Human Factors最新文献

ObjectiveThis study investigates how users' trust evolves during their first ride in a fully driverless robotaxi and how it can be affected by user characteristics, system design, and traffic scenarios.BackgroundAs driving automation technology matures, driverless robotaxis have become available. Despite its immense economic and social potential, public acceptance can be strongly influenced by user trust. Previous research on trust in autonomous vehicles often relied on surveys, driving simulators, or "Wizard of Oz" methods, potentially introducing biases.MethodAn on-road experiment was conducted in commercially operating fully driverless robotaxis on public urban roads. In total, 30 participants with no prior experience riding fully driverless robotaxis were recruited, comprising nondrivers (n = 10), and drivers with (n = 10) and without (n = 10) driving automation experience. Dynamic trust was collected at a 2-min interval during the ride, along with participants' think-aloud for changes in trust. A cumulative link mixed model was used to assess the impact of past driving experience, demographics, and riding time on trust development.ResultsOur findings revealed that dynamic trust increased gradually and stabilized over time, with user heterogeneity playing a moderating role in this process. Further think-aloud data analysis identified key factors in trust formation, including driving style, riding safety and comfort, and user interface design.ConclusionTrust in driverless robotaxis builds progressively with real-world exposure, shaped by user characteristics, vehicle control, and interface design.ApplicationOur findings underscore the importance of considering user heterogeneity in fostering trust and acceptance of robotaxis.

ObjectiveThe aim of this study was to explore the effect of contrast and spatial frequency intensities in a virtual environment on quiet, upright stance.BackgroundVisual feedback provides crucial sensory information to maintain postural control. Changes to contrast sensitivity and spatial frequency in the environment have been shown to influence postural stability; however, there is currently no work examining the influence of environmental contrast and spatial frequency on balance among young healthy populations.Methodology28 healthy participants stood on a force plate, feet together, while wearing a head-mounted display. Participants viewed a virtual room and were exposed to four 60s conditions, each with a modified level of contrast (low or high) and spatial frequency (low or high) of the surrounding wallpaper. Center of pressure and head displacement root mean square and mean power frequency were calculated to quantify balance behavior.ResultsHigher contrast reduced sway, particularly along the AP axis and on a foam surface (COP AP RMS foam: 7.56 ± 1.92 mm vs. 8.61 ± 1.70 mm; HMD AP RMS: 7.46 ± 2.57 mm vs. 8.92 ± 3.20 mm, mean ± SD). Spatial frequency affected only COP ML RMS on foam, with lower spatial frequencies producing slightly greater sway amplitude (7.93 ± 1.93 mm vs. 7.42 ± 1.75 mm).ConclusionIn conclusion, the level of both contrast and spatial frequency in the surrounding environment impact balance control during quiet, upright stance.ApplicationThis study suggests visual environmental cues should be considered when designing environments to reduce fall risk.

ObjectiveThis study examined whether a powered ankle exoskeleton affected street crossing decisions and perceived mental workload of novice users without mobility limitations at a simulated traffic intersection.BackgroundExoskeletons are wearable mobility devices that can impact physical and cognitive performance. Exoskeleton commercialization for the public necessitates evaluations into how these systems influence novices' cognitive reasoning and directed attention in urban environments.MethodsParticipants (n = 20) made street crossing decisions with and without the exoskeleton. Participants walked through a simulated city using a self-paced treadmill and decided whether to cross the street at prespecified distances from the intersection. Cognitive workload perception was measured using the NASA-TLX survey.ResultsNo significant effects of the exoskeleton on street crossing decisions were observed. Rather, data indicated significant reductions in decisions to cross as distance from the intersection increased and with vehicle presence at the intersection. Cognitive workload scores marginally worsened when wearing the exoskeleton.ConclusionStreet crossing decisions were unaffected, but exoskeletons can influence perceived mental workload. These results highlight the importance of designing wearable systems that align with both physical and cognitive task demands. Future studies should incorporate different exoskeletons, tasks, and user groups to determine how these factors influence task performance.ApplicationUnderstanding the interaction between exoskeletons and novice user cognitions can support the development of exoskeletons that provide sufficient physical support without impeding the mental processes needed for their safe and efficient operation. Researchers can also utilize similar procedures to evaluate alternate exoskeleton designs for urban mobility decision making.

