Identifying critical links in urban traffic networks: a partial network scan algorithm
Abstract
Purpose
Critical links in traffic networks are those who should be better protected because their removal has a significant impact on the whole network. So, the purpose of this paper is to identify the critical links of traffic networks.
Design/methodology/approach
This paper proposes the definition of the critical link for an urban traffic network and establishes mathematical model for determining critical link considering the travellers’ heterogeneous risk-taking behavior. Moreover, in order to improve the computational efficiency, the impact area of a link is quantified, a partial network scan algorithm for identifying the critical link based on the impact area is put forward and the efficient paths-based assignment algorithm is adopted.
Findings
The proposed algorithm can significantly reduce the search space for determining the most critical links in traffic network. Numerical results also demonstrate that the structure of efficient paths has significant impact on identifying the critical links.
Originality/value
This paper identifies the critical links by using a bi-level programming approach and proposes a partial network scan algorithm for identifying critical links accounting for travellers’ heterogeneous risk-taking behavior.
Keywords
Acknowledgements
This work is supported by the Humanities and Social Science Foundation of Ministry of Education of China (No. 13XJC630017), the Natural Science Foundation of Gansu Province of China (No. 148RJZA052), the National Natural Science Foundation of China (No. 61164003 and No. 61364026). The authors wish to thank anonymous referees and the editor for their comments and suggestions.
Conflict of interests: the authors declare that there is no conflict of interests regarding the publication of this paper.
Citation
Yang, X., Liu, L., Li, Y. and He, R. (2016), "Identifying critical links in urban traffic networks: a partial network scan algorithm", Kybernetes, Vol. 45 No. 6, pp. 915-930. https://doi.org/10.1108/K-05-2015-0144
Publisher
:Emerald Group Publishing Limited
Copyright © 2016, Emerald Group Publishing Limited