bluuebunny/crossref_metadata_2025 huggingface dataset:
UTT: A Conceptual Model to Guide the Universal Design of Autonomous Vehicles
Authors: Carvalho Stephen , Ahire Suyash , Huff Earl W. , Brinkley Julian
Published: February 2021

Autonomous vehicles (AVs) are closer to becoming a reality in changing the landscape of commercial and personal transportation. The launch of these vehicles come with the promise of improved road safety, reduced traffic fatalities, and enhanced mobility. However, there are questions as to whether the design of AVs will meet the needs of everyone, including people with disabilities and older adults. We argue that there exists no conceptual model that guide sthe inclusive design of autonomous vehicles to benefit all intended users. This paper proposes such a model, called the User Transportation-Activity Technology (UTT) model, which supports the inclusive design of AVs. We present a review of current models of assistive technology design and their drawbacks followed by an introduction of the UTT model and its application in AV design. This paper may benefit researchers, designers, and developers of autonomous vehicles interested in addressing accessible design issues in such vehicles.
A Comparison of Rule-Based and Machine Learning Models for Classification of Human Factors Aviation Safety Event Reports
Authors: Darveau Katherine , Hannon Daniel , Foster Chad
Published: February 2021

There is growing interest in the study and practice of applying data science (DS) and machine learning (ML) to automate decision making in safety-critical industries. As an alternative or augmentation to human review, there are opportunities to explore these methods for classifying aviation operational events by root cause. This study seeks to apply a thoughtful approach to design, compare, and combine rule-based and ML techniques to classify events caused by human error in aircraft/engine assembly, maintenance or operation. Event reports contain a combination of continuous parameters, unstructured text entries, and categorical selections. A Human Factors approach to classifier development prioritizes the evaluation of distinct data features and entry methods to improve modeling. Findings, including the performance of tested models, led to recommendations for the design of textual data collection systems and classification approaches.
Friendlier Skies: Development of Electronic Checklists for Emergency Procedures for the KC-135 Stratotanker
Authors: Bailey Fausset Cara , Weldon Elizabeth , Williams Latrice , Boyle Matt , Cartwright Kevin , Robinson Mark , Bosch Joe , Crosland Marcia , Meeks Bayne
Published: February 2021

The KC-135 Stratotanker has been a workhorse aircraft for the U.S. Air Force and Air National Guard for over 60 years. The aircraft and its technologies have had many modifications and updates over the decades, but the Emergency Procedures (EPs) section of the KC-135 In-Flight Manual has only been updated based on engineering modifications and incident and accident reports. The goal of this project was to systematically assess, identify, and document issues in the KC-135 EPs using aviation checklist design guidance and a crew-centric human factors approach. Electronic checklists were then created to address the issues in the KC-135 EPs. The number of emergency procedures was reduced by over 50%: 351 KC-135 EPs were streamlined into 154 electronic checklists. The revised electronic checklists for emergency procedures will optimize KC-135 crew responses to non-normal situations and ensure safe and efficient operation of the KC-135 beyond its projected sunset in 2040.
Investigating attitudes towards drone delivery
Authors: Eißfeldt Hinnerk , End Albert
Published: February 2021

In recent years, civil drones have become increasingly present in the media and in everyday life. There has been a high level of interest in drone delivery from the very beginning, yet public acceptance of drone delivery still seems limited, with acceptance rates usually ranging from 30 to 40%. The present paper reports findings of a representative national study about the acceptance of civilian drones in Germany. Several factors limiting public support of drone delivery are identified, such as concerns about traffic safety, noise, and animal welfare. In addition, gender effects are discussed, showing female respondents to be more critical about drone delivery in general. Moreover, an effect of NIMBYism is confirmed in the context of drone delivery: Even residents who envision using drones for delivering their own parcels frequently state that they would not agree to flights over their own homes. This particular effect is termed ‘NOMOH’ (‘Not Over My Own Home’).
Frontiers of Human-Machine Teaming: How Human Factors Is Contributing
Authors: Rayo Michael F. , Rayo Michael F. , Roth Emilie M. , Morison Alexander M. , Zelik Daniel J. , Trent Stoney A.
Published: February 2021

Although the majority of effort in Artificial Intelligence (AI) ideation, design, and development seeks to optimize the AI as the primary method of optimizing overall system performance, the evidence is clear that for risk-critical work in high-complexity, high-uncertainty settings, it is the interactions between human and machines that must be prioritized. Only be effectively coordinating the available machine and human agents can the system be resilient to an increasing set of system demands. This panel will convey the work that they are doing and obstacles they are facing in the following areas: (1) demonstrating the critical importance of human-machine teaming, (2) hardening design patterns that result in successful human- machine teams, (3) designing and evaluating new automation solutions for their ability to team, and (4) ensuring that new automation solutions are implemented and adopted for risk-critical work.
Trusting the X in XAI: Effects of different types of explanations by a self-driving car on trust, explanation satisfaction and mental models
Authors: Schraagen Jan Maarten , Elsasser Pia , Fricke Hanna , Hof Marleen , Ragalmuto Fabyen
Published: February 2021

