About this Research Topic
Spatial disorientation (SD) remains a persistent problem in military and commercial aviation. Flight simulators are regularly used to train pilots how to recognize and avoid SD. Devices developed to better inform pilots of their ongoing spatial position relative to gravity have had some benefit, especially haptic cueing. Nonetheless, the incidence of fatal accidents remains virtually unchanged. With the introduction of new technologies and displays, cockpit instrument panels have become increasingly complex and difficult to master, increasing the cognitive demands on the pilot.
SD is now often characterized according to type. Type I: the pilot does not recognize the discrepancy between actual and perceived orientation. Type II: the pilot recognizes a discrepancy between perceived self-orientation and orientation as conveyed by flight instruments. Type III: the discrepancy between the pilot’s perceived and actual orientation becomes so great that aircraft control becomes erratic and crashing becomes likely.
SD is not confined to aircraft and spacecraft but can occur on land and at sea as well. Different types of vehicles can cause SD, and under very different conditions. Although the concept of SD includes misperception of orientation under terrestrial conditions on Earth, misperception under aerospace conditions is the source of the greatest safety concerns. In the context of new insights into our physiological and cognitive adaptations to Earth gravity, the whole concept of SD needs to be reconsidered. It is important to determine whether the three SD types typically identified might be augmented via an SD taxonomy and/or model-based analyses and whether different vehicles need to be characterized in different ways. Is it possible to develop cueing techniques that have benefit across multiple domains or are specialized devices tailored to each environmental context necessary to help prevent SD? Linear models of orientation mechanisms have had some success in explaining SD, especially for explaining why certain aircraft crashes have occurred. Are they adequate for extension to other types of vehicles? Virtual environment technology is rapidly being incorporated into training simulators and cockpits. What types of benefits could this have for lowering pilot demands, what potential drawbacks?
SD remains an operational problem despite multiple attempts to provide pilots with alternative sources of information about their orientation. Both theoretical and empirical papers are invited to address the broad scope of SD. Some potential topics includes the following:
- Could attention to SD on land and sea lend insights with cross-domain significance?
- What types of SD prevention training protocols would be likely to be internalized without extensive training protocols so they could be used automatically?
- What protocols could be developed to assess an individual’s likely susceptibility to SD in different situations?
- Could such protocols be used across different exposure domains?
- What role does sleep deprivation play in enhancing the likelihood of experiencing SD?
- What medical conditions likely contribute to SD. How strong is the evidence that SD training in ground-based simulators enhances performance in operational conditions?
- Could virtual reality assessments of susceptibility to SD during virtual self-motion also predict SD in comparable real motion operational conditions?
- What types of models are necessary to deal with SD across different motion domains and vehicles in space, air, sea, and land?
- Does artificial intelligence have a role in individualized training or operational assistance?
- Can we develop a framework for an SD taxonomy?
- How can model-based analyses of accident data yield an enhanced understanding of SD and associated incidents?
SD is now often characterized according to type. Type I: the pilot does not recognize the discrepancy between actual and perceived orientation. Type II: the pilot recognizes a discrepancy between perceived self-orientation and orientation as conveyed by flight instruments. Type III: the discrepancy between the pilot’s perceived and actual orientation becomes so great that aircraft control becomes erratic and crashing becomes likely.
SD is not confined to aircraft and spacecraft but can occur on land and at sea as well. Different types of vehicles can cause SD, and under very different conditions. Although the concept of SD includes misperception of orientation under terrestrial conditions on Earth, misperception under aerospace conditions is the source of the greatest safety concerns. In the context of new insights into our physiological and cognitive adaptations to Earth gravity, the whole concept of SD needs to be reconsidered. It is important to determine whether the three SD types typically identified might be augmented via an SD taxonomy and/or model-based analyses and whether different vehicles need to be characterized in different ways. Is it possible to develop cueing techniques that have benefit across multiple domains or are specialized devices tailored to each environmental context necessary to help prevent SD? Linear models of orientation mechanisms have had some success in explaining SD, especially for explaining why certain aircraft crashes have occurred. Are they adequate for extension to other types of vehicles? Virtual environment technology is rapidly being incorporated into training simulators and cockpits. What types of benefits could this have for lowering pilot demands, what potential drawbacks?
SD remains an operational problem despite multiple attempts to provide pilots with alternative sources of information about their orientation. Both theoretical and empirical papers are invited to address the broad scope of SD. Some potential topics includes the following:
- Could attention to SD on land and sea lend insights with cross-domain significance?
- What types of SD prevention training protocols would be likely to be internalized without extensive training protocols so they could be used automatically?
- What protocols could be developed to assess an individual’s likely susceptibility to SD in different situations?
- Could such protocols be used across different exposure domains?
- What role does sleep deprivation play in enhancing the likelihood of experiencing SD?
- What medical conditions likely contribute to SD. How strong is the evidence that SD training in ground-based simulators enhances performance in operational conditions?
- Could virtual reality assessments of susceptibility to SD during virtual self-motion also predict SD in comparable real motion operational conditions?
- What types of models are necessary to deal with SD across different motion domains and vehicles in space, air, sea, and land?
- Does artificial intelligence have a role in individualized training or operational assistance?
- Can we develop a framework for an SD taxonomy?
- How can model-based analyses of accident data yield an enhanced understanding of SD and associated incidents?
Keywords: Spatial Disorientation, Crashes, Conceptual Reformulation, Training, Models, Prediction
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