ObjectiveThis study investigates the factors influencing drivers' decisions to intervene in conditional driving automation (SAE Level 3) without system alerts or failures.BackgroundIn complex traffic environments, mismatches between drivers' perception of traffic situations and the response of automation can lead to driver-initiated disengagements, even when the system can safely manage events. While such interventions may be safety conservative, they can also disrupt system operations, compromise safety, and reduce user trust.MethodA driving simulation with 23 participants was conducted in which a conditionally automated vehicle encountered a stopped vehicle blocking its lane, with oncoming traffic present in the adjacent lane. The system was programmed to safely overtake using the opposing lane considering the distance to the oncoming traffic. Participants could either remain in automated mode or override the system.ResultsDrivers intervened in more than 20% of events, most often by pressing the brake pedal while approaching the stopped vehicle when the gap to the oncoming traffic was perceived as insufficient. In challenging overtaking gaps, discrepancies between the behavior of a leading human-driven vehicle and the system further increased intervention likelihood, with some drivers misunderstanding the system's ability to detect oncoming vehicles. Although drivers who intervened completed overtaking faster than the system, their maneuvers were marked by abrupt steering and acceleration, raising concerns about encroaching into opposing traffic.ConclusionEnhancing system feedback and better aligning automation behavior with driver expectations may reduce unnecessary disengagements.ApplicationThe findings provide guidance for designing more intuitive automated driving systems that enhance user trust and safety.

ObjectiveThis work examined performance costs for a spatial integration task when two sources of information were presented at increasing eccentricities with an augmented-reality (AR) head-mounted display (HMD).BackgroundSeveral studies have noted that different types of tasks have varying costs associated with the spatial proximity of information that requires mental integration. Additionally, prior work has found a relatively negligible role of head movements associated with performance costs. However, currently no studies have examined the magnitude of costs for spatial integration tasks when information is separated laterally using an AR-HMD.MethodsParticipants completed a spatial integration task in which information to be integrated was separated by multiple lateral visual angles. Participants were required to judge whether XY coordinate numbers were located within a designated red zone presented on a map.ResultsA significant effect of separation distance was found on response time, with no impact on accuracy. The effect of separation on response time increased considerably in the AR-HMD format compared to prior work examining the performance costs on a wide-angle monitor. Head movements became more costly to response time once information began to enter the head field at around 32 degrees of separation.ConclusionsThe current results taken with previous work indicate a task-device interaction, in which head movements become more costly dependent upon the type of information to be integrated.ApplicationOur findings imply the need for careful evaluation of task characteristics when modeling information separation costs on a desktop display for an AR-HMD format.

ObjectiveThis work presents a comprehensive analysis of fundamental performance of crossing-based moving target selection.BackgroundAlthough the crossing interaction with static targets has been theoretically studied, there has yet to be a generalizable, controlled empirical study investigating the fundamental performance of crossing-based selection for moving targets.MethodWe conducted an experiment with stylus input to investigate how users acquire moving targets with crossing compared to pointing as a baseline.ResultsThe most noteworthy finding of our study is that crossing had overall greater advantages over pointing for moving target selection (a 12.37% reduction in task completion time and a 5.88% increase in accuracy rate for orthogonal crossing, and a comparable task time and a 4.71% increase in accuracy rate for collinear crossing). However, the advantages of crossing would be insignificant when targets become larger than approximately 14.69 mm or move slower than 14.69 mm/s.ConclusionCrossing performance varied between collinear crossing and orthogonal crossing. $T=a+blo{g}_2\left(A+\frac{V}{k}\right)-clo{g}_2\left(\frac{W}{2}-\frac{V}{k}\right)$ in (Hoffmann, 1991) can be used to model time performance of crossing-based moving target selection.ApplicationSuch results provide a theoretical foundation for crossing-based interface design with moving objects.

ObjectiveWe developed a taxonomy for human-agent teams (HATs) and conducted a literature review of existing HAT testbeds using our proposed taxonomy.BackgroundWith the increasing interest in HATs, numerous research studies in this field have utilized different testbeds. Despite this, there is a lack of comprehensive understanding regarding the capabilities and limitations of the existing testbeds.MethodWe first developed a taxonomy for HATs by modifying the existing framework for classifying human teams. Our proposed taxonomy comprises ten attributes. Subsequently, using the taxonomy, we analyzed 103 testbeds identified from 235 empirical research studies. After coding each testbed, we conducted frequency analyses on each attribute to determine the distribution of the testbeds.ResultsRegarding team composition, the majority of testbeds afford single human participants paired with few agents, typically in subordinate roles. Also, in most testbeds, the leadership structure is designated, with humans assuming leadership roles, or none. The communication dynamics present an area for further exploration, especially with larger team sizes. Additionally, nearly all reviewed testbeds focus on long-term teams, overlooking dynamics in ad hoc teams, which are common in real-world settings.ConclusionOur findings underscore the importance of further research into diverse team attributes, such as team composition, leadership structure, communication structure, direction, and medium. It would facilitate a deeper understanding of complex team dynamics in HATs and lead to designing effective teams.ApplicationThe current study would be valuable for discussing future research directions when developing new testbeds or designing novel experiments leveraging existing ones.

