Prediction Model of Emergency Rescue time for Special Major Accidents in High-speed Railway based on GERTS Network

Abstract

The existing emergency rescue process of high-speed railway mainly depends on the command and experience of emergency managers, and the rescue efficiency fluctuates greatly. In order to solve this problem, this paper constructs a model which can predict the time needed for emergency rescue. Firstly, the emergency rescue process of high-speed railway emergency is analyzed, then the relationship between key rescue tasks and the required time can be obtained according to the data mining of rescue cases and expert consultation, and the GERTS network model is established. Finally, the Yong-Wen line accident rescue case is simulated. The accident of Yong-Wen line was interrupted for 32 hours and 35 minutes, the number of simulations is 10000, and the average time is 32 hours. The results show that the model can accurately predict the time needed for emergency rescue and assist the rescue department to make scientific decisions.