John D Lee

University of Wisconsin–Madison | UW · Department of Industrial and Systems Engineering

As societies transition to hybrid mobility systems, interactions between automated vehicles (AVs) and human users in public spaces become more complex, highlighting the critical role of prosocial behaviors. These behaviors are essential for the seamless operation of interdependent transportation networks, helping to address integration challenges o...

Driving automation introduces multiple driving modes to maximize the system’s benefits, but drivers must monitor and stay aware of these modes, which can sometimes lead to mode confusion. We modified Degani and Heymann’s state diagram method to assess the mode structure of a hypothetical driving automation system and the likelihood of discrepancies...

Many lines of human factors inquiry rely on dialogue data to examine team dynamics, coordination, and trust in automation. While embeddings enable the transformation of such qualitative information into mathematical representations, they can be challenging to explore—a vector of hundreds or thousands of numbers lacks simple interpretation. To addre...

Automation’s imperfection requires driver engagement to handle challenging tasks, creating interdependent relationships where both parties influence each other. Therefore, it is vital to support driver-automation interdependence to align their behaviors with team goals. We expand the Interdependence Analysis (IA) method to evaluate interdependent r...

The objective of this panel is to better understand how machine learning (ML) systems influence users and to identify strategies to make such interactions more effective when designing decision support systems and joint cognitive systems for real-time control. The panelists will draw upon their insights from the fields of aviation, defense, ground...

Both drivers and the current state of advanced driver-assistance systems (ADASs) are imperfect, but their collaboration as a team can compensate for individual limitations. Unstructured driving environments (e.g., parking lots and off-road trails) entail greater challenges for an ADAS and require driver-automation collaboration. However, few studie...

BACKGROUND Dispensing errors significantly contribute to adverse drug events, resulting in substantial healthcare costs and patient harm. Automated pill verification technologies have been developed to aid pharmacists with medication dispensing. However, pharmacists’ trust in such automated technologies remains unexplored. OBJECTIVE This study aim...

The driving style of an automated vehicle (AV) needs to be comfortable to encourage the broad acceptance and use of this newly emerging transport mode. However, current research provides limited knowledge about what influences comfort, how this concept is described, and how it is measured. This knowledge is especially lacking when comfort is linked...

BACKGROUND Dispensing errors significantly contribute to adverse drug events, resulting in substantial healthcare costs and patient harm. Automated pill verification technologies have been developed to aid pharmacists with medication dispensing. However, pharmacists’ trust in such automated technologies remains unexplored. OBJECTIVE This study aim...

Introduction Trust has emerged as a prevalent construct to describe relationships between people and between people and technology in myriad domains. Across disciplines, researchers have relied on many different questionnaires to measure trust. The degree to which these questionnaires differ has not been systematically explored. In this paper, we u...

Demands to manage the risks of artificial intelligence (AI) are growing. These demands and the government standards arising from them both call for trustworthy AI. In response, we adopt a convergent approach to review, evaluate, and synthesize research on the trust and trustworthiness of AI in the environmental sciences and propose a research agend...

When people experience the same automation, their trust in automation can diverge. Prior research has used individual differences—trust propensity and complacency—to explain this divergence. We argue that bifurcation as an outcome of a dynamic system better explains trust divergence. Linear mixed-effect models were used to identify features to pred...

Driver assistance technologies have rapidly advanced. However, using partially automated driving systems in urban environments is still challenging. The potential disuse of driving automation is one of the challenges that prevents users from taking full advantage of the system. To address this issue, we investigated whether sharing the vehicle’s si...

Despite multiple taxonomies and descriptions of automation there is inconsistency in describing automation capabilities, making it difficult to interpret and replicate research. We conducted a systematic literature review to investigate how studies document automation. The Scopus ® database was searched on January 13th, 2023, for vehicle automation...

