基于因果关系的列控系统模型约简方法

Automatic Train Control System Model Reduction Based on Causal Relation

摘要:

在基于安全需求对验证问题进行投影的方法基础上，针对投影出的验证子问题，提出了基于因果关系的变量约简方法，定义了环境变量间的因果关系，归纳出基本的因果关系组合，并提炼出变量约简规则，通过变量约减减少了验证问题的状态空间.采用国内某地铁线路的相关数据进行建模和验证，结果表明，该方法能够有效降低系统验证复杂度.

Abstract:

Based on the previous work about verification problem projection according to the safety requirements, a variable reduction approach was proposed based on causal relation for the projected subproblems. First, the causal relations among the environment variables of the projected subproblems were defined. Then, the basic causal relation combination of variables and the reduction rules were concluded. Through variable reduction, the state space of the verification problem was reduced. Finally, with configuration of a domestic metro line, an experiment of modeling and verification was demonstrated to show that the variable reduction approach efficiently reduces the verification complexity.