航空
过程(计算)
操作员(生物学)
运筹学
动态决策
工程类
飞行训练
工作(物理)
商用航空
航空学
混乱的
模拟
计算机科学
飞行模拟器
人工智能
机械工程
航空航天工程
生物化学
化学
抑制因子
转录因子
基因
操作系统
作者
Utku Kale,Omar Alharasees,József Rohács,Dániel Rohács
标识
DOI:10.1108/aeat-02-2022-0053
摘要
Purpose The purpose of this paper is to investigate and evaluate the subjective decision-making of pilots during final approach with varying degrees of experience for landing and go-around. Design/methodology/approach In this research, the “Lorenz Attractor” was modified and used to model the subjective decision-making of pilots during the final approach. For landing and go-around situations, “hesitation frequency” and “decision-making time” were calculated for the subjective decision-making of pilots. Findings In this research, the modified Chaotic Lorenz Model was used on MATLAB with varying degrees of experience, namely, student pilots, less-skilled pilots, experienced pilots and well-experienced pilots. Based on the outcomes, the less-skilled pilot needs nearly four times more decision-making time on landing or go-around compared to the well-experienced pilot during the final approach. Practical implications Operators (pilots, air traffic controllers) need to make critical and timely decisions in a highly complex work environment, which is influenced by several external elements such as experience level and human factors. According to NASA, 80% of aviation accidents occur due to human errors specifically over the course of the aviation decision-making process in dynamic circumstances. Due to the consequences of this research the operators' training should be redesigned by assisting flight instructors on the weaknesses of pilots. Originality/value This research explores the endogenous dynamics of the pilot decision-making process by applying a novel “Chaotic Lorenz Model” on MATLAB. In addition, the operator's total decision time formula was improved by including the decision reviewing time and external factors. Moreover, subjective decision-making model created by the current authors and Wicken's information model were modified to the highly automated systems.
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