Collective behavior in the North Rhine-Westphalia motorway network

Author:

Wang Shanshan,Gartzke Sebastian,Schreckenberg Michael,Guhr Thomas

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.

Publisher

IOP Publishing

Subject

Statistics, Probability and Uncertainty,Statistics and Probability,Statistical and Nonlinear Physics

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Response functions as a new concept to study local dynamics in traffic networks;Physica A: Statistical Mechanics and its Applications;2023-09

2. Transitions between quasi-stationary states in traffic systems: Cologne orbital motorways as an example;Journal of Statistical Mechanics: Theory and Experiment;2023-09-01

3. Identifying subdominant collective effects in a large motorway network;Journal of Statistical Mechanics: Theory and Experiment;2022-11-01

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