bluuebunny/crossref_metadata_2025 huggingface dataset:
Student Perspectives on Changing Requirements for Human Factors Engineering Education
Authors: Zhang Bella Yigong , Rantanen Esa M. , Chignell Mark
Published: November 2021

In today’s digital economy, the Internet of Things (IoT) has connected devices, humans, and everyday objects to each other in ways that were unimaginable before. Vast amounts of data are collected everywhere and disrupting how we design systems and products. Data science and emerging technologies offer challenges and opportunities for early-career human factors professionals who are looking to grow their careers and their human factors practice. In this paper, we report on a survey to assess the perspectives of students currently studying human factors. The survey items examined shortfalls in current human factors education with re-spect to relevance to industry trends. The survey results show that students see a need to include more relevant subjects in data science, as well as opportunities to learn trending industry problems, hands-on experience with real-life projects, prior to graduation.
Effects of Human Personal Space on the Robot Obstacle Avoidance Be havior: A Human-in-the-loop Assessment
Authors: Chen Yuhao , Smith Trevor , Hewitt Nathan , Gu Yu , Hu Boyi
Published: November 2021

To ensure both the physical and mental safety of humans during human-robot interaction (HRI), a rich body of literature has been accumulated, and the notion of socially acceptable robot behaviors has arisen. To be specific, it requires the motion of robots not only to be physically collision-free but also to consider and respect the social conventions developed and enforced in the human social contexts. Among these social conventions, personal space, or proxemics, is one of the most commonly considered in the robot behavioral design. Nevertheless, most previous research efforts assumed that robots could generate human-like motions by merely mimicking a human. Rarely are the robot’s behavioral algorithms assessed and verified by human participants. Therefore, to fill the research gap, a Turing-like simulation test, which contains the interaction of two agents (each agent could be a human or a robot) in a shared space was conducted. Participants (33 in total) were asked to identify and label the category of those agents followed by questionnaires. Results revealed that people who had different attitudes and prior expectations of appropriate robot behaviors responded to the algorithm differently, and their identification accuracy varied significantly. In general, by considering personal space in the robot obstacle avoidance algorithm, robots could demonstrate more humanlike motion behaviors which are confirmed by human experiments.
Diminishing Reality: Potential Benefits and Risks
Authors: Murph I. , McDonald M. , Richardson K. , Wilkinson M. , Robertson S. , Karunakaran A. , Gandy Coleman M. , Byrne V , McLaughlin A. C.
Published: November 2021

Within distracting environments, it is difficult to maintain attentional focus on complex tasks. Cognitive aids can support attention by adding relevant information to the environment, such as via augmented reality (AR). However, there may be a benefit in removing elements from the environment, such as irrelevant alarms, displays, and conversations. De-emphasis of distracting elements is a type of AR called Diminished Reality (DR). Although de-emphasizing distraction may help focus on a primary task, it may also reduce situational awareness (SA) of other activities that may become relevant. In the current study, participants will assemble a medical ventilator during a simulated emergency while experiencing varying levels of DR. Participants will also be probed to assess secondary SA. We anticipate that participants will have better accuracy and completion times in the full DR conditions but their SA will suffer. Future applications include the design of future DR systems and improved training methods.
Phone-Related Distracted Walking Injuries as a Function of Age and Walking Environment
Authors: Haolan Zheng , Campbell Isabella M. , Giang* Wayne C.W.
Published: November 2021

Using phones while walking has been a factor that has led to accidents and injuries. However, few studies have analyzed the propensity of injuries due to distracted walking for different age groups and in different types of walking environments. This study aims to examine the number of emergency department (ED) visits due to distracted walking across different age groups and walking environments using a publicly available dataset, the National Electronic Injury Surveillance System (NEISS) database. The results suggest that there were an estimated 29140 distracted walking injuries between the years 2011-2019. Individuals between 11 and 20 years old had the most injuries, followed by 21 to 30, and 31 to 40. Furthermore, the proportion of estimated injuries that occurred in different walking environments differed across age groups. Safety-orient interventions for future research for stairs and home environments were also recommended in the present study.
Working with Industrial Cobots: The Influence of Reliability and Transparency on Perception and Trust
Authors: Kluy Lina , Roesler Eileen
Published: November 2021

Industrial human-robot collaboration (HRC) is not yet widely spread but on the rise. This development raises the question about properties collaborative robots (cobots) need, to enable a pleasant and smooth interaction. Therefore, this study investigated the influence of transparency and reliability on perception of and trust towards cobots. A video-enhanced online study with 124 participants was conducted. Transparency was provided through the presentation of differing information, and reliability was manipulated through differing error rates. The results showed a positive effect of transparency on perceived safety and intelligence. Reliability had a positive effect on perceived intelligence, likeability and trust. The effect of reliability on trust was more pronounced for low transparent robots. The results indicate the relevance of carefully selected information to counteract negative effects of failures. Future research should transfer the study design into a real-life experiment with more fine-grained levels of transparency and reliability.
Influence of Prior General Knowledge on Older Adults’ Takeover Performance and Attitude Toward Using Conditionally Automated Driving Systems
Authors: Zhou Huiping , Itoh Makoto , Kitazaki Satoshi
Published: November 2021