There is an increasing demand for opaque intelligent systems to explain themselves to humans, in order to increase user trust and the formation of adequate mental models. Previous research has shown effects of different types of explanations on user preferences and performance. However, this research has not addressed the differential effects of intentional and causal explanations on both users’ trust and mental models, nor has it employed multiple trust measurement scales at multiple points in time. In the current research, the effects of three types of explanations (causal, intentional, mixed) on trust development, mental models, and user satisfaction were investigated in the context of a self-driving car. Results showed that participants were least satisfied with causal explanations, that intentional explanations were most effective in establishing high levels of trust, and that mixed explanations led to the best functional understanding of the system and resulted in the least changes in trust over time.
ISO Human-Computer Interaction Standards: Finding Them and What They Contain
Authors: Green Paul
Published: February 2021

An HFES Task Force is considering if, when, and which, HFES research publications should require the citation of relevant standards, policies, and practices to help translate research into practice. To support the Task Force activities, papers and reports are being written about how to find relevant standards produced by various organizations (e.g., the International Standards Organization, ISO) and the content of those standards. This paper describes the human-computer interaction standards being produced by ISO/IEC Joint Technical Committee 1 (Information Technology). Subcommittees 7 (Software and Systems Engineering) and 35 (User Interfaces), and Technical Committee 159, Subcommittee 4 (Ergonomics of Human-System Interaction), in particular, the contents of the ISO 9241 series and the ISO 2506x series. Also included are instructions on how to find standards using the ISO Browsing Tool and Technical Committee listings, and references to other materials on finding standards and standards-related teaching materials.
The Unreasonable Ineptitude of Deep Image Classification Networks
Authors: Mueller Shane T. , Agarwal Priyansh , Linja Anne , Dave Nisarg , Alam Lamia
Published: February 2021

The success of deep image classification networks has been met with enthusiasm and investment from both the academic community and industry. We hypothesize users will expect these systems to behave similarly to humans, and to succeed and fail in ways humans do. To investigate this, we tested six popular image classifiers on imagery from ten tool categories, examining how 17 visual transforms impacted both human and AI classification. Results showed that (1) none of the visual transforms we examined produced substantial impairment for human recognition; (2) human errors were limited to mostly to functional confusions; (3) almost all visual transforms impacted nearly every image classifier negatively and often catastrophically; (4) human expectations about performance of AI classifiers map more closely onto human error than AI performance; and (5) models trained with an enriched training set involving examples of the transformed imagery achieved improved performance but were not inoculated from error.
An Exploratory Study of a Masking Strategy of Cyberdeception Using CyberVAN
Authors: Aggarwal Palvi , Thakoor Omkar , Mate Aditya , Tambe Milind , Cranford Edward A. , Lebiere Christian , Gonzalez Cleotilde
Published: February 2021

During the network reconnaissance process, attackers scan the network to gather information before launching an attack. This is a good chance for defenders to use deception and disrupt the attacker’s learning process. In this paper, we present an exploratory experiment to test the effectiveness of a masking strategy (compared to a random masking strategy) to reduce the utility of attackers. A total of 30 human participants (in the role of attackers) are randomly assigned to one of the two experimental conditions: Optimal or Random (15 in each condition). Attackers appeared to be more successful in launching attacks in the optimal condition compared to the random condition but the total score of attackers was not different from the random masking strategy. Most importantly, we found a generalized tendency to act according to the certainty bias (or risk aversion). These observations will help to improve the current state-of-the-art masking algorithms of cyberdefense.
Observation and Records of Spatial Behavior For Wayfinding: A Case Study in a Hospital Built Environment
Authors: Rangel Márcia M. , Mont’Alvão Claudia
Published: February 2021

Autonomous and intuitive displacement is a parameter to verify the potential of information for spatial orientation in a built environment. Being oriented implies not getting lost on the route linked to a task, both in known or unknown environments. This topic is a maximum measurement of a user's behavior in their displacement. First, some main concepts will be presented, proposing some indicators for users’observation in the built environment. After that, a case study will be presented, using the indicators that are proposed based on the task, routes, strategies, and user behavior for a data collection. As a result, this data was checked with the Visibility Index (VI) method.
Employee Reactions to Electrochromic Glass Windows in a Financial Office Building
Authors: Hedge Alan , McKee Cameron
Published: February 2021

