Traffic Operation Risk Assessments of Large-Scale Activities Based on Fuzzy Bayesian Network

We proposed a traffic operation risks assessment method of large-scale activities based on fuzzy Bayesian network for the precise prevention of traffic operation risks and the rationalization of emergency plans during large-scale activities. Based on the establishment of a large-scale activities traffic operation risks indicator system, we constructed a fuzzy Bayesian network topology map structure based on the Interpretive Structural Modeling (ISM) and quantified the number, state and conditional probability of fuzzy Bayesian network nodes. Finally, we examined the opening ceremony of a major winter sports event at the National Stadium as a case study. We analyzed the traffic operation risks were analyzed using Netica’s reasoning analysis and control variable method function and studied the changes of large-scale activities traffic operation risks under different adverse conditions.