Cooperative automated vehicles (AVs) bring the potential for better safety, efficiency, and energy-savings on the individual and system level. Yet, these benefits can only be achieved if people cooperate. In this study, we explored the effects of cooperative and reciprocal AVs on people's well-being, trust, and cooperation. We conducted a mixed-des...

We propose the concept of directive driving automation that positively influences drivers’ intentions to achieve shared goals. As a step toward directive driving automation, this survey study explored how social norms can persuade drivers to continue using driving automation. We tested social norm messages using a 2x2x2x2 factorial within-subject d...

Extended exposure to reliable automation may lead to overreliance as evidenced by poor responses to auto-mation errors. Individual differences in trust may also influence responses. We investigated how these factors affect response to automation errors in a driving simulator study comprised of stop-controlled and uncon-trolled intersections. Driver...

Technology development often has profound consequences for human agency. Considering the evolution of seemingly mundane tools, such as pens, can help us anticipate the consequences of emerging technology. We consider how the evolution of pens might guide automation and artificial intelligence (AI) design. Automation and AI change activities by trad...

Qualitative analysis methods, while crucial for understanding complex factors influencing human behaviors like engagement with digital health technologies, can be conceptually challenging, time-consuming, and resource intensive. To address these challenges, semi-automated text analysis techniques like structural topic modeling (STM) may enhance the...

There is significant interest and research in engineering machines, algorithms, and systems that humans will trust. However, serious questions remain about trust: what it is, whether it can be measured and modeled, whether it provides useful information for engineering and design, and whether the engineering of trust will be deployed ethically. Thi...

Despite multiple taxonomies and descriptions of automation there is inconsistency in describing automation capabilities, making it difficult to interpret and replicate research. We conducted a systematic literature review to investigate how studies document automation. The Scopus® database was searched on January 13th, 2023, for vehicle automation...

Designers frequently look toward automation as a way to increase system efficiency and safety by reducing involvement. This approach can disappoint because the contribution of people often becomes more, not less, important as automation becomes more powerful and prevalent. More powerful automation demands greater attention to its design, supervisor...

This contribution outlines a high-fidelity simulation framework for Human-in-the-loop (HIL) traffic simulation built upon Project Chrono, an open-source physics simulation engine. The framework is designed to provide the software infrastructure for human factors, traffic, and human-automation interplay research. We conclude this platform overview p...

Objective: The objective of this study was to estimate trust from conversations using both lexical and acoustic data. Background: As NASA moves to long-duration space exploration operations, the increasing need for cooperation between humans and virtual agents requires real-time trust estimation by virtual agents. Measuring trust through convers...

Human-AI conversation provides a natural, unobtrusive, yet under-explored way to investigate trust dynamics in human-AI teams (HATs). In this paper, we modeled dynamic trust evolution in conversations using a novel method, trajectory epistemic network analysis (T-ENA). T-ENA captures the multidimensional aspect of trust (i.e., analytic and affectiv...

Self-driving vehicles promise many safety, mobility, and environmental benefits. However, users’ lack of trust and acceptance may threaten the success and potential of this technology. Monitoring the driver’s emotional state is one way to address this challenge. Empathetic automation can respond to the driver’s state and improve the experience and...

Drivers have spare visual capacity in driving, and often this capacity is used for engaging in secondary in-car tasks. Previous research has suggested that the spare visual capacity could be estimated with the occlusion method. However, the relationship between drivers’ occlusion times and in-car glance duration preferences has not been sufficientl...

Tesla's Full Self-Driving Beta (FSD) program introduces technology that extends the operational design domain of standard Autopilot from highways to urban roads. This research conducted 103 in-depth semi-structured interviews with users of Tesla's FSD Beta and standard Autopilot to evaluate the impact on user behavior and perception. It was found t...

During the use of partial driving automation, transfers of control (TOC) between the driver and automation happen routinely while the driver supervises and manages the driving environment. Although driver-initiated TOCs are more prevalent, they have not been explored to the same extent as system-initiated TOCs due to their low criticality. Drivers...

