Human Factors最新文献

ObjectiveWe investigated how various error patterns from an AI aid in the nonbinary decision scenario influence human operators' trust in the AI system and their task performance.BackgroundExisting research on trust in automation/autonomy predominantly uses the signal detection theory (SDT) to model autonomy performance. The SDT classifies the world into binary states and hence oversimplifies the interaction observed in real-world scenarios. Allowing multi-class classification of the world reveals intriguing error patterns previously unexplored in prior literature.MethodThirty-five participants completed 60 trials of a simulated mental rotation task assisted by an AI with 70-80% reliability. Participants' trust in and dependence on the AI system and their performance were measured. By combining participants' initial performance and the AI aid's performance, five distinct patterns emerged. Mixed-effects models were built to examine the effects of different patterns on trust adjustment, performance, and reaction time.ResultsVarying error patterns from AI impacted performance, reaction times, and trust. Some AI errors provided false reassurance, misleading operators into believing their incorrect decisions were correct, worsening performance and trust. Paradoxically, some AI errors prompted safety checks and verifications, which, despite causing a moderate decrease in trust, ultimately enhanced overall performance.ConclusionThe findings demonstrate that the types of errors made by an AI system significantly affect human trust and performance, emphasizing the need to model the complicated human-AI interaction in real life.ApplicationThese insights can guide the development of AI systems that classify the state of the world into multiple classes, enabling the operators to make more informed and accurate decisions based on feedback.

ObjectiveThis study investigates the relationship between motion sickness and body movements experienced by car passengers during non-driving related activities.BackgroundThe theory linking motion sickness to postural instability is well-documented in static environments. However, evidence supporting this theory in dynamic environments, such as moving vehicles, is still lacking.MethodUsing an experimental approach replicating a naturalistic 15-min car ride, 56 participants were equipped with an in-ear sensor to measure the linear accelerations of the head. Participants reported their motion sickness severity at 3-min intervals during the experiment and once more post experimentation. Additionally, the UniPG numerical model was used to estimate motion sickness severity.ResultsThe study identified significant relationships between specific head movement patterns and motion sickness severity, even though the overall symptoms reported were mild. Nonlinear interactions were identified between the standard deviation (p = .032) and the skewness (p = .028) of longitudinal head acceleration, as well as for the skewness (p = .004) and kurtosis (p = .008) of lateral head acceleration. Predictions from the UniPG model correlated with subjective ratings for 67% of participants with some motion sickness symptoms.ConclusionHighly variable longitudinal movements appear more tolerable when lateral movements remain symmetric; however, when both variability and asymmetry in head movements are present together in a specific pattern, they may exacerbate motion sickness symptoms.ApplicationIncorporating motion sickness prediction models in vehicles, based on the measurement of head movements, might improve detection of the escalation of symptoms in car passengers.

ObjectiveThis study investigates the impact of whole-body vibrations caused by external vehicle perturbations, such as aircraft turbulence, on the perception of electrovibration displayed on touchscreens.BackgroundElectrovibration is a promising technology for providing tactile feedback on future touchscreens, potentially addressing usability challenges in vehicle cockpits. However, its performance under dynamic conditions, such as whole-body vibrations caused by turbulence, remains largely unexplored.MethodWe measured the absolute detection thresholds of 24 human participants for short (0.2 s) and long (0.5 s) duration electrovibration stimuli displayed on a touchscreen. These measurements were taken in the absence and presence of two types of turbulence motion (Gaussian and Multisine) generated by a motion simulator. Concurrently, we recorded participants' applied contact force and finger displacements.ResultsElectrovibration stimuli displayed on vehicle cockpit touchscreens were more reliably perceived with a 0.5-s duration than a 0.2-s duration, both in the presence and absence of turbulence. Both turbulence types led to increased vibration-induced finger displacements and scan speeds in the direction of turbulence, as well as higher applied forces and force fluctuation rates. Gaussian turbulence significantly elevated perception thresholds, but only for short-duration electrovibration stimuli.ConclusionThe findings indicate that whole-body vibrations impair the perception of short-duration electrovibration stimuli, primarily due to unintentional finger movements and increased fluctuations in applied normal force.ApplicationOur findings offer valuable insights for the future design of touchscreens with tactile feedback in vehicle cockpits.