ObjectiveThis study aims to introduce a novel augmented display technology that enhances visibility of forward vehicles by projecting critical highlighting information onto the windshield, and to validate its effectiveness in improving occupants' reaction, acceptance, and workload.BackgroundThe rapid advancements in autonomous driving technology have brought significant changes to the automotive landscape; however, trust and safety concerns remain major barriers to widespread acceptance. To address these issues, enhancing occupants' reaction efficiency with workload and acceptance in autonomous vehicle operations is critical.MethodUtilizing two distinct highlighting display methods-surface and outline-within a virtual reality simulation, the research examines their effects on occupants' acceptance including perception of safety through AVAM (Autonomous vehicle acceptance model), and workload through NASA-TLX to dynamic road scenarios during autonomous driving.ResultsThe findings reveal that highlighting display significantly enhances acceptance and workload with reaction time, but their effectiveness varies. Surface highlighting was found to better reduce anxiety and increase perceived safety, while outline highlighting more effectively reduced mental demand.ConclusionThese results offer valuable insights into the dynamic interaction between advanced display technologies and autonomous vehicle operations, highlighting the potential benefits and challenges in their implementation to foster broader acceptance of autonomous vehicles.ApplicationBy intuitively projecting critical information during takeover scenarios, this technology addresses trust and safety barriers in autonomous driving, potentially enhancing prompt responses, accelerating autonomous vehicle integration, and improving the overall driving experience.

ObjectiveThis study empirically investigates the embodiment of occupational exoskeletons (OEs) through repeated use.BackgroundOEs are wearable devices designed to assist operators' movements. Their embodiment- the phenomenon by which they come to be perceived as an integral part of oneself - remains underexplored, thus limiting our understanding of OE adoption. We operationalize embodiment through readiness-to-hand (using the device with minimal conscious attention) and sense of ownership (perceiving the device as part of oneself).MethodStudy 1 is a laboratory study using a within-subject design to examine the evolution of embodiment through two single-item scales over repeated training sessions with an upper-limb exoskeleton in a sample of 14 participants. Study 2 is a field study using a cross-sectional design to investigate differences in OE embodiment across 27 operators with varying experience of OE use. Embodiment was assessed using the same measures as in Study 1.ResultsStudy 1 showed that repeated use shifted attention from the device to the task. Additionally, repeated use led to a progressive integration of the exoskeleton within oneself. Study 2 provided similar results, showing that experienced users focused more on the task when using their OEs and exhibited a greater integration of OEs into the self than novice users.ConclusionRepeated OE use is linked to the cognitive disappearance of the exoskeleton and merging of self and device.ApplicationUnderstanding embodiment can guide the development of OEs. Integrating embodiment assessments can optimize implementation strategies and strengthen our understanding of users' adoption and rejection.

ObjectiveThis study investigates how task demand and experience influence perceived available cognitive resources and control mode, and how these factors affect performance under pressure. It also examines how control mode-cognitive resource mismatches impact performance within the contextual control model (COCOM) framework.BackgroundAdaptive decision-making is essential in high-stakes domains. COCOM posits that individuals adopt control modes, which are patterns of decision-making strategies ranging from reactive to planful (Scrambled, Opportunistic, Tactical, Strategic), based on contextual factors like subjectively available time. However, empirical validation of COCOM mechanisms remains limited.MethodThirty-seven participants completed an air traffic control simulation game across three sessions (representing experience) and four task levels. Behavior-anchored questionnaires assessed perceived cognitive resources and control mode. Performance was obtained from simulation logs.ResultsPerceived available cognitive resources decreased with task demand but increased with experience. Participants employed more planful control modes as cognitive resources and experience increased. Cognitive resource appraisals mediated the effect of task demand on control mode. Planful control was associated with higher performance when paired with high cognitive resources and complex tasks. Performance declined when planful modes were chosen despite low perceived resources.ConclusionFindings provide within-person evidence for a mechanistic pathway of adaptive cognitive control, demonstrating that task demand and experience shape cognitive resource appraisals, which in turn influence control mode and performance. Mode-resource alignment is critical for effective decision-making, enhancing performance.ApplicationTraining and decision support can target control mode-cognitive resource alignment by building metacognitive skills for monitoring cognitive resources and selecting appropriate control modes.