Influences of Attention on Aspects of a Cognitive Map for Cockpit Operation

A cognitive map is a mental model of a process virtually represented to depict interactions with an environment. It is made up of situational awareness and memory. In the article Situation Awareness and Workload in Aviation (2002), Wickens identifies three types of situational awareness: spatial, system, and task. These three types of awareness ultimately make up a cognitive map of the cockpit operation.

Because a cognitive map is virtual and created from memory, it is not only personal. It also fluctuates and is affected by a person’s emotions, the task, and the level of alertness, which, per load theory of attention, is directly influenced by the amount of mental workload. Therefore, the main concern with cognitive maps is determining a design for an operative system and its environment that maintains alertness and maximizes attention span for both normal and unexpected situations. Simultaneously, avoid overwhelming the user with salient cues, thus preventing fatigue-related errors related to the over-occupying of attention.

Memory is created from neural processes activation, including bottom-up and top-down processes, and the attention used to comprehend. When alertness is decreased, the brain risks a decrease in recall ability, increasing potential errors. Therefore, when designing an operative system, designers cannot rely on users' memory. Instead, designers should focus on promoting situational awareness. According to Wickens (2002), memory is synthesized in cognitive maps, making cognitive maps more dynamic and adaptive to the situation than memory alone. Therefore, cognitive maps are more useful when encountering unexpected scenarios, a common occurrence in pilots' flight missions. 

Types of Awarenesses

Spatial Awareness

One type of awareness that makes up situational awareness is spatial awareness. It is used by a pilot to navigate the aircraft in a 3D space. As Wickens (2002) presents in the article, there are multiple angles in which the plane's location can be displayed in relation to the environment. Choosing which angle to display, a designer will first need to accurately display the aircraft's location from an angle that is compatible and customary regarding the pilot's cognitive map. Second, the display has to provide functionality and enough stimuli to ensure attention, but not so many stimuli that would cause mental overloading. A mental overload decreases attention duration because more stimuli share a limited resource; therefore, it increases the chances of inattentional and change blindnesses, leading to errors. (Goldstein, 2019, p.117)

System Awareness

In terms of system awareness in cognitive mapping, it is essential to consider how much automation can be added to the system. As Wickens (2002) mentions, monitoring a system's decision can be challenging if the pilot is already experiencing a high mental workload. When working with an automated machine, the pilot is likely already using selective attention to focus on his primary task and responding only when a cue signals. However, suppose an automated machine suddenly requires attention. In that case, the pilot is not only needed to switch from selective to alternating attention, which already causes deficits to attention span; the pilot is also required to spend additional attention to understand the system's decisions. Therefore, the challenge becomes giving enough signal for allowing the pilot to engage the system's decisions, but not so many stimuli that would pose distractions to the pilot. 

Task Awareness

The last aspect of cognitive mapping is task awareness. Aviation is a multitask performance. However, attention is a limited resource. Therefore, the human mind performs best when using selective attention, where the mind is allowed to focus on one task. Automation reduces task load and refrains the pilot from alternating or divided attention, which has a shorter attention span as attention is being distributed across more tasks. Yet, multitasking is still inevitable even with the help of automation. A display needs to provide information on tasks to ensure a pilot understands the tasks' priorities and maintains alertness for other tasks when needed. The display cannot be so minimal that it only contains information the pilot needs at that moment because when selective attention is used, tunneling attention to a single task risks inhibiting attention to surroundings, which does not promote situational awareness (Wickens, 2002).

Attention Assessment

Fatigue directly affects attention because it decreases the brain's ability to filter out irrelevant stimuli (Faber, Maurits & Lorist, 2012). When feeling fatigued, the user then falls into the vicious cycle of using divided attention to acquire more data, which shortens attention span further, thus feeling even more fatigued. There are a few ways to monitor the level of fatigue in a pilot continuously. One is to have the pilot self-report the level of fatigue. A more empirical method is to calculate the number or percent errors made compared to simulation or flight guidelines. Mizuno et al. 's (2011) research shows a positive correlation between parasympathetic activities and mental fatigue. Therefore, measuring heart rate, blood pressure, and urine secretion should also be used as scientific evidence of fatigue level, which predicts if operation attention is affected by fatigue or not.

References

Faber, L. G., Maurits, N. M., & Lorist, M. M. (2012). Mental fatigue affects visual selective attention. PloS one, 7(10), e48073. https://doi.org/10.1371/journal.pone.0048073

Goldstein, E. B. (2019). Cognitive psychology: Connecting mind, research, and everyday experience. Boston, MA: Cengage.

Mizuno, K., Tanaka, M., Yamaguti, K. et al. Mental fatigue caused by prolonged cognitive load associated with sympathetic hyperactivity. Behav Brain Funct 7, 17 (2011). https://doi.org/10.1186/1744-9081-7-17

Wickens, C. D. (2002). Situation Awareness and Workload in Aviation. Current Directions in Psychological Science,11(4), 128-133. https://doi.org/10.1111/1467-8721.00184