ObjectiveThe purpose of this scoping review is to identify physical environmental facilitators and barriers related to performing robotic-assisted surgery (RAS) in operating rooms (ORs).BackgroundAs new robotic surgery technology is developed and brought to market, there is a need to understand how existing and future operating rooms are adapted and designed to support patient safety, surgical workflow, and teamwork. This review will focus on literature related to physical environment factors that impact workflow and communication, as well as the adoption of RAS technology.MethodThe scoping review search was conducted during November 2022, following the PRISMA guidelines. An independent reviewer screened articles for inclusion and exclusion and two independent reviewers completed a quality appraisal was on the included articles.ResultsOf the 9325 texts screened, 28 articles were included for analysis. The primary physical environment and outcome variables were extracted and synthesized under the following categories: RAS process or task-related, environmental features, environmental qualities, and staff or patient outcomes.ConclusionThe physical environment of the OR, such as OR layout, OR size, environmental noise, and dedicated robotic ORs played a significant role in efficiency and workflow outcomes for RAS, as well as workload measures, staff and patient safety, and surgical performance.ApplicationSince there are minimal evidence-based resources available for the application of RAS, this review provides distinct connections between RAS outcomes and specific environmental features for considerations among design researchers, architects, human factors professionals, hospital administrators, and practitioners to aid in decision making during and after implementation of RAS technology.

ObjectiveWe aimed to find objective measures of the impact of spatially disorienting (SD) stimuli on pilot cognition in an ecologically valid environment.BackgroundSD frequently occurs in military rotary-wing operations and often contributes to mishaps. Effects of SD stimuli on pilots are usually quantified using control errors, but effects on cognition have not yet been successfully quantified.MethodMilitary helicopter pilots (n = 14) performed scenarios with six SD stimuli (SD condition) and six corresponding control stimuli (NoSD condition) in a motion-base simulator with integrated virtual reality headset. SD stimuli were: false horizon, featureless terrain, leans, brownout, a somatogyral yaw illusion, and loss of horizon due to night vision goggles (NVGs). Mental workload was measured using auditory arithmetic task performance and attentional focus was measured using eye-tracking.ResultsAverage arithmetic task performance was significantly impaired, and proportional gaze dwell time on the attitude indicator was significantly increased in the SD compared to the NoSD condition. Of the six SD stimuli, the featureless terrain, the leans, and the brownout induced significant effects on performance, whereas the featureless terrain, brownout, and false horizon significantly affected gaze behavior. The NVGs and somatogyral yaw stimuli did not induce significant effects. Pilots' self-reports indicated awareness of all SD stimuli, except for the featureless terrain.ConclusionThe results indicate that SD impacts pilot mental workload and attentional focus.ApplicationModern military aircraft present a large volume of mission-related information to pilots. This study shows that SD stimuli may negatively impact the processing of such information.

ObjectiveThis study investigates students' acceptance of e-learning during the COVID-19 pandemic, examining differences between voluntary and involuntary use contexts.BackgroundDuring the COVID-19 pandemic, universities shifted to online instruction for an extended period. E-learning became mandatory to use and was met with varying degrees of acceptance by students, whose educational expectations and experiences were altered. By 2022, institutions began transitioning to optional e-learning use, creating a natural setting to examine technology acceptance under both voluntary and involuntary conditions.MethodThis study employed a two-phase approach, first validating an extended Technology Acceptance Model (TAM) incorporating seven factors derived from focus groups. Second, conducting multigroup analysis of acceptance between voluntary and involuntary users. Data was collected through surveys from 908 undergraduate students.ResultsPLS-SEM analysis revealed strong explanatory power (R² = .463-.731) for the extended TAM framework. Compatibility demonstrated the strongest effect on perceived usefulness, while information quality and system quality influenced both perceived usefulness and ease of use. Multigroup analysis revealed significant contextual differences in students' acceptance. Perceived ease of use more strongly influenced behavioral intention for voluntary users, while perceived usefulness had stronger effects for involuntary users.ConclusionThe extended TAM framework significantly predicted e-learning acceptance in both voluntary and involuntary contexts. Significant differences between usage scenarios were identified, extending TAM's applicability to crisis situations.ApplicationThis study provides insights for postpandemic educational technology implementation, emphasizing system quality and alignment with learning preferences. Practitioners should consider differences in adoption contexts when working to facilitate acceptance among both voluntary and mandatory users.

