Widespread Traffic Congestion Prediction for Urban Road Network Based on Synergetic Theory

Zhang Liangliang (), Jia Yuanhua (), Niu Zhonghai and Liao Cheng
Additional contact information
Zhang Liangliang: Institute of System Engineering and Control School of Traffic and Transportation, Beijing Jiaotong University, Beijing100044, China
Jia Yuanhua: Institute of System Engineering and Control School of Traffic and Transportation, Beijing Jiaotong University, Beijing100044, China
Niu Zhonghai: Institute of System Engineering and Control School of Traffic and Transportation, Beijing Jiaotong University, Beijing100044, China
Liao Cheng: Institute of System Engineering and Control School of Traffic and Transportation, Beijing Jiaotong University, Beijing100044, China

Journal of Systems Science and Information, 2014, vol. 2, issue 4, 366-371

Abstract: The traffic congestion often occurs in urban road network. When one of the sections becomes congested, it will lead to a series of congestions in other sections. The traffic congestion spreads rapidly until part of road network becomes congestion ultimately. In this case, the paper investigates the mechanism of the traffic congestion in urban road network and points out that subsystems of the traffic congestion always perform completive and cooperative functions in the process of traffic congestion. The process behaves in a manner of self-organized criticality, which can be forecasted. The paper also establishes synergetic predictive models based on self-organized criticality of the synergetic theory. Finally, the paper takes Beijing road network as an example to forecast the widespread traffic congestion. The result shows that the established models are accuracy, and the traffic congestion is featured of self-organized criticality.

Keywords: urban road network; traffic congestion; self-organized criticality; synergetic theory; predictive model (search for similar items in EconPapers)
Date: 2014
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/JSSI-2014-0366 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:jossai:v:2:y:2014:i:4:p:366-371:n:7

DOI: 10.1515/JSSI-2014-0366

Access Statistics for this article

Journal of Systems Science and Information is currently edited by Shouyang Wang

More articles in Journal of Systems Science and Information from De Gruyter
Bibliographic data for series maintained by Peter Golla ().