle-stationary-queuing and vehicle-parking have different spacing distributions (GSE vs GUE) seems to lie in the difference of driving patterns.