Spatial Correlation Analysis of Traffic Flow on Parallel Motorways in Germany

TL;DR

This study applies correlation matrix analysis to traffic flow data on parallel motorways in Germany, revealing strong temporal correlations and structural features that reflect daily traffic patterns and congestion states.

Contribution

It demonstrates the application of correlation analysis to traffic networks, uncovering structural features related to traffic states and daily patterns, advancing complex system understanding.

Findings

High positive correlation in traffic flow during rush hours

Structural features capture average traffic conditions

Correlations reflect daily traffic evolution

Abstract

With the widely used method of correlation matrix analysis, this study reveals the change of traffic states on parallel motorways in North Rhine-Westphalia, Germany. In terms of the time series of traffic flow and velocity, we carry out a quantitative analysis in correlations and reveal a high level of strongly positive traffic flow correlation and rich structural features in the corresponding correlation matrices. The strong correlation is mainly ascribed to the daily time evolution of traffic flow during the periods of rush hours and non-rush hours. In terms of free flow and congestion, the structural features are able to capture the average traffic situation we derive from our data. Furthermore, the structural features in correlation matrices for individual time periods corroborate our results from the correlation matrices regarding a whole day. The average correlations in traffic flows and velocities over all pairwise sections disclose the traffic behavior during each individual time period. Our contribution uncovers the potential application of correlation analysis on the study of traffic networks as a complex system.