• Home
  • Catherine Neubauer
Catherine Neubauer

Catherine Neubauer
Army Research Laboratory and University of Southern California · Human Research and Engineering Department

PhD

About

32
Publications
34,601
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
722
Citations
Citations since 2016
20 Research Items
613 Citations
2016201720182019202020212022020406080100120
2016201720182019202020212022020406080100120
2016201720182019202020212022020406080100120
2016201720182019202020212022020406080100120
Introduction
Catherine Neubauer is a Research Psychologist at the US Army Research Laboratory. Her research focuses on the use of cognitive models and computer algorithms to assess human performance and decision-making within basic and applied settings. More specifically her recent work has focused on team cohesion, trust in automation and automatic analysis of human emotion and facial expressions. She has published in several major journals and is co-editor of the 2012 Handbook of Operator Fatigue.

Publications

Publications (32)
Article
The rise in artificial intelligence capabilities in autonomy-enabled systems and robotics has pushed research to address the unique nature of human-autonomy team collaboration. The goal of these advanced technologies is to enable rapid decision making, enhance situation awareness, promote shared understanding, and improve team dynamics. Simultaneou...
Article
Full-text available
Cohesion is an important property of teams that can affect individual teammates and team outcomes. However, cohesion in teams that include autonomous systems as teammates is an underexplored topic. We examine the extant literature on cohesion in human teams, then build on that foundation to advance the understanding of cohesion in human–autonomy te...
Conference Paper
Phase I of the Soldier Operational Experiment was held at Fort Carson, Colorado in 2020, to assess the current capability of a manned vehicle and unmanned weaponized vehicle collaborative team capabilities during live fire gunnery operations and situational training exercises. Here we discuss the performance of the crews during these exercises, and...
Chapter
The U.S. Army is currently working to integrate artificial intelligence, or AI-enabled systems, into military working teams in the form of both embodied (i.e., robotic) and embedded (i.e., computer or software) intelligent agents with the express purpose of improving performance during all phases of the mission. However, this is largely uncharted t...
Article
Full-text available
Cohesion is an important construct in understanding human-autonomy team dynamics and effectiveness, yet methods to adequately measure this construct are still being developed. Here we describe the initial steps of the development of a new human-autonomy team cohesion scale: item development, content validation, and preliminary scale item evaluation...
Chapter
Team resilience affects both the cohesion and subsequent performance of that team. For human teams, resilience is tied to team learning, team flexibility, social capital, and collective efficacy. But for human-autonomy teams, resilience also includes cyber resilience and robust and adaptable robotic control. This work builds out the theory associat...
Article
Full-text available
Evaluation of team communication can provide critical insights into team dynamics, cohesion, trust, and performance on joint tasks. Although many communication-based measures have been tested and validated for human teams, this review article extends this research by identifying key approaches specific to human-autonomy teams. It is not possible to...
Chapter
Trust is a critical factor in the development and maintenance of effective human-autonomy teams. As such, new processes are needed to classify affective state change that could be related to either an accurate or a misaligned change in trust that occurs during collaboration. The task for the current study was a leader-follower, simulated driving ta...
Conference Paper
Full-text available
Multimodal interaction technologies have enabled new applications for training interpersonal skills such as public speaking. Various training paradigms have been proposed, most of them relying on some form of graphical feedback provided to the trainee in real-time during their training or after training using an after-action review tool. Another pa...
Conference Paper
Full-text available
Research has shown beneficial performance gains from concurrent multimodal presentation of visual and tactile signaling. Studies have also suggested the importance of closely matching or emulating the spatial characteristics of tactile signaling to its visual counterpart, resulting in intuitive tactile signals that are easily learned and that provi...
Conference Paper
Full-text available
High fidelity military simulators have been a vital part of training and developing warfighters over the last eighty plus years. As military simulator technologies have evolved, continued emphasis tends toward high fidelity as a means to create the most extreme environments that offer novices opportunities to employ a broad spectrum of cognitive an...
Conference Paper
Full-text available
The current study was motivated to understand the relationship between the external behavior and inner affective state of two team members ("instructor"-"defuser") during a demanding operational task (i.e., bomb defusion). In this study we assessed team member's verbal responses (i.e., length of duration) in relation to their external as well as in...
Chapter
Full-text available
This article reviews advancements in methods for detection of task-induced driver fatigue. Early detection of the onset of fatigue may be enhanced by spectral frequency analysis of the electrocardiogram (ECG) and analysis of eye fixation durations. Validity may also be improved by developing algorithms that accommodate driver sleep history assessed...