A post occupancy evaluation survey of workers in a new financial office building with EC windows was conducted. Results show that those occupants with window views responded more favorably to the effects of the EC windows than those who did not have these views. Most occupants did not report eyestrain or headache. Significantly more occupants with EC window views reported comfortable daylight, better daylight quality, better daylight satisfaction, better alertness, greater energy, relaxation and happiness at work, better sleep quality, and increase productivity. Implications of these findings are discussed.
Understanding Veteran Attitudes, Interests, and Needs around Virtual Care Applications
Authors: Saleem Jason J. , Moon Brian , Bross Emma , Anders Shilo , Conway Brandon , Wilck Nancy R. , Frisbee Kathleen L. , Herout Jennifer
Published: February 2021

Given the substantial increase in interest and activity in the virtual care space, the Department of Veterans Affairs (VA) is making a concerted effort to increase opportunities for Veterans to adopt virtual care applications. We investigated Veteran attitudes, interests, and needs for virtual care applications, including privacy considerations and specific types of data they would be comfortable sharing with their providers through various Veteran-facing tools. We administered a 28-item questionnaire to 40 Veterans and performed follow-up interviews with a subset of nine Veterans. Study results revealed broad support by Veterans for using virtual care applications, including wearable devices, for sharing all types of health information with their providers. Further, Veterans expressed a desire for consolidation across VA-provided virtual care tools. Our findings will inform a strategy for Veteran-facing tools. Other health care systems may be interested in exploring these topics, based on our study results.
A Heuristic Evaluation of Usability for Environmental Control Units’ Eye-Tracking Interfaces at Veterans Affairs Spinal Cord Injuries and Disorders Centers
Authors: Hancock Gabriella M. , Anvari Sam S. , Mok Nicole B. , Ayvazyan Aram , Bai Xiaolu , McCoy Kelsey M. , Nare Matthew T. , Mather Gregory P. , Machado Carmen L. , Chompff Rebecca M.E. , McBride Amanda S. , Morales Natalia
Published: February 2021

Heuristic evaluation is a valid method for assessing interface usability. Results derived from these methods are useful in identifying the most impactful design elements influencing usability and user experience of a system. By establishing the features in need of most improvement, designers can more effortful consider their approaches for iterative efforts to improve usability and user experience. This work used established design principles (i.e., Shneiderman’s Golden Rules and Nielsen’s Heuristics) to analyze the inpatient environmental control units deployed at VA Spinal Cord Injuries and Disorders (SCI/D) Centers to assist with task completion, foster independence, and improve the quality of life in veterans with spinal cord injuries and disorders. Analyses revealed many usability issues in the current interface, varying in severity from minor to catastrophic. Specific design recommendations to address these issues are provided.
A Systematic Review of The Semantic Vigilance Literature
Authors: Neigel Alexis R. , Dhanani Lindsay Y. , Waldfogle Grace E. , Claypoole Victoria L. , Szalma James L.
Published: February 2021

The present study sought to review and summarize the extant literature on semantic vigilance, or lexical vigilance, to benchmark the performance, stress, and workload associated with such tasks. This review also seeks to better define and describe semantic vigilance in relation to the vigilance taxonomy (Parasuraman & Davies, 1977; Parasuraman, Warm, & Dember, 1987). In a database search, 5499 records were identified. After removing duplicates and screening articles based on the inclusion criteria, 8 full-text articles on semantic vigilance were retained for further analysis. The results of this review indicated that semantic vigilance tasks, while short in length, reliably produce a traditional vigilance decrement that is associated with high workload and low stress state scores. While a nascent field of research, this review identified several gaps within the field including limitations in participant selection and inclusion, a lack of application to real world semantic vigilance tasks, and limited variability in the stimuli used for measuring semantic vigilance performance over time.
Evaluating Postural Risk Level of Digitally Represented Workplace: Analyzing Postural Possibilities
Authors: Moon Hayoun , Park Woojin
Published: February 2021

Eliminating awkward and stressful working postures through the ergonomics workplace design is important in preventing work-related musculoskeletal disorders. However, effective design tools are currently lacking. Different postural analysis tools have been proposed to help evaluate workplaces in the level of postural stresses experienced by the workers, but they are not capable of supporting the proactive ergonomics in design. In an effort to address the problem, this study presents a novel memory-based workplace evaluation (MBWE) model. When given an input scenario expressed in terms of the worker anthropometric characteristics, the task requirement, and the geometric descriptions of the to-be-evaluated workplace design, the model computes the range of feasible working postures for the scenario, determines their postural stress levels, and presents a report on the overall postural risk level of the input scenario. The MBWE model combines the memory-based posture planning (MBPP) model and the Ovako working posture analysis (OWAS) method.
Prediction of Occupational Physical Activities using Inertial Measurement Units and Deep Learning Models
Authors: Yan Yishu , Fan Hao , Li Yibin , Hoeglinger Elias , Wiesinger Alexander , Barr Alan , Adamson Carisa Harris
Published: February 2021

