Chinese Science Bulletin

, Volume 55, Issue 10, pp 1000–1006 | Cite as

An evacuation risk assessment model for emergency traffic with consideration of urban hazard installations

  • Qiang Li
  • Xiang Chen
  • Jin ChenEmail author
  • Qiao Tang
Articles Mechanical Engineering


The Critical Cluster Model (CCM) is an optimization model assessing the evacuation risk on the scale of neighborhoods. The static evacuation risk in the CCM is measured by Bulk Lane Demand (BLD) — an index that solely depends on network structure and population of evacuees. The advantage of the CCM is having less input parameters and with relatively smaller computational cost. Moreover, the process of risk assessment by the CCM is a global optimization process. For this reason, the CCM provides a relatively ideal solution for planning emergency traffic evacuation in open spaces. Considering that hazard installations in urban areas are becoming an increasing threat to urban safety, in the paper we proposed an evacuation risk assessment model with consideration of such installations. This model was developed on the basis of the CCM by introducing two important factors: the accident risk impact factor which was negatively correlated with distance, representing the impact of hazard installation; the evacuation direction which was under the consideration of evacuating away from the hazard installation, providing feasible evacuation routes. Finally, an application of the new model was presented for Beijing, China with the support of Geographical Information System (GIS).


urban public safety Critical Cluster Model (CCM) hazard installation traffic evacuation risk Geographical Information System (GIS) 


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Copyright information

© Science in China Press and Springer Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.College of Resources Science and TechnologyBeijing Normal UniversityBeijingChina
  2. 2.Academy of Disaster Reduction and Emergency ManagementBeijing Normal UniversityBeijingChina
  3. 3.College of Information Science and TechnologyBeijing Normal UniversityBeijingChina

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