Research Of Quantitative Human Reliability Assessment Method For Rail Transit System Based On Bayesian Network

Rail transit plays a huge important role not only in life, but also in national economy. However, accidents resulted from railway never disappear when people are enjoying convenience. There is so much to do for system safety assuring as far as possible. Survey found that among identified rail transit accidents, at least half part were related to human activities directly or indirectly. With hardware perfected constantly, human are becoming the most significant contributor to system safety, and HRA (human reliability assessment) have been an indispensable part of safety assessment.Based on self-situation of railway, human factors related to major participants are analyzed in this document. In condition of shortcomings of current HRA methods and advantage of Bayesian network in human interfere, HRA model based on Bayesian network is established. For human and machine are of an organic whole, interrelationship between human and measurement and control system are considered as precondition of HRA model based on Bayesian network, rather than analyzing operators alone. In addition, the principle difference between human and machine is human agency, thus, key of established model is modeling of human's situation assessment, especially human cognition processing. Take driver for example, quantitative HRA and analysis on effect factors are accomplished as well. In the last place, driver's HRA of rail transit system is analyzed based on Bayesian network mode established in this document, and influencing factors, such as devices and environment, impact on human performance is compared here as well.The built HRA model makes safety assessment of rail transit more correct and objective. Besides of human reliability assessment, the model can be applied for man-machine interface design, stuffing, training and so on, particularly for solution of warning arranging in cab.