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Abstract
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BACKGROUND: In complex socio-technical systems like aviation systems, human error is said to be the main cause of air transport incidents, accounting for about 75 percent of these incidents and events. air traffic management (ATM) is considered a highly reliable industry; however, there is a persistent need to identify safety vulnerabilities and reduce them or their effects, as ATM is very human-centered and will remain so, at least in the mid-term (e.g., until 2025).
Objectives: The current study aimed to conduct a predictive analysis of controllers' cognitive errors using the TRACEr technique in an airport control tower.
Materials and Methods: This paper was done as a qualitative case study to identify controllers' errors in an airport control tower. First, the controllers' tasks were described by means of interviews and observation, and then the most critical tasks, which were more likely to have more errors, were chosen to be examined. In the next step, the tasks were broken down into sub-tasks using the hierarchical analysis method and presented as HTA charts. Finally, for all the sub-tasks, different error modes and mechanisms of their occurrence were identified and the results were recorded on TRACEr worksheets.
Results: The analysis of TRACEr worksheets showed that of a total 315 detected errors, perception and memory errors are the most important errors in tower control controllers' tasks, and perceptual and spatial confusion is the most important psychological factor related to their occurrence.
Conclusions: The results of this study led to the identification of many of the errors and conditions that affect the performance of controllers, providing the ability to define safety and ergonomic interventions to reduce the risk of human error. Therefore, the results of this study can be a basis for planning ATM to prioritize prevention programs and safety enhancement
Keywords: Airport Control Tower; Human Error; Controller; TRACEr
Language: en |