Evaluating Operator Fatigue States During the 2018 Kilauea Volcano: Implications for Human-Robotic Interactions during Disasters

There has been an increasing use of mobile robots in disaster and incident response (Murphy, 2014). These robots mediate between human operators and the environment to provide remote presence at the disaster (Murphy & Burke, 2008). Murphy (2014) reports that all mobile robots deployed to 34 known disasters and extreme incidents between 2001 and 2013 were teleoperated. Furthermore, 50% of robot failures within the same period were attributed to human failure, suggesting that human-robot interaction (HRI) is a major issue facing disaster robots (Murphy, 2014). However, few studies have focused specifically on documenting and understanding the unique attributes associated with HRI in disaster robotics. Of interest in the present study are small UAS (sUAS) defined by the FAA to be under 55 pounds (25 kilograms) and capable of limited altitudes (Murphy, 2014). We focus on evaluating fatigue states of sUAS operators, known to arrive at disaster environments with lost sleep, exacerbated by disrupted sleep/rest schedules as the mission unfolds (Casper & Murphy, 2003). Methods for evaluating operator states when they interact with disaster robots include subjective, performanceoriented, and physiological techniques. The Psychomotor Vigilance Test (PVT; Dinges & Powell, 1985) is a performance-oriented method used to evaluate operator states across several domains including UAVs (e.g., Yang, Choi, & Park, 2018). Heart rate (HR) and heart rate variability (HRV) are physiological metrics used to assess operator states in several domains including UAS (e.g., Jasper, Sibley, & Coyne, 2016). The objective of the present study was to assess fatigue states of five sUAS pilots (2 females) who flew sUASs during both day and night missions while assisting with tactical response during the 2018 Kilauea Volcano Lower East Rift Zone event. The flight schedules were unpredictable and on several days the team worked more than 12 hours. We collected pilots’ physiological data with E4 wristbands (Empatica, Milan, Italy) worn on their nondominant wrist for 3 minutes. We assessed pilots’ vigilance and behavioral alertness with the 3-minute PVT. We used mean of the reciprocal of response time (mean response speed), number of lapses, and performance score as PVT outcome measures for analysis. From the recorded HR, we computed percent HR Reserve (%HRR) as (HRmission – HRrest)/ HRrest) * 100, where HRmission is the average HR for a mission, and HRrest is the average HR for the 3 minutes resting baseline period. Our results showed that for all the pilots both mean response speed and performance score appeared to decrease, and mean number of lapses appeared to increase from the morning of second day to the morning of the last day of the deployment. These results indicate that pilots’ vigilance and alertness decreased after each mission, suggesting that they were fatigued by the mission (Riethmeister, Bültmann, Gordijn, Brouwer, & de Boer, 2018). sUAS pilot fatigue may have, in part, been induced by circadian rhythm and sleep disruption. %HRR results showed that sUAS pilots did exceed the 28% HRR upper threshold for moderate work demand (Mital, Desai, & Mital, 2016). Prior to this study, understanding of assessing HRI during tactical response has been largely experimental or based on expert opinions and subjective narratives from field robotics researchers. This is the first study of this kind that involves evaluating operator states during HRI in a real-world disaster response. It is imperative that the relationship between task performance and pilots’ physiological limits of maximal adaptability be investigated. Investigations, like the present study, are critical in understanding and assessing pilots’ cognitive and physical capabilities such that any compromised functions are either mitigated by design or externally supported via traditional or technological cognitive supports.