This study aims to investigate the influence of general knowledge, which denotes·driving automation’s taxonomy, definitions, function, driver role, and the request to intervene (RtI), on older adults’ takeover performance when using conditionally driving automation (DA), and to clarify the influence of knowledge on drivers’ attitudes toward DA. We introduced two types of DAs: full range and limited range. A driving simulator (DS) experiment was conducted to collect data, including driving behavior in taking over vehicle control and driver’s subjective evaluation of the DA. Data were collected from 36 elderly (mean age = 71.4±4.8 years) and 36 non-elderly (mean age = 40.8±9.5 years) participants. The results showed significant differences between the elderly and non-elderly, such that educating knowledge had a greater influence on the older adults, that is, instructing knowledge to the drivers contributed to a statistical increase in successful takeover rate from 0.66 to 0.80, but no effect was seen on either the response time or the maximum steering angular velocity. Furthermore, more frequent glance behavior of looking forward from a non-driving related task was observed in the educated groups. Self-rating scores of subjective evaluations revealed that older adults who were given the knowledge had a higher level of trust in and expectation from the DA, and more confidence in comprehending system functions. This study demonstrates the necessity of general knowledge instruction to enhance drivers’ positive attitudes toward DA.
Combining Process Tracing and Policy Capturing Techniques for Judgment Analysis in an Anti-Submarine Warfare Simulation
Authors: Labonté Katherine , Lafond Daniel , Chatelais Bénédicte , Hunter Aren , Akpan Folakemi , Neyedli Heather F. , Tremblay Sébastien
Published: November 2021

The Cognitive Shadow is a prototype decision support tool that can notify users when they deviate from their usual judgment pattern. Expert decision policies are learned automatically online while performing one’s task using a combination of machine learning algorithms. This study investigated whether combining this system with the use of a process tracing technique could improve its ability to model human decision policies. Participants played the role of anti-submarine warfare commanders and rated the likelihood of detecting a submarine in different ocean areas based on their environmental characteristics. In the process tracing condition, participants were asked to reveal only the information deemed necessary, and only that information was sent to the system for model training. In the control condition, all the available information was sent to the system with each decision. Results showed that process tracing data improved the model’s ability to predict human decisions compared to the control condition.
Effect of Computer Keyboard Slope on Upper Limb Postures at Sitting and Standing ComputerWorkstations : A Pilot Study
Authors: Nash Howraa , Nayak Gourav Kumar , Thota Jashwant , Alsowaidi Mohammed , Alsowaidi Hashem , Urbanic Jill , Kim Eunsik
Published: November 2021

A user’s posture at a computer workstation, especially wrist posture, is determined by the keyboard angle. Most commercially available computer keyboards have a built-in positive slope that requires the user to extend their wrist approximately 20° when typing. The purpose of this study is to find the negative keyboard angles that minimize wrist extension for both sitting and standing workstations. In this study, we compared upper limb working postures, including those of the wrist, elbow and shoulder, at 5 different keyboard angles between −16° and +6° in sitting and standing postures. Based on our results, we can conclude that the optimal range of keyboard slope is from −4° to −12° in sitting posture and −8° to −12° in the standing posture in terms of minimum wrist extension, typing performance, and user preference. We also propose a universal keyboard support design as an attachment to currently available keyboards.
Consumer Knowledge and Acceptance of Driving Automation: Changes Over Time and Across Age Groups
Authors: Lee Chaiwoo , Gershon Pnina , Reimer Bryan , Mehler Bruce , Coughlin Joseph F.
Published: November 2021

Increasing availability of and extensive investments toward automation in consumer vehicles call for a better understanding of public perceptions and acceptance. This study presents a five-year series of large-scale surveys (N=17,548, average 3,510 participants/year) on consumer knowledge and acceptance of vehicle automation in the United States. Results suggest a continued hesitance toward use of self-driving vehicles, with willingness to use increasing sharply under hypothetical conditions around inability to drive and added safety assurance. While drivers of all ages were most comfortable with driver assist level automation, acceptance of automation overall decreased with age. Findings also indicate that the public may have incorrect beliefs regarding the availability of self-driving vehicles. In conclusion, drivers’ acceptance of vehicle automation changes over time, is tied to factors beyond the current state of development and deployment, and may depend on a relative assessment of benefits and reliability in comparison to their own driving capabilities.
Visual attention and steering wheel control: From engagement to disengagement of Tesla Autopilot
Authors: Morando Alberto , Gershon Pnina , Mehler Bruce , Reimer Bryan
Published: November 2021

