Moment analysis of highway-traffic clearance distribution

TL;DR

This study analyzes inter-vehicle spacings on a highway to understand traffic phase transitions, revealing that higher moments like skewness and kurtosis are sensitive indicators of critical points in traffic flow.

Contribution

It introduces a moment analysis approach to traffic data, showing how higher moments signal phase transitions and critical densities in highway traffic.

Findings

Variance increases with mean vehicle spacing

Skewness and kurtosis peak at critical densities

Higher moments are sensitive probes for traffic phase transitions

Abstract

To help with the planning of inter-vehicular communication networks, an accurate understanding of traffic behavior and traffic phase transition is required. We calculate inter-vehicle spacings from empirical data collected in a multi-lane highway in California, USA. We calculate the correlation coefficients for spacings between vehicles in individual lanes to show that the flows are independent. We determine the first four moments for individual lanes at regular time intervals, namely the mean, variance, skewness and kurtosis. We follow the evolution of these moments as the traffic condition changes from the low-density free flow to high-density congestion. We find that the higher moments of inter-vehicle spacings have a well defined dependence on the mean value. The variance of the spacing distribution monotonously increases with the mean vehicle spacing. In contrast, our analysis suggests that the skewness and kurtosis provide one of the most sensitive probes towards the search for the critical points. We find two significant results. First, the kurtosis calculated in different time intervals for different lanes varies smoothly with the skewness. They share the same behavior with the skewness and kurtosis calculated for probability density functions that depend on a single parameter. Second, the skewness and kurtosis as functions of the mean intervehicle spacing show sharp peaks at critical densities expected for transitions between different traffic phases. The data show a considerable scatter near the peak positions, which suggests that the critical behavior may depend on other parameters in addition to the traffic density.