Many workers engaged in manual material handling (MMH) jobs experience high physical demands that are associated with work-related musculoskeletal disorders (WMSD). Quantifying the physical demands of a job is an important legal requirement in the US that is used by human resources in the job hiring process. Most physical demands analysis (PDA) are performed using observational and semi-quantitative methods. The lack of accuracy and reliability of these methods can create problems when assigning acceptable tasks to an injured worker. In this study, various deep learning models were applied to data from eight inertial measurement units (IMUs) to predict 15 occupational physical activities (OPA). Overall, a 95% accuracy was reached by convolutional neural network (CNN) for predicting occupational physical activities when performed in isolation. More work is needed to estimate the accuracy of the model when OPA elements are combined into a more complex task.
A Machine Learning Approach to Hand-Arm Motion Prediction for Active Upper Extremity Occupational Exoskeleton Devices
Authors: Kudernatsch Simon , Wolfe Christopher , Ferdowsi Hasan , Peterson Donald
Published: February 2021

Exoskeleton devices are currently being utilized in a variety of occupational settings to reduce musculoskeletal efforts to lower fatigue, improve performance, and minimize work-related injuries associated with musculoskeletal disorders (MSDs). The intrinsic challenges that accompany the development of fully supporting and active upper extremity multi-degrees of freedom (DOF) devices include not only the mechanical design, but also lack of an intuitive way to control and operate these devices. A proof-of-concept instrumented handle consisting an embedded sensor network was developed with the intention to utilize artificial neural networks (ANN) to properly identify the intended motion of the user and to estimate the motion intensity. Results show this method is feasible and delivers useful insight into developing the next stages of the “smart handle” technology that will include the remaining hand motions, correctly classifying combination of intended motions and using the handle output to control complex multi-DOF upper extremity exoskeletons devices.
Predicting Shoulder Joint Reaction Forces From 3D Body Kinematics: A Convolutional Neural Network Approach
Authors: Mubarrat Syed T. , Chowdhury Suman K. , Nimbarte Ashish D.
Published: February 2021

This study aimed to develop a convolutional neural network (CNN) model to predict shoulder joint reaction forces from 3D body kinematics. Results showed a good convergence between CNN model prediction and musculoskeletal model estimation for six novel tasks. Therefore, a CNN-based deep learning model can be used as a simple and relatively less time- and labor-intensive method to identify unsafe shoulder exertions in order to prevent the incidence of shoulder injuries or pathologies in occupational settings.
Monitoring muscle fatigue following continuous load changes
Authors: Yoon Woojin , Shin Gwanseob
Published: February 2021

Human-Robot collaboration (HRC) have been actively applied in industry in a form of interactacting with workers by detecting their muscle fatigue. During repetitive movements such as dynamic muscle contractions, the information of decrement of electromyography (EMG) center frequency can suggest muscle fatigue occurred. However, the method was not evaluated both for development and recovery of muscle fatigue during such dynamic situations. If the decrement can be detected during the work without interruptions, the method can be highly useful in the industry. This study aims to confirm validity of the dynamic fatigue evaluation method using the wavelet transform in both direction of fatigue (development and recovery) by varying load intensity. Seventeen healthy males conducted four sets of repetitive elbow flexion-extension exertions work with one set of 2-minute work with a 2 kg weight (‘heavy work’) and then another with an 1 kg weight (‘light work’). Muscle fatigue was quantified by calculating the EMG center frequency from dynamic evaluation and static evaluation for each set of exertion work task. In the result, the EMG center frequency was significantly decreased during every ‘heavy work’ and increased during every ‘light work’, which was consistent with the result from dynamic fatigue evaluation based on the wavelet transform. The result suggests the possibility of monitoring muscle fatigue in real-time in industry and providing a guideline in designing a human-robot interaction system.
Development of a Civilian 3d Hand Scan Database
Authors: Juhnke Bethany , Pokorny Colleen , Griffin Linsey , Sokolowski Susan
Published: February 2021

Despite the complexity of the human hand, most large-scale anthropometric data for the human hand includes minimal measurements. Anthropometric studies are expensive and time-consuming to conduct, and more efficient methods are needed to capture hand data and build large-scale civilian databases to impact product design and human factors analyses. A first of its kind large-scale 3D hand anthropometric database was the result of this study with 398 unique datasets. This database was created at minimal cost and time to researchers to improve accessibility to data and impact the design of products for hands.
When User Research Leads Design Astray
Authors: Karn Keith , Harper Christy , Rantanen Alisa , Edwards Rochelle , Bartha Michael C.
Published: February 2021

User research in all its forms—from early ethnographic studies to late stage usability validation studies— undoubtedly can add value to any product design and development process. At its best, user research is tightly integrated with the design process, and designers and other team members eagerly seek out research findings to guide design decisions. At its worst, user research can hinder rather than help the efforts of the larger product design and development team—answering the wrong questions, providing misleading information, and focusing attention on issues that are not critical to product success. This can lead to friction between researchers and designers and other members of the product development team. This panel addresses the challenges of integrating user research into the product development process in a way that truly adds value, while suggesting ways to avoid common pitfalls that can result in user research leading designers astray.
Arranging Icons on Small Displays: Do Hexagonal Layouts Improve Search Performance?
Authors: Bouwman Tassilo , Brumby Duncan P.
Published: February 2021