Automated driving needs to be comfortable to encourage the broad acceptance and usage of automated vehicles (AVs). However, current research provides limited knowledge on the descriptions and influencing factors of user comfort in automated driving, especially from the perspective of an AV’s driving styles. This paper presents results from an onlin...

Objective: This study explores subjective and objective driving style similarity to identify how similarity can be used to develop driver-compatible vehicle automation. Background: Similarity in the ways that interaction partners perform tasks can be measured subjectively, through questionnaires, or objectively by characterizing each agent's act...

In this study, we focus on the impact of daily virtual nature experiences combined with mindfulness practices on remote workers' creativity, stress, and focus over an extended period (9 weeks) during the COVID-19 pandemic. Our results show a positive effect of virtual reality (VR) nature experience on increasing focus and reducing stress. When VR n...

Advances in automated driving systems (ADSs) have shifted the primary responsibility of controlling a vehicle from human drivers to automation. Framing driving a highly automated vehicle as teamwork can reveal practical requirements and design considerations to support the dynamic driver-ADS relationship. However , human-automation teaming is a rel...

Human-automation driving style similarity may be a source of trust that influences drivers' automation use decisions. This is generally examined in scenarios where the driver is attentive to the automation. However, future automation may not require driver attention. Thus, driving style similarity must be revisited as various levels of attention ma...

As human-AI teaming becomes increasingly prevalent, goal alignment has emerged as a critical yet unsolved issue. Misaligned goals can be amplified by the situation and strategic interactions, which can further impact the teaming process and performance. These interrelated factors lack a systematic and computational model. To address this gap, we de...

Riding a bicycle, walking, and running are generally health-promoting and environmentally friendly activities, but tens of thousands of cyclists and hundreds of thousands of pedestrians worldwide die in accidents each year. There is an urgent need to address this complex problem with a multidisciplinary and multi-faceted approach. This panel will p...

Human-automation driving style similarity may be a source of trust that influences drivers’ automation use decisions. This is generally examined in scenarios where the driver is attentive to the automation. However, future automation may not require driver attention. Thus, driving style similarity must be revisited as various levels of attention ma...

Machine learning promises many advantages, but achieving these promises requires methods that smooth the interaction between humans and machine learning. Machine learning systems require meticulous training on large, labeled datasets. Labeling data is a tedious expensive process, and many times requires complex human-judgment skills. Mixed-initiati...

As NASA moves to long-duration space exploration operations, there is an increasing need for human-agent cooperation that requires real-time trust estimation by virtual agents. Our objective was to estimate trust using conversational data, including lexical and acoustic features, with machine learning. A 2 (reliability) × 2 (cycles) × 3 (events) wi...

As human-AI teaming becomes increasingly prevalent, goal alignment has emerged as a critical yet unsolved issue. Misaligned goals can be amplified by the situation and strategic interactions, which can further impact the teaming process and performance. These interrelated factors lack a systematic and computational model. To address this gap, we de...

As NASA moves to long-duration space exploration operations, there is an increasing need for human-agent cooperation that requires real-time trust estimation by virtual agents. Our objective was to estimate trust using conversational data, including lexical and acoustic features, with machine learning. A 2 (reliability) × 2 (cycles) × 3 (events) wi...

Tesla’s Full Self-Driving Beta (FSD) program introduces technology that extends the operational design domain of standard Autopilot from highways to urban roads. This research conducted 103 semi-structured interviews with users of Tesla’s FSD Beta and standard Autopilot to evaluate the impact on user behavior and perception. It was found that drive...

Background Patient mobility is an evidenced-based physical activity intervention initiated during intensive care unit (ICU) admission and continued throughout hospitalization to maintain functional status, yet mobility is a complex intervention and not consistently implemented. Cognitive work analysis (CWA) is a useful human factors framework for u...

