An Automated Accident Causal Scenario Identification Method for Fully Automatic Operation System Based on STPA

Fei Yan,Ru Niu,Tao Tang,Junqiao Ma,Mo Li

doi:10.1109/access.2021.3050472

Abstract

Accident causal scenario can describe the process logic of the accident clearly and concretely from the perspective of the control mechanism. Only by improving the quality of the causal scenario can the effective control measures be taken. Combining the technical characteristics of the fully automatic operation (FAO) system, the paper proposes an automated accident causal scenario identification method for FAO system based on the System-Theoretic Process Analysis (STPA) method. Aiming at the problem that there are too many layers in the hierarchical control structure diagram of STPA method, which makes it impossible to effectively trace the cause and the problem that the basic control structure model only contains the control structural information and lacks the cause information, a new basic control structure model is defined to model multiple control processes in time sequence, and then the paper extends it from four aspects: control action, input variables, external disturbance, and synchronous timing to add more system cause information. For the lack of a unified standard description problem for the causal scenario, a four-stage causal scenario description method is defined, this paper has developed the first timing, non-first timing, synchronous timing, and external disturbance causal scenario search rules to ensure the automatic identification of the causal scenarios. Applying the automated safety analysis method to the case study of the operational scenarios of parking in a station of Beijing Yanfang Line, the automated identification of related causal scenarios is successfully completed through the Auto-STPA platform, and corresponding safety requirements are added. The feasibility of the method and the applicability to the analysis of operational scenarios are verified.

Highlights

Metros have been in existence since mid-1860s and serve many of the world’s major cities
This paper proposes an automated accident causal scenario identification method for Fully automatic operation (FAO) system
In order to add more system information generated by the causal scenario, extended information from four aspects of control action, input variable, synchronous timing, and external disturbance are added

Summary

INTRODUCTION

Metros have been in existence since mid-1860s and serve many of the world’s major cities. Automatic operation (FAO) system is a new generation of urban rail transit system aims at enhancing operational services and the functionality and performance of system equipment via modern information and automation technology. THE AUTOMATED ACCIDENT CAUSAL SCENARIO IDENTIFICATION METHOD In the search for the causal scenarios of the unsafe control action, it is obvious that STPA does not provide enough guidance, relying on manual judgment and analysis, resulting in the arbitrariness of the generated causal scenarios. It cannot guarantee the comprehensiveness and precision, so that the subsequent safety requirements are insufficient, which weakens the guiding significance of safety analysis.

CONSTRUCT BASIC CONTROL STRUCTURE MODEL

CASE STUDY

Findings

CONCLUSION