Predicting Accidents in Interlocking Systems: An SHA Model-Based Approach

Abstract

In recent days, rail transit accidents happen from time to time, but the causes are difficult to be found. According to the stochastic and real-time characteristics of equipment faults, three layer models based on stochastic hybrid automata (SHA) are proposed for interlocking systems. The three layer models consist of a system model, a monitoring model and a fault prediction model. The accidents caused by the equipment faults are predicted by simulating these models together on UPPAAL-SMC platform. The main contributions of this paper include: (1) extracting model patterns for interlocking systems (2) presenting a pattern-based system model generation process and an automatic generation method of monitoring model based on time constraints and (3) defining the accidents prediction model of collision accidents to predict the accidents and monitoring accident causes through model simulation.

Simplifying the Formal Verification of Safety Requirements in Zone Controllers Through Problem Frames and Constraint-Based Projection

“…We choose the first 21 variables to form V : where the first 15 variables are independent, and the last 6 ones are chosen from dependent variables. According to the definition of constraint-based projection, we project the V P as follows: 33 , ita 40 , ita 41 , ita 42 , ita 44 , ita 45 , ita 46 , ita 48 , ita 50 , · · · , ita 73 } where each interaction is shown either in Table V or VI. In the exact process of interaction projection, the phenomena replacement could be computed by Algorithm 2.…”

“…Hansen [31] presented a Vienna Development Model (VDM) [32] model of an interlocking system, and described how the model is validated through simulation in ML (programing language). Wang et al [33] provided a three layer model based on stochastic hybrid automata for interlocking systems. Through model simulation with UPPAAL-SMC, they predicted the accidents caused by the equipment faults.…”