Risk Analysis, Pilot Motivation, and Decision-Making: Application of the PAVE Personal Minimums Checklist to Pilot Decision-Making in Three General Aviation Accidents

Ruiz, Lorelei E.

doi:10.22488/okstate.18.100303

Cited by 1 publication

(2 citation statements)

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“…The analysis of flight risk factors is the basis of risk identification. This paper uses the HHM model and the risk identification framework [30] (Pilot-in-Command, Aircraft, Environment, External Pressures-PAVE) to identify risk sources, which requires constructing a risk scenario framework for the risks encountered in flight. Based on the iterative idea of the hierarchical holographic modeling process and the Delphi method, this paper constructs the HHM-PAVE framework to identify the risk factors in flight training.…”

Section: Risk Scenario Identificationmentioning

confidence: 99%

“…Based on the accident report of China's civil aviation safety management system and the aviation safety briefing data, this paper completed the risk factor analysis through Figure 2. From the pilot's perspective, the PAVE framework [30] is adopted to cultivate the critical thinking of pilot trainees. All risk factors are divided into four subsystems of P, A, V, and E. PAVE consists of four parts: P = Pilot-in-command (PIC); A = Aircraft; V = Environment; and E = External pressures.…”

Section: Hhm Framementioning

confidence: 99%

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Flight Training Risk Identification and Assessment Based on the HHM-RFRM Model

et al. 2023

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Due to the unavoidable operational risks and insufficient risk management capabilities of beginner pilots in flight training, the challenge of risk control in aviation schools has become increasingly prominent. To ensure the safety of flight training in aviation schools and to reduce costs and increase revenue, the essential prerequisite for improving efficiency is risk management. Therefore, it is necessary to explore risk identification and assessment methods. This paper adopts the holographic modeling (HHM) method and risk filtering, rating and management (RFRM) theory. First, the HHM idea is used to construct a risk identification framework (HHM-PAVE) for flight training. Second, based on the dual criteria, multiple criteria and cloud model (CM) in the RFRM approach, an improved risk assessment matrix-cloud model (IPC-CM) is proposed and combined with the N-K model and Bayes’ theorem to propose a coupled risk scenario hazard measurement model (CR-HM) based on the HHM-RFRM approach in risk assessment. In the assessment process, the impact of risk factors on system stability as well as the uncertainty problem and coupling–risk quantification problem in expert assessment are considered to obtain scientific and objective quantitative assessment results. Finally, the risk identification and assessment experiments were conducted using HHM-RFRM on the flight training. The results show that the method can more accurately identify critical risk factors in a flight training system and provide a new perspective for risk prevention and control.

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Section: Risk Scenario Identificationmentioning

confidence: 99%

Section: Hhm Framementioning

confidence: 99%