Previous research indicates that drivers may forgo their supervisory role with partial-automation. We investigated if this behavior change is the result of the time automation was active. Naturalistic data was collected from 16 Tesla owners driving under free-flow highway conditions. We coded glance location and steering-wheel control level around Tesla Autopilot (AP) engagements, driver-initiated AP disengagements, and AP steady-state use in-between engagement and disengagement. Results indicated that immediately after AP engagement, glances downwards and to the center-stack increased above 18% and there was a 32% increase in the proportion of hands-free driving. The decrease in driver engagement in driving was not gradual over-time but occurred immediately after engaging AP. These behaviors were maintained throughout the drive with AP until drivers approached AP disengagement. In conclusion, drivers may not be using AP as recommended (intentionally or not), reinforcing the call for improved ways to ensure drivers’ supervisory role when using partial-automation.
Learning ‘Learning Curves’ with R Shiny
Authors: Bernardo Nicholas D. , Macht Gretchen A.
Published: November 2021

Learning curves are fundamental in understanding individual task performance, with ubiquitous implementation in task assignments, worker scheduling, team formulation, etc., in domains bridging from manufacturing to healthcare. With a broad range of applicability, it is critical that students conceptualize, visualize, and build learning curves to activate that knowledge for effective decision-making. This paper describes a hands-on experiential approach for teaching learning curves that utilizes building LEGO® sets with mathematical formulation and data visualization in an open-source R Shiny application. The R Shiny application was designed to educate and inform students of their curve status while automating the power curve fitting calculations. The proposed methodology appeals and applies to students of all ages and was preliminarily field-tested in two collegiate courses and a K-4 after-school program. This paper introduces this approach and the R Shiny app, while future work includes quantifying improved learning.
Gamma Oscillations Index Sustained Attention in a Brief Vigilance Task
Authors: Borghetti Lorraine , Morris Megan B. , Jack Rhodes L. , Haubert Ashley R. , Veksler Bella Z.
Published: November 2021

Sustained attention is an essential behavior in life, but often leads to performance decrements with time. Computational accounts of sustained attention suggest this is due to brief disruptions in goal-directed processing, or microlapses. Decreases in gamma spectral power are a potential candidate for indexing microlapses and discriminating between low and high performers in sustained attention tasks, while increases in beta, alpha, and theta power are expected to exhibit compensatory effort to offset fatigue. The current study tests these hypotheses in a 10-minute Psychomotor Vigilance Test, a context that eliminates confounds with measuring gamma frequencies. 34 participants ( Mage = 22.60; SDage = 4.08) volunteered in the study. Results suggested frontal gamma power declined with time-on-task, indicating reduction in central cognition. Beta power increased with time-on-task, suggesting compensatory effort; however, alpha and theta power did not increase. Additionally, gamma power discriminated between low and high performers, potentially suggesting motivational differences between the groups.
Human-Centered Drone LED Illumination System: A Proof-of-Concept Prototype
Authors: Hao Shuai , Yerebakan Mustafa Ozkan , Hu Boyi
Published: November 2021

Recent years have seen a rapid increase in drone usage in both commercial and personal use, due to recent changes in guidelines by the Federal Aviation Administration (FAA). In those guidelines, however, there seems to be very few requirements in terms of illumination requirements, apart from the need to use a visible strob ing anti-collision light for nighttime operations. Hence in this study, wereviewed existing LED illumination systems in off-the-shelf drones to determine what type of configurations they have and how is the LED illumination system generally used. We also introduced a customizable LED illumination system and tested it in a human in the loop study. Our p reliminary findings have revealed that the colors that are preferred by the participants did not match the most used colors in existing LED illumination systems in most off-the-shelf drones. We also observed a possible relationship between the color preferred and the weather conditions.
Employing a User-Centered Approach for Evaluating a VR-based Pilot Training System
Authors: Montalbano CJ , Abich Julian , Sikorski Eric
Published: November 2021

Researchers took a user-centered approach to evaluate pilots’ preferences and perceptions of training with an innovative VR-based immersive training device (ITD). Over the course of one week, usability and user experience data were gathered from U.S. Air Force instructor pilots (IPs), unqualified instructor pilots (UIs),and student pilots (SP). Coming from various squadrons, these pilots provided feedback regarding their interactions with the ITDs. A think-aloud protocol, observations, and surveys were used to capture participants’ perceptions of the different hardware variants using the following usability metrics: fit and feel, function, and sustained and future use. At this stage of the development, various configurations of the ITDs were evaluated to determine which technological components should be included in the final design. The data presented here focused on one of those components, the aircraft control or center stick. The results for the stick component will be discussed as a use case as it illustrates the user-centered approach and data analysis strategy that captured and identified noteworthy differences in perceived training value.
Developing a Peer Mentorship Program in Human Factors Academia
Authors: Rickel Emily A. , Chaparro Barbara S.
Published: November 2021

