Research On High-speed Railway Traffic Dispatching System Risk Identification And Analysis Based On Risk Management Theory

In recent years, high-speed railway has developed dramatically in China, with the continuous improvement of the running speed and the increase of the density of traffic, high-speed railway on the safety requirements and standards have increased accordingly. Based on risk management theory, this paper is commissioned to analyze the core subsystem of the high-speed railway dispatching command system so as to reduce the accident and ensure the safety of traffic.In the first place, the theory of risk management is explained in detail, followed by some concepts related to the risk, and the key link of risk management is nailed down, namely, risk identification, risk analysis and risk control. Several methods of risk analysis are given, moreover, the characteristics of each method are evaluated, and the most suitable risk analysis method for high-speed railway traffic dispatching system is selected in this part.Then, combining with the human factors analysis and classification model (HFACS), a qualitative risk identification of high-speed railway traffic control system is expounded from three major views:human-machine-environment.32 identified hazard factors are classified, and 14 refined hazard factors are obtained. By using the grey correlation analysis method, several riskier factors are selected according to the correlation of these 14 risk factors, which is sorted by MATLAB simulation.Thirdly, based on the risk identification of high-speed railway traffic dispatching system, the next step of risk management-risk analysis is in progress. This paper studied on the transformation algorithm from Fault Tree to Bayesian Network, to get the conditional probability of a non-root node. Combined with fuzzy set theory, studied on the research of fuzzy evaluation of the Bayesian network prior probability of the root nodes algorithm and Bayesian network reasoning method.Finally, the highest risk of dangerous factor of the high-speed railway dispatching command system-the temporary speed limit of human unsafe behavior-has been selected in this paper, with in-depth analysis. The fault tree model of temporary speed restriction has been built, which then has been converted into Bayesian network model. Based on multi-expert fuzzy evaluation algorithm, the prior probability of the root nodes has been found. The simulation software of GeNIe is used for the positive causal reasoning of the model with the purpose of getting the probability of temporary speed limit, followed by the reverse diagnosis reasoning, which is to find out the significant factors affecting the system and the risk control, thereby ensuring the safety of traffic.