Spatial correlation analysis of traffic flow on parallel motorways in Germany

Sebastian Gartzke, Shanshan Wang, Thomas Guhr and Michael Schreckenberg

Physica A: Statistical Mechanics and its Applications, 2022, vol. 599, issue C

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.

Keywords: Correlation matrix; Time series analysis; Vehicular traffic; Traffic state; Complex system; Road network (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:599:y:2022:i:c:s0378437122002850

DOI: 10.1016/j.physa.2022.127367

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