Safety Risk Identification of Rail Transit Signaling System Based on Accident Data

Abstract:

To quantitatively identify the safety risk factors in rail transit signaling system accidents， an accident data mining method is presented. First， the original accidents were divided into different types of accident data in accordance with the law of Heinrich. Then， a 5M（management-machine-man-media-mission factor） based factor analysis identification method was adopted to identify respectively the 254 larger-casualty accidents and the 220 minor-casualty accidents considering the accident causation multi-factors after the general-statistic method and the statistic identification method analysis. The results indicate that the natural disaster， the signal equipment material fault， the poor construction management， and the inadequate staff protection are the most important major factors leading to the signaling system accident. The 5M based factor analysis method can be used to sort quantitatively the importance ranking of accident causation factors under multi-scale comprehensive measurement. A comparison of the general-statistic method and the statistic identification method suggests that the 5M based factor analysis method has the best identification effect， with a relatively higher influencing rate of 106% increase and moderate coverage rate.

Key words:rail transit;signaling;accident;5M (management-machine-man-media-mission factor) model;identification