Mobile devices with small displays can use hexagonal layouts of circular icons to use space more efficiently – we test whether this design choice improves people's search performance. An experiment is reported in which 24 participants performed known-item searches of menus that varied along four dimensions: (1) whether icons were arranged using a hexagonal or a grid layout, (2) how closely icons were placed next to each other, (3) the number of icons in the display that shared the same color as the target, and (4) whether icons stayed in the same location or moved between trials. Results show that search times were faster with hexagonal layouts but only when there were many same-color distractors and icons were packed very close to each other. This work contributes new empirical findings on how icon arrangements, in interaction with other critical visual design features, affect search performance.
Load Carriage affects Kinematics during Ingress and Egress on Simulated Travelators
Authors: Charbonneau Alexa , Garson Ben , Bisoffi Fiona , Esparza Stephanie , Bhakta Miral , Bailey Luke , Soangra Rahul
Published: February 2021

Technology advancements has impacted the quality of life in the modern world. Nowadays travelators found popularly as conveyers in airports have been widely used but it is not known how load carriage affects Ingress/egress on travelators. Ten healthy young adults stepped off a metal platform onto a forward moving treadmill belt at a given speed and then stepped on to a second platform. Data was collected to understand how load carriage could influence ingress and egress in participants. Participants were tested for four conditions (load, No load, speed of 0.3 m/s and 0.6 m/s). Load carriage at speed 0.6 m/s were found to have significantly higher knee flexion angles. Ankle angles measured for ingress presented different trends amongst the four conditions. Load carriage at speed 0.6 m/s showed greater plantarflexion compared to the other three conditions. Our future work will assess effects of load carriage on travelators among older adults.
Human-Centered Design of GRE Preparation Applications for Non-Native English Speakers
Authors: Martell Matthew , Xing Yilun , Sun Xiaonan , Kim Ji-Eun
Published: February 2021

The Graduate Record Examination (GRE) is a primary barrier to entry into US graduate programs for non-native English speakers. The goal of this study is to develop a GRE preparation mobile phone application for non-native English speakers through the human-centered design cycle. We conducted a Cognitive Task Analysis and Knowledge Audit for the Magoosh GRE App to identify the most difficult tasks while using the app. We proposed features to help with the most difficult tasks and implemented the most promising feature through iterative prototyping taking into account user feedback. Usability testing for the most recent prototype demonstrates the need for a GRE preparation app targeted at non-native English speakers. Results show that the additional functionality added in the prototype shows promise for assisting non-native English speakers in studying for the GRE.
Real-Time Gaze-Aware Cognitive Support System for Security Surveillance
Authors: Marois Alexandre , Lafond Daniel , Williot Alexandre , Vachon François , Tremblay Sébastien
Published: February 2021

Security surveillance entails many cognitive challenges (e.g., task interruption, vigilance decrements, cognitive overload). To help surveillance operators overcome these difficulties and perform more efficient visual search, gaze-based intelligent systems can be developed. The present study aimed at testing the impact of the Scantracker system—which pinpointed neglected cameras while detecting and correcting attentional tunneling and vigilance decrease—on human scanning behavior and surveillance performance. Participants took part in a surveillance simulation, monitoring cameras and searching for ongoing incidents, and half of them was supported by the Scantracker. Although behavioral surveillance performance was not improved, participants supported by the Scantracker showed more efficient gaze-based measures of surveillance. Moreover, some of these measures were associated with performance, suggesting that scan pattern improvements might lead indirectly to more efficient incident detection. Overall, these results speak to the potential of using gaze- aware intelligent systems to support surveillance operators.
Stress Management and Air Traffic Control Trainees: Development and Evaluation of a New Training Course
Authors: Barrett Jamie D. , Torrence Brett , Bryant Michelle , Pierce Linda , Buck Julia
Published: February 2021

The primary mission of the Federal Aviation Administration (FAA) is to maintain the safety of the National Airspace System (NAS). As part of this mission, the FAA is tasked with ensuring that future air traffic controllers are adequately trained to perform the high-risk job of directing air traffic. The FAA Academy curriculum for newly hired controllers involves 3-4 months of intensive lessons and performance assessments. It has been suggested that this training program is quite stressful, and successful trainees tend to be those who can better manage stress. To support ATC trainees, researchers at the Civil Aerospace Medical Institute (CAMI) have conducted operational research to develop and evaluate a stress management training to help trainees manage their stress during training at the FAA Academy.
Effects of Audio Learning on Semi-Autonomous Driving Safety
Authors: Chen Hung-Tao M. , Thomas Megan
Published: February 2021

