Risk Coupling Analysis of Railroad Accident Based on Two-Layer N-K Model

Railroad accident risk analysis is crucial for railroad accident prevention and active safety assurance. In this paper, we adopt coupled risk theory to analyze the traffic safety risk of railroad transportation system, starting from the coupling of four types of main risk factors, namely human, machine, environment and management, and expanding them to secondary sub-factors, establishing a two-layer N-K model and quantifying their coupling degrees. The coupling degrees of primary main factors and secondary sub-factors of railroad accidents are calculated under different coupling modes of single-factor, two-factor and multi-factor respectively. The results show that the coupling degree of railroad transportation safety risk increases with the number of coupling factors; human factors are the main influencing factor and can influence other factors to some extent; the coupling degree of “human–machine” is the largest in the parallel coupling relationship. In addition to the management of personnel, it is also necessary to continuously improve the safety performance of the train itself and reduce the degree of risk of equipment; in the causal coupling relationship, the coupling degree of “locomotive staff-train signal-human management” is the largest. N-K model can provide some theoretical support for the prevention of safety accidents in railroad transportation, and bring practical significance to improve the safety prevention and control of railroad transportation.