Peer mentorship programs that pair more experienced students (i.e., mentors) with less experienced students (i.e., mentees) can have an effective, positive impact on university students’ personal, academic, and professional outcomes. The purpose of this paper is to describe the process and lessons learned in the creation of a peer mentorship program in a Human Factors and Ergonomics (HF/E) academic department. Through a combination of peer networking opportunities and skill development workshops, the mentorship program outlined in this paper aims to promote students’ academic and professional growth. Take-aways that can be utilized by other HF/E academia departments interested in starting or revamping their own peer mentorship programs are included.
End-user Preference for and Understanding of Hurricane Forecast Graphs
Authors: Millet Barbara , Majumdar Sharanya J. , Cairo Alberto , Diaz Carolina , Ding Qinyu , Evans Scotney D. , Broad Kenneth
Published: November 2021

Hurricane forecast graphics have the challenging task of communicating information about spatio-temporal uncertainty. This study assesses the impact of graph literacy and graph format on user preference and understanding. In a laboratory setting, we compared user responses to official National Hurricane Center advisory maps and alternative visualizations. Results indicate that prior experience with a visualization drives preference and that graph literacy, visualization format, and tropical cyclone characteristics, in combination, influence interpretations of hurricane forecast track. The findings from this study are expected to inform redesign efforts of hurricane risk communication products.
Applying change management to general aviation: Pilot self-briefings for weather
Authors: Domingo Cassandra , Blickensderfer Beth
Published: November 2021

General aviation (GA) pilots are increasingly relying on available weather technology to conduct preflight weather self-briefings, rather than call-in briefings to Flight Services. However, research has shown that GA pilots’ have difficulty in interpreting weather products, such as radar, and that this problem persists even after additional training. The domain of change management examines how to properly plan and implement transitions in technology. The current paper examines this transition from call-in to self-briefing using principles of change management, specifically from the Unified Theory of Acceptance and Use of Technology.
Human Factors Considerations in Designing a Portable Dialysis Device: Understanding Patients’ and Care Partners’ Needs for Increased Mobility
Authors: Anna Jónsdóttir Auður , Firestone Siena , Kessler Larry , Kim Ji-Eun
Published: November 2021

The objective of this study is to guide the designs of a portable dialysis device that allows patients with End-Stage Renal Disease (ESRD) greater mobility and flexibility to travel. We gathered patients’ and care partners’ motivations behind their travels along with the barriers they experience when planning an overnight trip. Using a quantitative analysis approach for the open-ended questions along with rank-order of response frequencies, our findings indicate that the majority of the motivations behind participants travel is to visit their family and friends but the participants find themselves either completely hindered or experience significant challenges when planning overnight trips where the designs of current dialysis devices and or the logistics of planning or scheduling treatments in an unfamiliar dialysis center outweigh the enjoyment of traveling. Our results give an estimate of parameters for the largest acceptable size and weight of a portable dialysis device that meets users’ needs. The results of this study help provide the designers of a portable dialysis device with better-targeted solutions to design a device that comfortably supports patients’ mobility and freedom of travel.
Validating the Strategic Task Overload Management (STOM) Model Using MATB II and Eye-tracking
Authors: Zabala Garrett M. , Gutzwiller Robert S.
Published: November 2021

Operators can be overloaded and struggle to make sense of and prioritize multiple tasks. Task selection in these cases is of utmost importance. We replicated an experiment using the Multi Attribute Task Battery II (MATB II) for validating a model of strategic task switching (STOM), adding eye tracking measurement, resulting in a new assessment. Task difficulty affected how operators switched tasks, while priority had little to no effect. Newly measured for STOM, eye tracking revealed a link between task difficulty and time spent performing a task but failed to meet predictions for interest and priority effects. The outcome of the validation effort as it relates to the STOM model, as well as eye tracking implications, are discussed.
Can We Decrease Floor Impact Noise by Changing Walking Patterns? - a Preliminary Report
Authors: Yoon Woojin , Kwon Yujin , Yoon Jaehyun , Choi Seobin , Shin Gwanseob
Published: November 2021

Floor impact noise from the footsteps of neighbors is one of the major social problems among people living in apartment buildings. In this laboratory environment, walking patterns and impact force on the floor were quantified from seventeen young adults while they were walking normally and quietly to investigate how the voluntary quiet walking to reduce the footstep noise would be different from the normal walking. Eight out of the 17 participants walked with a rearfoot strike pattern, and the rest (9 participants) changed their gait pattern to a non-rearfoot foot strike pattern when asked to walk quietly. Both groups showed decreases in impact peak and vertical loading rate, but the magnitude of the decrements was greater for the participants who walked with the non-rearfoot strike pattern. The preliminary result of this ongoing study suggests that people may not walk quietly even they believe to do so, and it warrants further studies to investigate more effective and easy-to-conduct walking strategies to address the floor impact noise issue of apartment buildings.
Visual Search and Decluttering in Tactical Situation Displays: A Computational Modeling Approach
Authors: Lazaro May Jorella , Kim Sungho , Kang Yohan , Hwan Yun Myung
Published: November 2021

