摘要
轨道交通不仅为人们的生活提供了极大的便利,而且还是国民经济发展的大动脉。轨道交通在发挥着其巨大作用的同时,各种各样的交通事故却屡见不鲜。最大可能地保证系统的安全性成为摆在轨道交通系统相关人员面前一个巨大的挑战。调查发现,在已查明原因的轨道交通事故中,至少有一半以上的事故直接或间接地与人的活动有关。随着硬件水平的不断完善,人成为轨道交通系统安全最重要的贡献者,对人的可靠性的分析也成为系统安全评价中不可缺少的一部分。
论文针对轨道交通系统自身的情况,研究了轨道交通系统中不同参与者相关的人的因素。鉴于现有常用人因可靠性分析方法的不足,以及贝叶斯网络在处理人的推理方面的优势,提出使用贝叶斯网络建立人的可靠性定量分析模型。由于人和机器是一个有机的整体,对人的可靠性的研究不能脱离系统独立进行,因此本文研究人的行为过程以人和测控系统的相互依赖为前提。另外,人与机器最大的不同就是人具有能动性,因而本文人的可靠性研究的重点就是对人的认知、决策过程的研究。最后使用本文提出的基于贝叶斯网络的人的可靠性分析模型,对轨道交通系统司机的人因可靠性进行了定量分析,并对比分析了设备、环境等因素对司机表现的影响。
根据论文所建立的司机的可靠性定量分析模型,为轨道交通系统中的安全评价提供了便利；而且通过定量分析不同因素对人的可靠性的影响,为轨道交通系统人机界面的设计、人员配置管理等活动提供了依据,尤其提出了一直难以解决的驾驶室报警数量和先后顺序设置的解决方案。
Rail transit plays a huge important role not only in life, but also in national economy. However, accidents resulted from railway never disappear when people are enjoying convenience. There is so much to do for system safety assuring as far as possible. Survey found that among identified rail transit accidents, at least half part were related to human activities directly or indirectly. With hardware perfected constantly, human are becoming the most significant contributor to system safety, and HRA (human reliability assessment) have been an indispensable part of safety assessment.
Based on self-situation of railway, human factors related to major participants are analyzed in this document. In condition of shortcomings of current HRA methods and advantage of Bayesian network in human interfere, HRA model based on Bayesian network is established. For human and machine are of an organic whole, interrelationship between human and measurement and control system are considered as precondition of HRA model based on Bayesian network, rather than analyzing operators alone. In addition, the principle difference between human and machine is human agency, thus, key of established model is modeling of human's situation assessment, especially human cognition processing. Take driver for example, quantitative HRA and analysis on effect factors are accomplished as well. In the last place, driver's HRA of rail transit system is analyzed based on Bayesian network mode established in this document, and influencing factors, such as devices and environment, impact on human performance is compared here as well.
The built HRA model makes safety assessment of rail transit more correct and objective. Besides of human reliability assessment, the model can be applied for man-machine interface design, stuffing, training and so on, particularly for solution of warning arranging in cab.
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