Semi-autonomous driving has been found to require less cognitive resources from drivers. It is not immediately clear if engaging in secondary tasks such as audio learning is safe in a semi-autonomous driving situation, especially considering the finding that semi-autonomous drivers tend to be less engaged. The current study investigated the effects of audio learning during a simulated semi-autonomous driving situation. Our results indicated that audio learning could delay warning message reaction time, and drivers had worse audio learning performance in a simulated semi-autonomous driving situation. Implications of current findings on driver safety, audio learning, and forensic practices are described in the discussion section.
Novices Perform Like Experts on a Closed Card Sort but Not an Open Card Sort
Authors: Robertson Ian , Kortum Philip , Oswald Frederick L. , Ziegler Acemyan Claudia
Published: February 2021

Developing good psychological measures benefits from the input of content experts. For many constructs or domains, however, who constitutes an ‘expert’ might be ill-defined. Novices—such as students, customers, or co-workers—may possess the same knowledge as experts. Moreover, as convenience samples, novices are more readily available and less costly. Card sorting is a technique frequently used in human factors to elicit expert knowledge. This study compared novice and expert performance on a card sort task under two conditions, an open sort and a closed sort. Because the closed sort offered a category structure for sorting, it was predicted and found that novices in the closed sort tended to match expert sorting results more closely than in the open sort. The structure also made novice solutions better approximate the expert open sort. This suggests that novices can be useful in the follow-up stage of measure development, but not in the initial stage.
Face-to-Face and Online Friendships: Examining Differences in Trust and Distrust Based on Modality
Authors: Griggs Andrew C. , Rickel Emily A. , Lazzara Elizabeth H. , Frederick Embry-Riddle Christina M.
Published: February 2021

There is growing concern that the quality and psychological benefits of online friendships are not comparable to their face-to-face counterparts. Trust is a key component of relationships and has been studied within the context of virtual relationships for decades. However, previous literature has not thoroughly explored differences in trust among online friendships and online gaming friendships specifically. The purpose of this study was to examine differences in trust and distrust in online friendships based on the relationship’s modality (face-to-face or online). We collected questionnaire responses from participants ( n = 253) regarding characteristics of their friendships as well perceptions of trust and distrust within these relationships. Repeated measures multivariate analysis of covariance did not reveal statistically significant differences between trust and distrust as a function of friendship modality. We discuss these results in terms of theoretical and practical implications for modern friendships and offer recommendations for future research.
Evaluation Methodologies for Virtual Reality and Physical Test Environments for Spaceflight Design
Authors: Litaker Harry , Archer Ron , Montoya Brett , Howard Robert
Published: February 2021

NASA human factor design engineers wanted to examine if there would be any differences in testing low-fidelity conceptual designs in a physical environment compared to a virtual environment. An evaluation of two identical environments was conducted with subject matter experts (SMEs). Results indicated that when testing a design concept at this early stage, a high correlation between the two environments exists, meaning SMEs found little to no difference when evaluating a design in either a physical or a virtual environment. There are advantages and limitations to both environments. The virtual world gave the experts a better sense of the microgravity space and the relationships of space and human presence that are difficult to simulate in a 1-g physical environment. However, the interaction between human and mechanics is better enhanced in the physical world compared to the virtual world. These advantages and limitations of each environment are important; thus, at this early design life cycle phase, virtual reality shows great promise as an evaluation environment for testing early design concepts that will cost less, give more options, and increase designer’s time to design.
The Impact of Mental States on Semi-autonomous Driving Takeover Performance: A Systematic Review
Authors: Huang Gaojian , Petersen Christine , Pitts Brandon J.
Published: February 2021

Semi-autonomous vehicles still require drivers to occasionally resume manual control. However, drivers of these vehicles may have different mental states. For example, drivers may be engaged in non-driving related tasks or may exhibit mind wandering behavior. Also, monitoring monotonous driving environments can result in passive fatigue. Given the potential for different types of mental states to negatively affect takeover performance, it will be critical to highlight how mental states affect semi-autonomous takeover. A systematic review was conducted to synthesize the literature on mental states (such as distraction, fatigue, emotion) and takeover performance. This review focuses specifically on five fatigue studies. Overall, studies were too few to observe consistent findings, but some suggest that response times to takeover alerts and post-takeover performance may be affected by fatigue. Ultimately, this review may help researchers improve and develop real-time mental states monitoring systems for a wide range of application domains.
Predicting the Cross-sectional Areas of Low Back Intervertebral Discs: Archived Medical Record Versus MRI Scans from Asymptomatic Subjects
Authors: Tang Ruoliang , Gungor Celal , Sesek Richard F. , Gallagher Sean , Davis Gerard A. , Foreman Kenneth Bo
Published: February 2021