Clutter in tactical situation displays (TSD) is a persistent problem that affects pilots’ performance. Decluttering methods such as dimming, dotting, small-sizing and removal have been used in several display types to reduce clutter. This study aims to investigate the effects of different decluttering methods applied in TSD on pilots’ visual search performance. It also aims to uncover the basic psychophysical processes underlying the pilots’ visual search behavior through computational modeling. Data from fifteen Air-Force pilots showed that accuracy is higher and response time is faster when the TSD is decluttered, regardless of the technique. However, when the data was fitted into the hierarchical drift-diffusion model, it was revealed that among the techniques tested, dimming yielded the best search performance based on the model parameters. This study suggests that analyzing behavioral data through computational modeling may lead to better insights that are more practical and applicable in solving the issues in visual search in TSDs.
Stopping Position Matters: Drawing A Better Communication between Pedestrian and Driverless Automated Vehicles on Narrow Roads
Authors: Soshiroda Jun , Lee Jieun , Daimon Tatsuru , Kitazaki Satoshi
Published: November 2021

Automated vehicles (AVs) are expected to be used as mobility services for improving the quality of life in aging rural areas. In this study, we investigated problematic cases of interaction between pedestrians and AVs in Japanese rural areas and observed cases that occurred on narrow roads. To explore a better communication method when pedestrians interact with vehicles, a virtual reality experiment examined the impacts of two communication methods (external human-machine interface and vehicle movement) regarding two types of vehicles (golf cart and bus). The results showed that pedestrians could decide on crossing the road quickly when the AV attempted to reduce speed early and stopped maintaining an appropriate distance from pedestrians. The stopping position is an important contributor to pedestrian decision-making in crossing and attitude toward AVs. The findings of this study have implications for the design of future automated service vehicles in rural areas.
Decision Deferral in a Human-AI Joint Face-Matching Task: Effects on Human Performance and Trust
Authors: Salehi Pouria , Chiou Erin K. , Mancenido Michelle , Mosallanezhad Ahmadreza , Cohen Myke C. , Shah Aksheshkumar
Published: November 2021

This study investigates how human performance and trust are affected by the decision deferral rates of an AI-enabled decision support system in a high criticality domain such as security screening, where ethical and legal considerations prevent full automation. In such domains, deferring cases to a human agent becomes an essential process component. However, the systemic consequences of the rate of deferrals on human performance are unknown. In this study, a face-matching task with an automated face verification system was designed to investigate the effects of varying deferral rates. Results show that higher deferral rates are associated with higher sensitivity and higher workload, but lower throughput and lower trust in the AI. We conclude that deferral rates can affect performance and trust perceptions. The tradeoffs between deferral rate, sensitivity, throughput, and trust need to be considered in designing effective human-AI work systems.
Communication Metrics for Human-Autonomy Teaming: Lessons Learned from us Army Gunnery Field Experiments
Authors: Baker Anthony L. , Fitzhugh Sean M. , Forster Daniel E. , Schaefer Kristin E.
Published: November 2021

The development of more effective human-autonomy teaming (HAT) will depend on the availability of validated measures of their performance. Communication provides a critical window into a team’s interactions, states, and performance, but much remains to be learned about how to successfully carry over communication measures from the human teaming context to the HAT context. Therefore, the purpose of this paper is to discuss the implementation of three communication assessment methodologies used for two Wingman Joint Capabilities Technology Demonstration field experiments. These field experiments involved Soldiers and Marines maneuvering vehicles and engaging in live-fire target gunnery, all with the assistance of intelligent autonomous systems. Crew communication data were analyzed using aggregate communication flow, relational event models, and linguistic similarity. We discuss how the assessments were implemented, what they revealed about the teaming between humans and autonomy, and lessons learned for future implementation of communication measurement approaches in the HAT context.
Design Considerations for the Development of Crowdsourcing Systems
Authors: Harper Samantha B. , Dorton Stephen L. , Creed Glory
Published: November 2021

We present a case study on factors that affect the usability and User Experience (UX) of a crowdsourcing platform for argumentation. While this particular system is focused on argumentation, we have aimed to abstract our findings such that they are generalizable to other use cases so that others may consider these lessons learned and recommendations for the development of more effective crowdsourcing and collaborative work platforms. Several themes were identified in participant responses about the usability and UX of the crowdsourcing system, including a desire for less structure, the need for additional training, the desire for a streamlined workflow and UI, improved navigation, and the enjoyment of interactions with other users.
Manipulating situational risk in human-automation research – Validation of a new experimental paradigm in virtual reality
Authors: Hösterey Steffen , Onnasch Linda
Published: November 2021