Trust has emerged as a prevalent construct to describe relationships between people and between people and technology in myriad domains. Across disciplines, researchers have relied on many different questionnaires to measure trust. The degree to which these questionnaires differ has not been systematically explored. In this paper, we use a word-emb...

This study expands existing taxonomies for transfer of control (TOC) with driving automation. A TOC taxonomy is necessary to categorize types of TOC, interpret drivers' behavior during a transition, and assess the safety implications of each TOC type. However, existing taxonomies do not capture important aspects of the driver's reaction to the tran...

Developing vehicle automation that accommodates other road users and exhibits familiar behaviors may enhance traffic safety, efficiency, and fairness, leading to tolerance of the technology. However, the interdependence between vehicle automation and other road users makes them more challenging than typical control and path planning tasks. Through...

Remote meetings have become more prevalent due to the COVID-19 pandemic and technology that facilitates remote work. There is limited research on the effect of remote meetings on group performance and the goal of this study is to identify how distractions affect the individual and group creativity in remote work meetings. A virtual study was conduc...

Background ‘One Health’ recognizes the interconnectivity of humans with their production and companion animals, and the environment. Emergence and transmission of antimicrobial resistance (AMR) within and between these compartments is a recognized global threat that requires further understanding to design interventions protecting both human and an...

Remote work presents a challenge to workers' creativity, especially during the COVID-19 pandemic and the stay-at-home requirements. Individual differences in creativity, considered through the lens of distributional models, and their stability across different conditions are unknown. We assess the between-person variability in common metrics of cre...

One way to compensate for the limitations of automated vehicles is to use a remote operator as a fallback controller. Indeed, this has been proposed for fleet management and intermittent vehicle control. However, existing remote operation applications have demonstrated control challenges, such as latency and bandwidth, that inhibit the effectiveness...

This panel discussion is third in a series examining the educational challenges facing future human factors and ergonomics professionals. The past two panels have focused on training of technical skills in data science, machine learning, and artificial intelligence to human factors students. This panel discussion expands on these topics and argues f...

Familiarity with a route is influenced by levels of dynamic and static knowledge about the route and the route network such as type of roads, infrastructure, traffic conditions, purpose of travel, weather, departure time, etc. To better understand and develop route choice models that can incorporate more meaningful representations of route familiar...

Objective: To explore the ramifications of attribution errors (AEs), initially in the context of vehicle collisions and then to extend this understanding into the broader and diverse realms of all forms of human-machine interaction. Background: This work focuses upon a particular topic that John Senders was examining at the time of his death. He...

Objective This paper reviews recent articles related to human trust in automation to guide research and design for increasingly capable automation in complex work environments. Background Two recent trends—the development of increasingly capable automation and the flattening of organizational hierarchies—suggest a reframing of trust in automation...

Automated driving research over the past decades has mostly focused on highway environments. Recent technological developments have drawn researchers and manufacturers to look ahead at introducing automated driving in cities. The current position paper examines this challenge from the viewpoint of scientific experts. Sixteen Human Factors researche...

Automated driving research over the past decades has mostly focused on highway environments. Recent technological developments have drawn researchers and manufacturers to look ahead at introducing automated driving in cities. The current position paper examines this challenge from the viewpoint of scientific experts. Sixteen Human Factors researche...

Communication among road users smooths interactions, improves efficiency, and mitigates risk. Eye contact and waving may be the most salient of this communication, but more often road users use their movement or position as implicit signals. Vehicle automation may disrupt these signals by introducing unfamiliar or unclear interactions that may not...

The goal of the Mid-career Professional Group of the Human Factors and Ergonomics Society is to support the development and mentoring of mid-career professionals. One opportunity for which early mid-career professionals lack knowledge is the sabbatical. Following a designated number of years of consecutive service, a sabbatical can provide a time f...