Chapter
Full-text available
This work proposes a process for formulating a model and estimation scheme to predict changes in decision authority with a simulated autonomous driving assistant. The unique component of this modeling approach is the use of direct estimation of governing mental decision states via recursive psychophysiological inference. Treating characteristic qua...
Article
The impacts of fatigue on the vehicle driver may change with technological advancements including automation and the increasing prevalence of potentially distracting in-car systems. This article reviews the authors' simulation studies of how fatigue, automation, and distraction may intersect as threats to safety. Distinguishing between states of ac...
Conference Paper
Full-text available
The effects of oxytocin on facial emotional expres-sivity were investigated in individuals with schizophrenia and age-matched healthy controls during the completion of a Social Judgment Task (SJT) with a double-blind, placebo-controlled, cross-over design. Although pharmacological interventions exist to help alleviate some symptoms of schizophrenia...
Conference Paper
Full-text available
It is commonly known that a relationship exists between the human voice and various emotional states. Past studies have demonstrated changes in a number of vocal features, such as fundamental frequency f0 and peakSlope, as a result of varying emotional state. These voice characteristics have been shown to relate to emotional load, vocal tension, an...
Article
Full-text available
Introduction: Voice communication may enhance performance during monotonous, potentially fatiguing driving conditions (Atchley & Chan, 2011); however, it is unclear whether safety benefits of conversation are outweighed by costs. The present study tested whether personalized conversations intended to simulate hands-free cell phone conversation may...
Conference Paper
Full-text available
Team cohesion has been suggested to be a critical factor in emotional resilience following periods of stress. Team cohesion may depend on several factors including emotional state, communication among team members and even psychophysiological response. The present study sought to employ several multimodal techniques designed to investigate team beh...
Article
Full-text available
As vehicle operation becomes increasingly automated, driver fatigue appears to be an increasingly pressing safety issue. Trivia games have been suggested as a fatigue countermeasure, but, like cell phone use, games may be distracting. The present study investigated whether secondary media devices impacted subjective responses and driver performance...
Article
Full-text available
Despite the known dangers of driver fatigue, it is a difficult construct to study empirically. Different forms of task-induced fatigue may differ in their effects on driver performance and safety. Desmond and Hancock (2001) defined active and passive fatigue states that reflect different styles of workload regulation. In 2 driving simulator studies...
Chapter
Full-text available
Task performance is frequently stressful, especially when the task imposes high cognitive demands. Research has shown that the subjective stress response to performance is multidimensional. Different types of task demand elicit different patterns of response. This chapter reviews the use of the Dundee Stress State Questionnaire (DSSQ: Matthews et a...
Article
Full-text available
Cell phone use has been identified as a threat to driver safety. Impairments may depend on the type of cell phone usage such as calling back and text messaging. The present study investigated whether the impact of phone use depends on the state of fatigue of the driver. A manipulation of full vehicle automation was used to induce a state of passive...
Article
Full-text available
A driving simulator was used to assess the impact on fatigue, stress, and workload of full vehicle automation that was initiated by the driver. Previous studies have shown that mandatory use of full automation induces a state of "passive fatigue" associated with loss of alertness. By contrast, voluntary use of automation may enhance the driver's pe...
Book
Fatigue is a recognized problem in many facets of the human enterprise. It is not confined to any one area of activity but enters all situations in which humans have to perform for extended intervals of time. Most problematic are the circumstances in which obligatory action is continuous and the results of failure are evidently serious or even cata...
Article
Full-text available
Automated driving systems have the potential to lower driver workload, but may also induce fatigue and loss of situation awareness. This study investigated individual differences in fatigue response to automation that is under the driver's control. Of particular interest was the driver's choice of whether or not to use an automation option. The stu...
Article
Full-text available
Research has shown beneficial performance gains from recent advances in automated driving systems. Although these systems show promise for mitigating potentially dangerous effects of driving, namely subjective feelings of stress and fatigue, there are some safety concerns, which may be investigated using simulator methods. This paper examines and i...
Conference Paper
Full-text available
United States Army military and civilian supervisors who manage civilian employees must complete the Supervisor Development Course (SDC) upon appointment, and every three years after their appointment. The original SDC online course focused on standardizing course content for supervisors across the Army, and the SDC provided quality information for...