Although situational risk has often been postulated as an important contextual factor in the literature of human-automation research, experimental evidence is scarce due to the difficulty operationalizing risk in an ethical way that is comparable to what real life operators can be exposed to. This study serves as a manipulation check of a newly developed experimental paradigm, in which a subjectively experienceable situational risk can be manipulated as part of a virtual reality environment. It is varied by the altitude participants must carry out the tasks in, including the possibility of virtually falling in case of a mistake. Results revealed medium to large effect sizes in subjective as well as objective metrics signifying a more pronounced perception of risk in the higher altitude condition. This is evidence for a successful manipulation of situational risk in a new paradigm that meets the same requirements of other multi-task environments used in human-automation research.
Ethical Decision Making Under Time Pressure: An Online Study
Authors: Yahoodik Sarah , Samuel Siby , Yamani Yusuke
Published: November 2021

Although research in Psychology and Philosophy indicates people’s preference for utilitarian ethics, how people respond to ethically fraught scenarios under time pressure is unclear. In this online experiment, 61 participants viewed videos of a simulated automated vehicle (AV) as it drove in the right lane on a four-lane road and were instructed to intervene if they thought that the vehicle should move to the left lane. At a crosswalk, five pedestrian avatars appeared one, two, or three seconds before projected impact either in the path of the vehicle or the left lane, with a single pedestrian appearing in the opposite lane half the time. Participants avoided the group of five (utilitarian response) but were more likely to veer into the group of five pedestrians at one second before impact than longer durations, violating utilitarian ethics under time pressure. This suggests limited ability to respond to ethical scenarios when taking over AV control at short notice.
Accessibility Retrofit of a Shared Automated Vehicle: Challenges and Lessons Learned
Authors: Tabattanon Kamolnat , D’Souza Clive
Published: November 2021

Driverless shared automated vehicles (SAVs) have the potential to substantially improve independent mobility for the growing number of older adults and people with disabilities who are unable or ineligible to drive. However, early designs and deployments of SAVs have lacked accommodations for people with disabilities. This article describes a case study where post-production modifications were performed on a commercial electric SAV in an attempt to comply with US accessibility guidelines for conventional vehicles. Findings emphasize the key human factors considerations for physical accessibility and some lessons learned in order to inform the broader conversation about the accessible design of emerging SAVs. The case study highlights the need for considering accessibility and usability early in the design of complex technological systems such as automated vehicles.
Stress, Operator Error, and Transportation Accidents
Authors: Crump Caroline , Walenchok Stephen , Johnson Chris , Pauszek Joseph , Young Douglas
Published: November 2021

Psychological and physiological stress impacts information processing at many levels, from attention and perceptual processes to reasoning and decision-making to motor execution. These effects can be highly adaptive, resulting in optimal performance. However, these effects can also result in serious degradation of performance, leading to human errors that often contribute to accidents. In this paper we review the variety of detrimental effects stress can have on different stages of information processing and provide examples of how these deficits can lead to accidents in motor vehicle operation and aviation.
History Trails Assist in the Detection of Hostile Intentions
Authors: Patton Colleen E. , Wickens Christopher D. , Smith C.A.P. , Clegg Benjamin A.
Published: November 2021

Detecting hostile intentions from movements alone is important in many real world scenarios. The current paradigm investigated how visual history trails might aid in the detection of two hostile movement behaviors on a simple display. Participants controlled movement of an icon representing their own ship, while six other ships moved around them. A single ship displayed one of two target hostile behaviors: shadowing (mimicking usership’s movements) or hunting (approaching the usership). Moving their own ship, participants attempted to identify the hostile ship and behavior with history trails that reflected the past nine movements, and without history trails. Detection accuracy was superior with history trails present. History trails also provided a notable benefit for detecting hunting when the hostile ship started farther away from the usership. History trails may be a suitable aid for improving detection of hostile behaviors, but even in this simplified scenario, detection rates remained far from optimal.
Investigating the role of Non-Technical Skills in Railway Traffic Operations through Expert Knowledge Elicitation
Authors: Jarosz* Iga , Lo Julia , Lijs Jan
Published: November 2021

Many high-risk industries identify non-technical skills as safety-critical abilities of the operational staff that have a protective function against human fallibility. Based on an established non-technical skills classification system, methods for expert knowledge elicitation were used to describe non-technical skills in the specific context of train traffic control in the Netherlands. The findings offer insights regarding the skill importance for good operational outcomes, skill difficulty, categorization, and attitudes based on subject matter experts’ opinions. Substantial overlap between the employed non-technical skills framework and the observed expert classification was found, which might indicate that the experts utilize a mental model of nontechnical skills similar to the one used. Furthermore, considerations concerning the organizational culture and the attitudes towards change provide a promising outlook when introducing novel solutions to non-technical skill training and assessment.
Looming in Forensics: Misapplication, Correction and Extension
Authors: Perez Frank A. , Walsh Bong J.
Published: November 2021