One advantage of highly automated vehicles is drivers can use commute time for non-driving tasks, such as work-related tasks. The potential for an auto-mobile office—a space where drivers work in automated vehicles—is a complex yet underexplored idea. This paper begins to define a design space of the auto- mobile office in SAE Level 3 automated veh...

The continued advances in artificial intelligence and automation through machine learning applications, under the heading of data science, gives reason for pause within the educator community as we consider how to position future human factors engineers to contribute meaningfully in these projects. Do the lessons we learned and now teach regarding...

The increasingly collaborative decision-making process between humans and agents demands a comprehensive, continuous, and unobtrusive measure of trust in agents. The gold standard format for measuring trust, a Likert-style survey, suffers from major limitations in dynamic human-agent interactions. We proposed a new approach to evaluate trust in a n...

One advantage of highly automated vehicles is drivers can use commute time for non-driving tasks, such as work-related tasks. The potential for an automobile office-a space where drivers work in automated vehicles-is a complex yet underexplored idea. This paper begins to define a design space of the automobile office in SAE Level 3 automated vehicl...

The concept of using automated vehicles as mobile workspaces is now emerging. Consequently, the in-vehicle environment of automated vehicles must be redesigned to support user interactions in performing work-related tasks. During the design phase, interaction designers often use personas to understand target user groups. Personas are representation...

How can technology support workers in our rapidly changing world? How can we help them be productive and creating, and how can we support their overall wellbeing? Our team explores these broad questions for two specific areas: working in future automated vehicles, and working from home. We argue that making progress in these areas will require conv...

What is the future of work and wellbeing? How did the COVID-19 crisis affect this future? What can, and what should, researchers and practitioners in the field of human-computer interaction do, as they develop interfaces for work and wellbeing? These are the questions that we explore in a weekly online series of conversations with HCI experts. In t...

Temporal frame sub-sampling (TFS) for reducing video object tracking (VOT) computing time is investigated. With a sampling ratio N, the TFS VOT algorithm will process a shorter video by sampling 1 out of N frames of the given video. The object trajectory of the remaining frames will be interpolated linearly based on those of sampled frames. Thus, T...

Data classification is central to human factors research, and manual data classification is tedious and error prone. Supervised learning enables analysts to train an algorithm by manually classifying a few cases and then have that algorithm classify many cases. However, algorithms often fail to leverage human insight. To address this, we augment su...

The Tactile Detection Response Task (TDRT) has been used to assess the cognitive workload of driver distraction with response time and miss rate as metrics of cognitive workload. However, it is not clear which metric is more sensitive and whether sensitivity is maintained for visual tasks. The objective of this study was to assess the sensitivity o...

Objective The aim of this special issue is to bring together the latest research related to driver interaction with various types of vehicle automation. Background Vehicle technology has undergone significant progress over the past decade, bringing new support features that can assist the driver and take on more and more of the driving responsibil...

When automobiles were first introduced in the early 1900s, poor communication and unsafe interactions between drivers and other road users generated resistance. This created a need for new infrastructure, vehicle design, and social norms to mitigate their negative effects on society. Vehicle automation may lead to similar challenges as drivers are...

Objective Understanding the factors that affect drivers’ response time in takeover from automation can help guide the design of vehicle systems to aid drivers. Higher quantiles of the response time distribution might indicate a higher risk of an unsuccessful takeover. Therefore, assessments of these systems should consider upper quantiles rather th...

The explosion of data science (DS) in all areas of technology coupled with the rapid growth of machine learning (ML) techniques in the last decade create novel applications in automation. Many working with DS techniques rely on the concept of “black boxes” to explain how ML works, noting that algorithms find patterns in the data that humans might n...

This session looks to serve the purpose of recalling and recounting the life and contributions of Professor John Senders. The contributors to this session include his direct colleagues, his students, his co-authors, those whom he inspired, and even members of his family. These designations are not exclusive! Senders made so many contributions acros...