J.P. Reitsma
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8 records found
1
RCO presents an opportunity to critically reassess automation on the flight deck by redefining the role of the pilot. Many researchers agree that the pilot remains the ultimate decision-maker and is responsible for ensuring the safety and success of the flight operation. The pilot’s role will encompass flight planning, communication, and surveillance, while system management tasks are considered suitable candidates for automation. However, automating system management may lead to diminished system state awareness, potentially compromising flight plan management performance. Consequently, additional support is needed to keep the pilot actively engaged with flight plan management tasks.
In addition to addressing the potential adverse effects of automating system tasks, the current support for flight plan management requires already a significant improvement. A key challenge in handling non-normals lies in assessing and integrating disturbances into the flight plan. Pilots must gather, combine, and analyze environmental and system information. This information is often fragmented across multiple sources and requires decryption to become actionable. This process heavily relies on the pilot’s initiative and experience, increasing the risk of unconsidered impacts.
This study examined the impact of elevating the Level of Automation (LOA) for system and flight plan management functions. A proposed concept elevated the LOA of the system management support, specifically the action execution stage from a stepby- step action support to a system that autonomously performs a sequence of actions after human activation. In flight plan management, the information acquisition and analysis stages were highly automated, with the goal of reducing workload while enhancing decision-making performance…
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RCO presents an opportunity to critically reassess automation on the flight deck by redefining the role of the pilot. Many researchers agree that the pilot remains the ultimate decision-maker and is responsible for ensuring the safety and success of the flight operation. The pilot’s role will encompass flight planning, communication, and surveillance, while system management tasks are considered suitable candidates for automation. However, automating system management may lead to diminished system state awareness, potentially compromising flight plan management performance. Consequently, additional support is needed to keep the pilot actively engaged with flight plan management tasks.
In addition to addressing the potential adverse effects of automating system tasks, the current support for flight plan management requires already a significant improvement. A key challenge in handling non-normals lies in assessing and integrating disturbances into the flight plan. Pilots must gather, combine, and analyze environmental and system information. This information is often fragmented across multiple sources and requires decryption to become actionable. This process heavily relies on the pilot’s initiative and experience, increasing the risk of unconsidered impacts.
This study examined the impact of elevating the Level of Automation (LOA) for system and flight plan management functions. A proposed concept elevated the LOA of the system management support, specifically the action execution stage from a stepby- step action support to a system that autonomously performs a sequence of actions after human activation. In flight plan management, the information acquisition and analysis stages were highly automated, with the goal of reducing workload while enhancing decision-making performance…
The Skill Assumption
Over-Relicance on Perception Skills in Hazard Analysis
Designing interfaces for effective decision-making supports for complex, dynamic systems is a challenging task. Besides the already challenging task of determining the visual form, the task of defining the content of these supports can be even more demanding. Especially for an unstable and complex work domain with multiple stakeholders and multiple interrelated systems, e.g., commercial flight operations. Various methodologies for designing such supports have been introduced in the last decades. In this paper two methodologies, Ecological Interface Design (EID) and Applied Cognitive Work Analysis (ACWA) are compared to determine what methodology is best suited for the design of an in-flight decision support system. The methodologies are compared on two aspects, (1) development of the knowledge-based model and (2) the means to translate this model into requirements for the actual representation. The functional abstraction network (FAN), as part of the ACWA, is the preferred knowledge-based modelling method for capturing a complex multi-system work domain, like commercial flight operations. Mainly due to the increased flexibility in modeling and ease of extending the model. The ACWA is also found to the preferable method to translate the functional model into representation requirements due to its structured step-wise and system engineering inspired approach.
Taking a Closer Look at Flight Crew Handling of Complex Failures
Ten Case Studies