In recent litigation Human Factors Experts have been misapplying the analysis of the looming threshold for offset motions. Looming (or image size expansion) analysis is appropriate for a rapid direct approach to an object (i.e., rear-end collisions) but is inappropriate for offset motions. Typically, looming threshold analysis is applied to nighttime driving when approaching a slow-moving or stopped vehicle presenting no visual cues other than rear tail lights. This paper lays out the foundation for looming, derives the accepted mathematical equation, and compares it to the rate of visual angle change, which is more applicable to offset motions. An appropriate offset looming threshold equation is derived. In addition, a special case of collision due to looming combined with lateral motion is addressed which has historical significance in open water vessel navigation.
User Experience: An evaluation of the Pilot Education Platform and Online Learning at Wright State University
Authors: Vredenburgh Michael J. , Stone Paul B. , Cao Caroline G.L.
Published: November 2021

American college students’ lives were upended when the global pandemic reached our shores. Instead of interacting face-to-face, they were forced to attend classes online. This new learning environment required students and faculty to rely on digital platforms provided by their universities. This study evaluated the effectiveness of the Pilot platform at Wright State University, and the user experience by its two primary user populations: students and faculty. Attributes studied include the usability of elements including feedback, assignments, and communication. Recommendations focus on adjusting the grading input for faculty and to standardize an assignment posting method.
Improving Quality of Care in Virtual Visits: Heuristic Evaluations of the User Interface in Telehealth
Authors: Khashe Yalda , Tabibzadeh Maryam , Zhou Daisy
Published: November 2021

The COVID-19 pandemic has expedited the growing rate of reliance on telehealth. Beyond the benefits of telehealth for patients and healthcare providers during atypical circumstances, the changes prompted by the pandemic have possibly altered the position of telehealth to the point that virtual communication will become the new normal. Therefore, the importance of designing an interface to facilitate user interaction with the system and consequently with one another is of utmost importance. Building on Nielsen’s usability heuristics and mapping them to the six aspects of quality of care introduced by the Institute of Medicine, we identify the design features that have the highest impact on the quality of care. Our analysis shows that error prevention and recovery is the most influential design feature, followed by help and documentation, visibility of the system, match between the system and the real world, flexibility and efficiency of use, and user control and freedom.
A Possible Predictor of Visual Discomfort of Viewing Stereoscopic 3D Maps: The Imbalance of Disparity Distributions
Authors: Sun Ganyun , Liu William , Fraser David , Zhang Yun
Published: November 2021

Stereoscopic 3D (S3D) maps provide an accurate 3D representation of terrain texture for the precise perception of Earth’s surface. Visual discomfort on S3D images primarily comes from accommodation-vergence conflict, which is related to disparity (the distance between two corresponding points in the left and right stereo images). Previous studies have identified that disparity characteristics are related to visual discomfort. However, the relation between disparity characteristics and visual discomfort has not been investigated in orthographic S3D maps. It is unknown whether disparity characteristics are good indicators of visual discomfort regarding S3D maps. This study proposed a new visual discomfort predictor and compared it to the disparity characteristics already existing in the IEEE standard 3333.1.1™-2015. The comparisons indicate that the imbalance index can be a good predictor of visual discomfort regarding S3D maps. The predictor will be used in a personalized computational model to predict visual discomfort.
Scaling team training: Using virtual worlds to support learning in massive open online courses
Authors: Siegle Robert F. , Cooke Nancy J. , Schroeder Noah L. , Li Siyuan , Craig Scotty D.
Published: November 2021

The implementation of electronic team training, e-team training, has been used to teach teamwork skills in a wide array of industries. By using e-team training, organizations have seen the observable benefits of improved team effectiveness, faster response times, and reduction in training costs. Those learning from e-team training have reported additional benefits of improved communication skills, learning team leadership tactics, and an improved satisfaction in their training over traditional team training methods. MOOCs, massive open online course, have yet to incorporate e-team training, due to previous technologies having unscalable, limiting constraints. We reviewed literature on how utilizing e-team training in virtual worlds improves current computer-supported collaborative learning ( CSCL) available in MOOCs, examined the constraints, and give recommendations for the best practices of moving e-team training in virtual worlds to at-scale.
Human Factors in Interactive Machine Learning: A Cybersecurity Case Study
Authors: Chignell Mark H. , Chung Mu-Huan , Yang Yuhong , Cento Greg , Raman Abhay
Published: November 2021

