地铁行车调度系统人误情景评价模型研究

A Model for Evaluating Human Error Context in Subway Traffic Scheduling System Based on Fuzzy Cognitive Map

为解决地铁行车调度系统人误影响因素(PIF)研究缺乏系统性的问题,建立人误情景(EC)评价模型,探索以专家经验为基础的PIF效应评估方法。首先,构建考虑PIF间的相互作用的EC概念模型。然后,以模糊认知图(FCM)方法为基础,建立PIF的影响效应路径搜索算法及PIF综合效应的评定技术。最后,以实例分析验证所建模型。结果表明:单个PIF状态的变化对整个EC产生影响,且PIF的综合影响程度远大于直接影响程度。因此,制定人误预防或减少措施时,有必要考虑PIF状态变化带来的综合效应。

For sake of solving the problem of lack of methods for analyzing human error PIFs in subway traffic dispatching system systematically, a EC evaluation model was built. An expert experience-based method for evaluating effects of PIFs was built. An algorithm for searching affecting paths of PIFs and a technique for evaluating PIFs integrated effect were worked out on basis of FCM method. Finally, a validation analysis was carried out with an example. Results showed that a change in a single human error PIF state may impact on the whole EC, and its indirect effect was much more than direct effect. Therefore, the integrated effects of a change in PIF state need to be considered during development of a human error pre- vention or reduction method.