Traffic congestion has become an urban phenomenon which impedes urbanization in China. Its main cause is the imbalance between the demand and supply of temporal and spatial resource, i.e., the imbalance between the dramatically growing short-term traffic demand and the slowly improving traffic supply.
Team of Li Daqing from the School of Reliability and Systems Engineering of Beihang University and team of Gao Ziyou from Beijing Jiaotong University published their joint research results, titled “Switch between Critical Percolation Modes in City Traffic Dynamics”, in Proceedings of the National Academy of Sciences of the United States of America on 27th Dec, 2018, suggesting that two modes of different critical percolation behaviors are switching in the same network topology under different traffic dynamics. The research was supported by the National Natural Science Foundation of China (Grant Nos.71621001 and 71822101) and others.
Based on real-time high-resolution GPS data in Beijing and Shenzhen, the results indicate two distinct modes characterized by different percolation critical exponents. The mode during rush hours on working days behaves like a 2D lattice with mainly short-range links, while the mode for other instants behaves like a small world (i.e., a lattice with long-range links). The difference between these two modes is explained here by the free flow on urban highways during nonrush hours, which is like adding long-range links in a 2D lattice. In contrast, during rush hours, such links almost disappear. Generally, a network is linked to one percolation model, but by analyzing the cluster size distribution of city traffic, they found that the disintegration transition of urban traffic can be characterized by two sets of percolation critical exponents. They also found that with the aid of dynamic traffic management methods, it may be possible to shift the system to the desired critical universality class by adjusting the amount of effective long-range connections.
The first author of the article is Zeng Guanwen, a Ph.D. student of the School of Reliability and Systems Engineering. Guo Shengmin, a Ph.D. student of the School of Computer Science and Engineering, also contributed significantly to the paper. In recent years, Li Daqing's team has made continuous breakthroughs on the condensation of the basic issues of "traffic reliability" and excavating the space-time transmission rule of traffic congestion. Related researches were published in PNAS (2015, 2018) and Nature Communications (2016).
For more information of the research:
https://www.pnas.org/content/116/1/23
Reported by Luo Longfei
Edited by Jia Aiping
Reviewed by Bai Zhaoyu
Translated by Zhao Yue
