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

作　　者：周庭梁[1,2] 许婧 陈小红[3] 赵时旻[1] 

机构地区：[1]同济大学道路与交通工程教育部重点实验室,上海201804 [2]卡斯柯信号有限公司,上海200071 [3]华东师范大学上海市高可信计算重点实验室,上海200062

出　　处：《同济大学学报（自然科学版）》2016年第11期1702-1708,共7页Journal of Tongji University:Natural Science

基　　金：国家自然科学基金(91418203)

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.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.

关 键 词：需求验证 变量约简 因果关系 列车运行控制系统 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]