Collective behavior in the North Rhine-Westphalia motorway network. (23rd December 2021)

• Record Type: Journal Article
• Authors: Wang, Shanshan; Gartzke, Sebastian; Schreckenberg, Michael; Guhr, Thomas
• Is Part Of: Journal of statistical mechanics. (2021:Dec.)
• Publication Date: 2021-12-23
• Subjects: correlation functions -- critical phenomena of socio-economic systems -- traffic and crowd dynamics -- socio-economic networks; Statistical mechanics -- Periodicals; Mechanics -- Statistical methods -- Periodicals; 530.1305
• DOI: 10.1088/1742-5468/ac3662
• Languages: English
• ISSNs: 1742-5468

Abstract

Abstract: To understand the dynamics on complex networks, measurement of correlations is indispensable. In a motorway network, it is not sufficient to collect information on fluxes and velocities on all individual links, i.e. parts of the freeways between ramps and highway crosses. The interdependencies and mutual connections are also of considerable interest. We analyze correlations in the complete motorway network in North Rhine-Westphalia, the most populous state in Germany. We view the motorway network as a complex system consisting of road sections which interact via the motion of vehicles, implying structures in the corresponding correlation matrices. In particular, we focus on collective behavior, i.e. coherent motion in the whole network or in large parts of it. To this end, we study the eigenvalue and eigenvector statistics and identify significant sections in the motorway network. We find collective behavior in these significant sections and further explore its causes. We show that collectivity throughout the network cannot directly be related to the traffic states (free, synchronous and congested) in Kerner's three-phase theory. Hence, the degree of collectivity provides a new, complementary observable to characterize the motorway network.