Modeling and Analysis of Train Rear-End Collision Accidents Based on Stochastic Petri Nets

Abstract EN

We proposed a model of the train rear-end collision accidents based on stochastic Petri nets (SPN) theory.

By isomorphic Markov chain model of the proposed accident model, we provide the quantitative analysis of the train rear-end collision accidents.

Fuzzy random method is also applied to analyze the performance of the proposed model.

In addition, according to the data extracted from a large amount of historical data of the accident statistics, we present a case analysis and discussion.

It showed that the results of the proposed train rear-end accident model based on SPN are reasonable in practical applications and can be used to effectively analyze the accidents and prevent loss, and the results may be a reference to the department of railway safety management.