Cybersecurity is emerging as a major issue for many organizations and countries. Machine learning has been used to recognize threats, but it is difficult to predict future threats based on past events, since malicious attackers are constantly finding ways to circumvent defences and the algorithms that they rely on. Interactive Machine learning (iML) has been developed as a way to combine human and algorithmic expertise in a variety of domains and we are currently applying it to cybersecurity. In this application of iML, implicit knowledge about human behaviour, and about the changing nature of threats, can supplement the explicit knowledge encoded in algorithms to create more effective defences against cyber-attacks. In this paper we present the example problem of data exfiltration where insiders, or outsiders masquerading as insiders, who copy and transfer data maliciously, against the interests of an organization. We will review human factors issues associated with the development of iML solutions for data exfiltration. We also present a case study involving development of an iML solution for a large financial services company. In this case study we review work carried out on developing visualization dashboards and discussing prospects for further iML integration. Our goal in writing this paper is to motivate future researchers to consider the role of the human more fully in ML, not only in the data exfiltration and cybersecurity domain but also in a range of other applications where human expertise is important and needs to combine with ML prediction to solve challenging problems.
The Impact of Familiarity on Visualizations of Spatial Uncertainty
Authors: Witt Jessica K. , Clegg Benjamin A. , Blalock Lisa D. , Warden Amelia C.
Published: November 2021

While visualization can support understanding complex phenomena, their effectiveness might vary with the recipient’s familiarity with both the phenomenon and the visualization. The current study contrasted interpretations of simulated hurricane paths using student populations from a high frequency hurricane area versus no local hurricane risk. Non-expert understanding of trajectory predictions was supported via two visualizations: common cones of uncertainty and novel dynamic ensembles. General patterns of performance were similar across the two groups. Participants from the high hurricane risk area did show narrower decision thresholds, in both common and novel visualization formats. More variability was consistently considered possible when viewing the dynamic ensemble displays. Despite greater likelihood of experiences with variability of trajectories outside of forecast paths, greater familiarity tended towards narrower interpretations of the need for evacuations within the variability possible. The results suggest an advantage of dynamic ensembles in grasping uncertainty even in populations familiar with hurricanes.
Navigating operating procedures in everyday work in a petrochemical facility: A comparative analysis of WAI and WAD
Authors: Mohammed Ashraf Atif , Son Changwon , Peres S Camille , Sasangohar Farzan
Published: November 2021

This study proposes a novel coding framework to quantify and categorize the differences between Work-As-Imagined (WAI) and Work-As-Done (WAD) based on the Safety-II perspective. While the Safety-I approach focuses on controlling deviations from Standard Operating Procedures (SOPs) as the solution to prevent incidents, this framework aims to describe and code workers’ adaptive behavior while executing their tasks. The proposed framework checks three attributes for each step; “Skip,” “Order,” and “Action” to help decide if WAI aligns with WAD. The framework was tested by applying it to an actual work environment in a petrochemical facility. Initial findings successfully demonstrated the ability of the framework to describe the differences between WAI and WAD.
Enhancing the Revised NIOSH Lifting Equation using ComputerVision
Authors: Greene Runyu L. , Chen Guanhua , Lu Ming-Lun , Hen Hu Yu , Radwin Robert G.
Published: November 2021

Trunk kinematics (i.e. speed and acceleration), a risk factor associated with low back pain (LBP), is difficult to measure in the field and is not incorporated in popular lifting analysis tools. In this study, computationally efficient computer vision-based methods were used to estimate trunk kinematics from video recordings collected in a previous prospective study. We explored the relationships between trunk kinematics and health outcomes, and if incorporating trunk kinematics into the revised NIOSH Lifting Equation (RNLE) may improve its predictability of LBP risk. Significant correlations between the percentage of LBP and the average trunk speed and acceleration were found. A multivariate logistic regression model was constructed using the kinematics variables and the RNLE lifting index (LI) as independent variables to predict the probability that a task was associated with high LBP risk. When trunk kinematics was incorporated to the LI model, the predictability of the model improved significantly ( p=0.003).
Identifying Tools and Technology Barriers to In-Home Care for Children with Medical Complexity
Authors: Parks Reid , Doutcheva Nadia , Umachandran Dhivya , Singhe Nawang , Noejovich Sofia , Ehlenbach Mary , Warner Gemma , Nacht Carrie , Kelly Michelle , Coller Ryan , Werner Nicole E.
Published: November 2021

Family caregivers use tools and technology to provide care for children with medical complexity (CMC) in the home. It is unclear what barriers families experience when using the tools and technology integral to the care and wellbeing of CMC. Our objective was to identify the barriers family caregivers experience in using tools and technology to provide care to CMC in the home. We used contextual inquiry to interview 30 caregivers in their homes and analyzed our data using a deductive content analysis informed by the patient work system (PWS) model and an inductive content analysis to identify emergent barriers. Through these combined analyses, we identified four categories of barriers families experienced using tools and technology to care for CMC: 1) Access and Cost; 2) Usability, which includes the subcategories Functionality, Tool design, Ease of use, and Reliability; 3) Short-term tool impact; and 4) Long-term tool impact. Our results point to the need for further interventions to reduce or mitigate tools and technology barriers to the in-home care for CMC.