Safety Analysis Of Urban Rail Transit Driverless System Based On Petri Net

Compared with the traditional urban rail transit driving system,the fully automated unmanned driving system has gradually become the development trend of urban rail transit with its advantages such as high reliability,high transportation capacity,high service level,and low cost.However,because the domestic fully automated unmanned driving system is still in its infancy,lack of operating experience,and lack of relevant safety analysis and verification,this article aims to solve this problem by establishing a model for operating safety levels of urban rail transit fully automated unmanned driving systems.Petri Net’s safety optimization technology optimizes the key functions of the fully automatic unmanned driving system to improve the safety and reliability of the system.For unmanned systems,it is difficult to optimize the entire system one by one.In traditional safety analysis,functions with lower system safety levels are generally selected for optimization,but this method lacks certain objectivity.This paper introduces the analysis of the operational safety level of a fully automated unmanned driving system based on the Fuzzy Analytic Hierarchy Process(FAHP),establishes an operational safety evaluation index system and a safety evaluation model for the fully automated unmanned driving system.The main functions of the fully automatic unmanned driving system are analyzed,and the qualitative and quantitative safety levels of each function are obtained,and the key functions of the system that need to be optimized for safety are determined.Traditional security analysis methods such as Fault Tree Analysis(FTA)and Event Tree Analysis(ETA)are mainly used for the static security analysis of the system,and the ability to describe the dynamic process of the system is insufficient.Petri nets can describe both the static structure of the system and the dynamic operation of the system.Therefore,in this paper,by studying the modeling elements and processes of the Petri net model,according to the evolution of the reachable graph of the Petri net model,the high-risk state of the reachable graph is determined.Identification,use the backtracking algorithm to solve the critical state,and then use the interlocking method to modify the Petri net model of the system,optimize the transition path of the critical state,eliminate the hidden dangers in the system,and then improve the security of the system.Finally,according to the constructed safety evaluation index system and safety evaluation model of the fully-automatic unmanned driving system,the key function systems with the safety level of “general” and below are obtained,and the door control system with the lowest safety value is selected as For example,security optimization based on Petri nets is performed.Finally,through a reachability graph analysis of the anti-pinch door control model,the safety of the optimized model was verified,and it was proved that the high-risk state of the fully automatic driverless door control system under the non-failure model was eliminated.