ObjectiveCurrent emergency response literature rarely focuses on the intersecting experiences of people with disabilities and first responders. This study employed a person-centered Human Factors approach to assess the experiences of people with disabilities and first responders during emergencies. This research identifies environmental and societal factors that hinder emergency response outcomes.MethodsWe conducted a needs assessment of 126 individuals (95 people with disabilities and 31 first responders). The survey included Likert-style items and open-ended responses. Open-ended items were analyzed using reflexive thematic analysis. An exploratory sentiment analysis was conducted to examine the alignment between qualitative and quantitative responses.ResultsThree major themes emerged: communication barriers, insufficient training, and limited resources. People with disabilities emphasized the importance of respectful, clear, and adaptive communication, while first responders noted challenges related to time constraints, tools, and accessible communication methods. Participants from both groups emphasized the urgent need for technology and training that can provide first responders with the necessary knowledge and skills to improve outcomes for people with disabilities.ConclusionThis needs assessment offers foundational insights into barriers that impact emergency response for people with disabilities and first responders. Actionable Human Factors solutions are proposed.ApplicationThe continued presence of barriers and tensions between the needs of people with disabilities and first responders suggests that Human Factors interventions should be developed to improve communication systems and equipment, training protocols, work systems, and environmental design for accessibility for people with disabilities, while also considering the safety and time-sensitive needs of first responders.

ObjectiveTo examine operator state variables (workload, fatigue, trust in automation, task engagement) that potentially predict return-to-manual (RTM) performance after automation fails to complete a task action.BackgroundLimited research has examined the extent to which within-person variability in operator states predicts RTM performance, a prerequisite to adapting work systems based on expected performance degradation/operator strain. We examine whether operator states differentially predict RTM performance as a function of degree of automation (DOA).MethodParticipants completed a simulated air traffic control task. Conflict detection was assisted by either a higher- or lower-DOA. When automation failed to resolve a conflict, participants needed to prevent that conflict (i.e., RTM). Participants' self-reported workload, fatigue, trust in automation, and task engagement were periodically measured.ResultsParticipants using lower DOA were faster to resolve conflicts (RTM RT) missed by automation than those using higher DOA. DOA did not moderate the relationship between operator states and RTM performance. Collapsed across DOA, increased workload (relative to participants' own average) and increased fatigue (relative to sample average, or relative to own average) led to the resolution of fewer conflicts missed by automation (poorer RTM accuracy). Participants with higher trust (relative to own average) had higher RTM accuracy.ConclusionsVariation in operator state measures of workload, fatigue, and trust can predict RTM performance. However, given some identified inconsistency in which states are predictive across studies, further research is needed.ApplicationsAdaptive work systems could be designed to respond to vulnerable operator states to minimise RTM performance decrements.

ObjectiveWe conducted two experiments to understand the effects of computationally diminishing reality on performance, awareness of the environment, and subjective workload.BackgroundAdvances in extended reality (XR) technologies make it possible to alter or remove auditory and visual distractions from an environment. Though distractions are known to harm performance, there is no work examining the effects of removal via XR.MethodAcross two samples, STEM graduate students and Johnson Space Center employees, the effects of reducing distraction during a novel, demanding assembly task via a form of XR (diminished reality) were compared to a full distraction control condition, studied in a virtual reality (VR) environment. In one condition, participants experienced universal attenuation of distractions. In a second condition, attenuation was context-aware: only nontask objects were made less visible and only unimportant off-task audio was eliminated.ResultsBoth experiments found subjective workload could be lowered via a Diminished reality (DR) aid. The STEM graduate student sample showed a benefit of a DR aid for performance and environment awareness; however, the sample of professionals from Johnson Space Center showed no performance differences with the DR aids. There were mixed results regarding awareness of the location of objects and events outside of the assembly task.ConclusionDR aids can have effects similar to those seen in studies that removed distractions entirely. More work is needed to understand the match between distraction removal design and task.ApplicationThese findings contribute to the development of a class of XR aids: Diminished Reality.

ObjectiveThe goal of this meta-analysis is to investigate the effect of partial automation on mental workload, visual behavior, and engagement in nondriving-related tasks.BackgroundThe literature on the human factors of operating partially automated driving offers mixed findings. While some studies show partial driving automation to result in suboptimal mental workload, others found it to impose similar levels of workload to the ones observed during manual driving. Likewise, while some studies evidence a marked increase in off-road glances when the automated system was engaged, other work has failed to replicate this pattern.Method41 studies involving 1482 participants were analyzed using the PRISMA approach.ResultsNo significant differences in mental workload were found between manual and partially automated driving, indicating no changes in mental workload between the two driving modes. A higher likelihood of glancing away from the forward roadway and engaging in nondriving-related tasks was found when the partially automated system was engaged.ConclusionAlthough the adoption of partial driving automation comes with some intended safety benefits, its use is also associated with an increased engagement in nondriving-related activities.ApplicationThese findings add to our understanding of the safety of partial automation and provide valuable information to Human Factors practitioners and regulators about the use and potential safety risks of using these systems in the real-world.