论文:2022,Vol:40,Issue(6):1250-1260
引用本文:
谢凝, 陈登凯, 周垚, 张献. 基于人因可靠性的民机驾驶舱人机界面评价方法[J]. 西北工业大学学报
XIE Ning, CHEN Dengkai, ZHOU Yao, ZHANG Xian. A method for evaluating human-machine interface in civil aircraft cockpit based on human factor reliability[J]. Journal of Northwestern Polytechnical University

基于人因可靠性的民机驾驶舱人机界面评价方法
谢凝1,2, 陈登凯1,2, 周垚1,2, 张献1,2
1. 西北工业大学 工业设计研究所, 陕西 西安 710072;
2. 工业设计与人机工效工信部重点实验室, 陕西 西安 710072
摘要:
为降低民机驾驶舱人因失误概率,基于SHEL模型对影响人机界面人因可靠性的行为形成因子(PSF)进行分类并构建PSF体系,利用解释结构模型(ISM)建立相应的邻接矩阵,得到多层级递阶结构,同时,引入Noisy-OR模型来构建贝叶斯网络,以此建立新的人机界面评价方法。通过对实际案例的贝叶斯网络因果推理验证了所得方法的有效性。研究提出了一套适用于民机驾驶舱人机界面的人因可靠性评价方法,为人因可靠性评估提供了新思路。
关键词:    驾驶舱    人因失误    解释结构模型    贝叶斯网络   
A method for evaluating human-machine interface in civil aircraft cockpit based on human factor reliability
XIE Ning1,2, CHEN Dengkai1,2, ZHOU Yao1,2, ZHANG Xian1,2
1. Institute of Industrial Design, Northwestern Polytechnical University, Xi'an 710072, China;
2. Key Laboratory of Industrial Design and Human-Machine Ergonomics for Ministry of Industry and Information Technology, Xi'an 710072, China
Abstract:
In order to reduce the probability of human error in the cockpit of a civil aircraft, based on the SHEL model, this paper classifies performance shaping factors (PSF) that affect the human factor reliability of the human-machine interface. Then it constructs the relevant PSF system and uses the interpretation structure model to establish the corresponding adjacency matrix. When a multi-level recursive structure is obtained, the Noisy-OR model is introduced to construct the Bayesian network, thus establishing the new human-machine interface evaluation method. Real cases are used to verify the effectiveness of the method thus established through causal inference with the Bayesian network. The evaluation method for the reliability of a set of human factors this paper proposes provides a new approach to evaluating the human-machine interface in the cockpit of a civil aircraft.
Key words:    cockpit    human factor error    interpretative structure model    Bayesian network   
收稿日期: 2022-02-25     修回日期:
DOI: 10.1051/jnwpu/20224061250
基金项目: 中央高校基本科研业务费(31020190504007)与陕西省特支计划领军人才项目(w099115)资助
通讯作者: 周垚(1993—),西北工业大学博士研究生,主要从事人机交互设计研究。e-mail:zhouy@mail.nwpu.edu.cn     Email:zhouy@mail.nwpu.edu.cn
作者简介: 谢凝(1993—),西北工业大学博士研究生,主要从事工业设计研究
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