An improved man-machine system Incident Tree model considering incident dependence

Abstract

The Incident Tree Analysis methodology (ITA) can consider the uncertain characteristics of accident by combining fuzzy logic and information flow approaches together. But the dependence of man-machine interaction is not considered in ITA approach, which ignores the differences of task scenarios meanwhile. In this paper, we put forward an Improved Incident Tree Analysis methodology (IITA) taking this dependence into account, and present its mathematic method. Firstly, information quantity and control sequence quantity are introduced and reformed to show the dependence of the man-machine interaction process at the information level. And then the steps of determining the two parameters values in different task scenarios are given. A vehicle-leaving-roadway accident is taken as an example to illustrate the proposed method. Contrasting with the results of ITA, IITA is proved better to evaluate the risk of complex man-machine systems.