Last updated on Jul 30, 2024

What are the best methods to measure and monitor UAV operator performance and fatigue?

Unmanned aerial vehicles (UAVs) are increasingly used for various military and civilian applications, such as reconnaissance, surveillance, and delivery. However, operating UAVs can be a demanding and complex task, requiring high levels of cognitive and perceptual skills, as well as situational awareness and decision making. How can we ensure that UAV operators perform optimally and avoid fatigue, stress, and errors? In this article, we will explore the concept of adaptive automation and how it can enhance human performance and workload management in the context of UAV.

1 What is adaptive automation?

Adaptive automation is a form of human-machine interaction that allows the level of automation to vary dynamically according to the operator's state, task demands, and environmental conditions. For example, an adaptive system can increase the level of automation when the operator is overloaded, distracted, or fatigued, or decrease it when the operator is underloaded, bored, or complacent. The goal of adaptive automation is to optimize the balance between human and machine roles, and to maintain the operator's engagement, performance, and situation awareness.

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Eyal Engel

Director - UAV Sales & BizDev. at IAI - Israel Aerospace Industries
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Just "passed by" this headline, and remembered a discussion I had a while ago with a colleague who's actually suffering from PTSD following his military duty as UAS operator. We all should remember, not only tiredness and fatigue are on the line here, but mental health and wellbeing too.

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2 Why is adaptive automation relevant for UAV?

UAV operations involve multiple and concurrent tasks, such as navigation, communication, payload control, and threat detection. These tasks can vary in complexity, uncertainty, and time pressure, depending on the mission objectives, terrain, weather, and adversaries. Moreover, UAV operators often work in remote and isolated environments, with limited social and physical support, and with long and irregular shifts. These factors can affect the operator's mental workload, attention, motivation, and fatigue, and potentially compromise their performance and safety. Adaptive automation can help to mitigate these challenges by adjusting the level of automation to match the operator's needs and preferences.

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3 How can we measure and monitor UAV operator performance and fatigue?

To implement adaptive automation effectively, we need to measure and monitor the operator's performance and fatigue in real time. This can be done through various methods and indicators, such as behavioral measures, physiological measures, and psychological measures. For instance, we can monitor the operator's reaction time, accuracy, efficiency, and satisfaction with the level of automation through their actions, responses, errors, and feedback on the system. Additionally, we can use electrocardiography (ECG), electroencephalography (EEG), or functional near-infrared spectroscopy (fNIRS) to detect the operator's arousal, stress, and cognitive load. Furthermore, questionnaires, interviews, or scales can be used to assess the operator's workload, fatigue, mood, and situation awareness.

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Robert Armstrong , MA , PMP

Servant Leader | SOF Veteran | Problem Solver
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One thing I’ve found helpful for tracking fatigue and strain is using a wearable device such as a Whoop or Oura ring. These devices measure sleep quality and quantity of sleep and daily strain to give a score of how rested you are each day. This type of metric would be helpful for leaders managing UAS operators as we would be able to tell which operators are at their peak and which ones might not be rested enough to handle the cognitive load of a UAS operator. This would play into their risk calculous when deciding workload. Wearables also tend to lead to positive behavior changes as individuals see exactly what effects their sleep each night.

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Carmen Prater

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I understand the hazards and the mitigation efforts here, but also believe that when possible, risk should be mitigated all together. My experience with High Altitude Long Endurance (HALE) UAS operations is that proper scheduling of operators is the best approach. When flying a 35 hr long mission (for example), operators become complacent and bored if they're in the Mission Control Element (MCE) for too long. I've found that 8 hr shifts staggered where pilots overlap each other by 4 hrs (meaning 2 pilots on deck for most of the mission) best mitigates the risk. Sure it makes operational costs a little higher, but it's still cheaper than loosing a multi-million $ asset because the pilot fell asleep.

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Dor Fridman

RPAS Flight Instructor & Operator @BlueBird Aero Systems Ltd. // I Test and Manage cutting edge technology
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To measure and monitor UAV operator performance and fatigue, emphasize proactive communication and situational awareness. Encourage operators to always brief forward, thinking ahead for mission success and fatigue identification. Thinking out loud and sharing thoughts help create transparency, enabling the team to understand the operator's situation. Implement fatigue risk management strategies, such as scheduled breaks and rotation of duties. Continuous feedback and an open communication culture contribute to effective performance monitoring and fatigue detection in UAV operators.

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4 What are the benefits and challenges of adaptive automation for UAV?

Adaptive automation can offer various advantages for UAV operations, such as improving performance, efficiency, and accuracy; enhancing workload management, engagement, and motivation; increasing situation awareness, trust, and confidence; and reducing fatigue, stress, and boredom. However, it also comes with some challenges and limitations. For instance, it can be difficult to find the optimal level of automation for each operator and situation. Additionally, adaptive systems must be designed to be transparent, predictable, and reliable to avoid unwanted changes in the level of automation. Furthermore, the effectiveness and acceptability of adaptive systems must be evaluated in terms of ethical, legal, and social implications.

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5 How can we design and evaluate adaptive systems for UAV?

To design and evaluate adaptive systems for UAV, we need to follow a user-centered and iterative approach. This involves analyzing the user's needs, goals, and characteristics, as well as the task requirements and environmental constraints. Additionally, objectives, criteria, and metrics for adaptive automation must be defined, along with scenarios and conditions for testing. The adaptive system must be developed and implemented using various methods and technologies for measuring and monitoring the operator's performance and fatigue. Testing and evaluation of the system should occur with various methods and techniques for collecting and analyzing behavioral, physiological, and psychological data. Finally, the system should be refined and improved based on feedback and results from the testing and evaluation.

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What are the best methods to measure and monitor UAV operator performance and fatigue?

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1 What is adaptive automation?

2 Why is adaptive automation relevant for UAV?

3 How can we measure and monitor UAV operator performance and fatigue?

4 What are the benefits and challenges of adaptive automation for UAV?

5 How can we design and evaluate adaptive systems for UAV?

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