Evidence suggests that biomechanical models should consider the variations in spinal geometry, particularly the geometry of the intervertebral discs (IVDs), to investigate the mechanism and pathogenesis of low back pain (LBP). Regression models, as a non-invasive and indirect method, have been developed using anthropometric variables to estimate the size of the IVDs, with two major sources of geometric data, archived medical record (AMR) from hospital database and samples of subjects asymptomatic of LBP (ASY). Unfortunately, there is a lack of comparison of model performance and validity between the two approaches. The objective of this study was to compare the two approaches of model development. Results from this study may help determine whether it is feasible and plausible to apply AMR-derived regression models to estimate the geometry of the low back IVDs and help develop more personalized workplace ergonomic assessments in industry.
A depth camera-based full-body reconstruction method for body pose training in occupational safety
Authors: Li Li , Chen Ken , Chen Karen , Xu* Xu
Published: February 2021

Occupational injuries have high incidence rates across various industries. Safety education is a key component to effectively reduce work-related injuries. Posture training for work safety is widely adopted to increase the awareness of unsafe movements at work and to evaluate workers to minimize work-related musculoskeletal stresses. However, existing one-size-fits-all pamphlet-based posture training is facing challenges in its effectiveness. In recent years, the substantial technological development in virtual reality (VR) and augmented reality (AR) has made immersive and personalized education possible. For VR/AR-assisted posture training, full-body reconstruction from multiple point clouds is the key step. In this study, we propose a fast and coarse method to reconstruct the full-body pose of safety instructors using multiple low-cost depth cameras. The reconstructed body images from depth cameras are registered through iterative closet point algorithm. The reconstructed full-body pose can be further rendered in VR/AR environments for next-generation safety education.
Does a New Version of the Direction Orientation Task Measure Spatial Ability?
Authors: Sweet Jacqueline , Coyne Joseph , Herdener Nathan , Ries Anthony J.
Published: February 2021

The US Air Force, Navy and Marine Corps use the direction orientation task (DOT) to assess spatial ability of potential pilots. However, recent research has shown limitations with the current implementation of the DOT, as well as an earlier candidate replacement the DOT 2. Specifically, there is evidence to suggest that the use of a math strategy and math ability may be related to performance on both tasks. The focus of the current paper is on the evaluation of a revised version of the DOT task (DOT 2.5) designed to encourage the use of spatial solutions by removing the numerical values from the task. We compared the performance of DOT 2.5 with previously validated measures of spatial ability, namely the paper folding and block rotation tasks. We also asked participants how often they employed different strategies on the task (e.g., a spatial strategy or mathematical one). Our results show the DOT 2.5 is significantly related to spatial ability as measured with block rotation. However, while participants were three times more likely to use a spatial strategy on the task, only the use of a math strategy was related to improved performance.
Dear Diary: Conducting Diary Studies with Participants with Visual Impairments
Authors: Huff Earl W. , Boateng Kwajo , Brinkley Julian
Published: February 2021

Within this report we critically reflect on our experiences using a diary study used to understand the use of social networking sites (SNS) by persons with a visual impairment. We elaborate on the development of the data collection process and the challenges involved in retrieving the data from the participants. Feedback from the participants during post-study interviews revealed that most participants were indifferent to the methods for submitting the diary entries and did not find it a challenge. Most of the participants found the process to be a positive experience for self-awareness of their social media use while reporting little to no adverse effects of carrying out the study. Lastly, we provide reflections and lessons learned from the process.
Smartphone usage pattern while walking: A survey on 441 young users in Korea
Authors: Kwon Yujin , Choi Seobin , Kim Eunjee , Kim Hyorim , Kim Misol , Shin Gwanseob
Published: February 2021

Smartphone usage rate has been increased, and so has on the streets while walking. Concerns for traffic accidents associated with the use have been growing, but there has been limited information regarding smartphone usage pattern while walking. A survey was conducted to explore the usage pattern in terms of frequency of use while walking, and history of accidents, and apps used while walking. Of 441 students, 95.9% used smartphones ‘sometimes’ or more often while walking. 91.8% and 54.6% of 423 used their phones while waiting for a signal and while crossing the crosswalk, respectively. 57.9% experienced accidents or near misses when using smartphones while walking. Text messaging (87.7%) was the most frequently used app while walking, followed by music and phone calls. The findings indicate that using smartphones while walking is a common behavior of young users, and suggest habitual users on the streets were in greater risks for accidents.
Efficiency-Thoroughness Trade-Off Characteristics of Air Traffic Controllers During Tower Operations
Authors: Takagi Tsubasa , Nakanishi Miwa
Published: February 2021

Air traffic demand has been growing for years and many countries are trying to solve this situation by modernizing their national airspace through advanced automation. Those projects aim to provide a greater level of efficiency while ensuring a safe flow of air traffic. However, human air traffic controllers have been coping with difficult situations and unexpected events by flexibly balancing efficiency and thoroughness throughout their operations. In this study, we conducted an experiment using a simulator depicting air traffic control tower operations and analyzed the trade-off decisions made by humans under varying situations. By doing so, we proposed a model with the aim of applying the results to future air traffic management systems. This could allow those autonomous systems to make decisions that are similar to those of human preferences, which could lead to a proactive management of safety and a higher level of automation acceptance.
Effect of texture on perception of axis of rotation of pivot doors
Authors: Raveendranath Balagopal , Pagano Christopher C.
Published: February 2021

