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The risk of an airport traffic accident in the context of the ground handling personnel performance

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  • Chikha, Paulina
  • Skorupski, Jacek

Abstract

Aviation organizations still record many incidents and accidents in airport surface traffic despite developing safety management systems. GSE (Ground Support Equipment) operators participate in many of those events. It is necessary to manage the personnel properly to minimize such occurrences. This paper aims to develop a general method for determining the minimum training level at which the risk of causing an accident in air traffic is acceptable. The analysis was inspired and illustrated by a real-life minor aviation incident. The study consists of determining the risk of the transformation of this event into an accident. For this purpose, in the article, we use an innovative method of accident risk assessment based on an expert system. Due to the necessity of considering many subjective parameters, mainly related to human behavior in a complex system, we used fuzzy inference systems. The developed expert system with a hierarchical structure allowed to describe both the actions of the participants of the event and their consequences, depending on the ground handling personnel's performance. As a result, the determined risk correlated to the transformation of the selected incident into an accident. Finally, the sensitivity analysis determined the minimum level of the GSE operator's training. This paper presents the application of the developed expert system. It showed that the training of the GSE operator plays a crucial role, for example, in a situation wherein environmental conditions, such as the surface condition or visibility, were unfavorable.

Suggested Citation

  • Chikha, Paulina & Skorupski, Jacek, 2022. "The risk of an airport traffic accident in the context of the ground handling personnel performance," Journal of Air Transport Management, Elsevier, vol. 105(C).
  • Handle: RePEc:eee:jaitra:v:105:y:2022:i:c:s0969699722001144
    DOI: 10.1016/j.jairtraman.2022.102295
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    References listed on IDEAS

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