Doors afford the action of entry and exit from an enclosed space. Although doors usually swing about an axis of rotation which falls along one of its side edges, certain types of doors, like pivot doors, rotate about an intermediate point, with the surface of the door extending on both sides of the axis of rotation. The current study investigates the optical information available to detect the axis of rotation in pivot doors. Participants clicked on the axis of a rotating panel simulated on a computer, as quickly and accurately as possible. Texture on the panel and background were varied, along with the position of axis of rotation. Response time was faster, and accuracy was better when there was texture in either the background or panel or both, compared to no texture at all. The results suggest the importance of texture information in the design of doors and built environments.
Influences of Stress on Interactions with Decision Support
Authors: Litaker Kylie , Mayhorn Christopher B.
Published: February 2021

People regularly interact with automation to make decisions. Research shows that reliance on recommendations can depend on user trust in the decision support system (DSS), the source of information (i.e. human or automation), and situational stress. This study explored how information source and stress affect trust and reliance on a DSS used in a baggage scanning task. A preliminary sample of sixty-one participants were given descriptions for a DSS and reported trust before and after interaction. The DSS gave explicit recommendations when activated and participants could choose to rely or reject the choice. Results revealed a bias towards self-reliance and a negative influence of stress on trust, particularly for participants receiving help from automation. Controlling for perceived reliability may have eliminated trust biases prior to interaction, while stress may have influenced trust during the task. Future research should address potential differences in task motivation and include physiological measures of stress.
Understanding Driver Behavior after Concussion: A Machine-Learning Approach
Authors: Daniali Maryam , Salvucci Dario D. , Schultheis Maria T.
Published: February 2021

Concussions are common cognitive impairments, but their effects on task performance in general, and on driving in particular, are not well understood. To better understand the effects of concussion on driving, we investigated previously gathered data on twenty-two people with a concussion, driving in a virtual-reality driving simulator (VRDS), and twenty-two non-concussed matched drivers. Participants were asked to per-form a behavioral task (either coin sorting or a verbal memory task) while driving. In this study, we chose a few common metrics from the VRDS and tracked their changes through time for each participant. Our pro-posed method—namely, the use of convolutional neural networks for classification and analysis—can accu-rately classify concussed driving and extract local features on driving sequences that translate to behavioral driving signatures. Overall, our method improves identification and understanding of clinically relevant driv-ing behaviors for concussed individuals and should generalize well to other types of impairments.
Participatory Design in the Classroom: Exploring the Design of an Autonomous Vehicle Human-Machine Interface with a Visually Impaired Co-Designer
Authors: Huff Earl W. , Lucaites Kathryn M. , Roberts Aminah , Brinkley Julian
Published: February 2021

Self-driving vehicles are the latest innovation in improving personal mobility and road safety by removing arguably error-prone humans from driving-related tasks. Such advances can prove especially beneficial for people who are blind or have low vision who cannot legally operate conventional motor vehicles. Missing from the related literature, we argue, are studies that describe strategies for vehicle design for these persons. We present a case study of the participatory design of a prototype for a self-driving vehicle human-machine interface (HMI) for a graduate-level course on inclusive design and accessible technology. We reflect on the process of working alongside a co-designer, a person with a visual disability, to identify user needs, define design ideas, and produce a low-fidelity prototype for the HMI. This paper may benefit researchers interested in using a similar approach for designing accessible autonomous vehicle technology.
Police Officer Interactions with In-vehicle Technologies: An On-Road Investigation
Authors: Shahini Farzaneh , Zahabi Maryam , Patranella Ben , Mohammed Abdul Razak Ashiq
Published: February 2021

Police motor vehicle crashes are a leading cause of officers’ fatalities in line of duty. These crashes have been attributed not only to driving at high speed in emergency situations but more importantly to interaction with different in-vehicle technologies. Prior studies in this domain have been limited to specific equipment and short exposure time and were typically conducted in laboratory settings with simulated environment or tasks which limit their generalizability to actual police operations. The objective of this study was to identify the most frequently used and cognitively demanding in-vehicle technologies for police officers while driving. Ten officers participated in a three-hour ride-along study. Findings suggested that the mobile computer terminal is the most frequently used and visually and cognitively demanding in-vehicle technology for police officers. Other factors such as work shift, duration, and average time spent in the vehicle per shift can also affect workload. The results indicated the need for improvements in in-vehicle technology design and implementation, officer training protocols, and departmental policies in order to reduce officers’ mental workload and improve safety in police operations.