Network

Cited By

Projects

Projects (6)
Project
Meaningful human control (MHC) is a focal construct intended to facilitate the responsible deployment of autonomous systems. Initially emerging from international discourse about autonomous weapons, the modern application space for MHC has expanded to include more generalized applications such as surgical robotics, self-driving vehicles, decision support systems, and likely others. Within this, the main challenge arises when systems of increasing abilities to learn and self-select courses of action are faced with compromises involving differential consequences that are associated with competing human values (e.g. freedom versus security). Yet, the role of the human has largely been limited to considering how much authority to delegate, to which agent, and over what types of system functions. In this Research Topic, we take the perspective that such limited considerations have inherently directed discourse away from the true benefit that humans offer: that is, their deep connection with humanity and all that comes with it. Humanity in the broad sense is much more than cognitive capability. Yet, cognition is the single human resource most commonly incorporated into human-machine teams. More completely, humanity is the connection with collective human society, across geography and history. Humanity references being humane and invokes compassion, integrity, empathy, self-awareness, and benevolence. Such social and emotional aspects of intelligence contribute to decision-making, especially for complex dilemmas with ethical or moral considerations. While MHC is ultimately about preserving human dignity, the aspects of humanity considered here are not often included in serious discourse within the domain. We contend that this is because of a perceived difficulty, and perhaps an assumed lower relevance, of incorporating socio-emotional state information into human-machine teams. To access humanity in this way implies observing, measuring, inferring, predicting, and influencing affective along with cognitive and physical states. This conflicts with the predominant approach to human-machine teaming, which involves designs that tacitly assume that applying uncertainty metrics will sufficiently account for any variability due to socio-emotional influences. Yet socio-emotional states are important. Unlike more present-focused and deliberative cognitive processes, these affective processes provide an immediate connection with the history of a person's lived experience and their culture, and thus can rapidly and directly modulate decision likelihoods in ways that fit their personal circumstances. In this Research Topic, we aim to elucidate the role of socio-emotional processes in value-based, moral, and ethical decision making. We seek to explore how to measure and draw inferences about such processes, and specifically how to use the information gleaned to improve human relationships with advanced, intelligent technologies. This topic explores the potentially transformative role of integrating socio-emotional state information for the responsible and ethical deployment of human-machine teams and thus establishing MHC. As such, we seek submissions regarding: • Implications of MHC within socio-technical ecosystems, including projected ethical, legal, and societal consequences • Metaphors and methods for integrating humanity into socio-technical ecosystems (e.g. adaptive and dynamic delegation, models of multi-scale social dynamics) • Theoretical and empirical methods for examining and modeling complex ecosystems that include human socio-emotional states • Moral psychology and the role of human emotion in complex, value-based, ethical decision-making • Rapport, camaraderie, and social dynamics in human-machine ecosystems • Multi-modal methods for observing, measuring, and predicting affective-cognitive dynamics in real-world settings • Lifecycle design and evaluation for hybrid human-intelligent agent systems (e.g. value elicitation, value-sensitive and human-centered design) • Developmental approaches for manifesting humane, moral, or ethical agents • Testing, evaluating, and verifying the quality of complex, value-based moral and ethical decisions in human machine teams • Real-time or near real-time affective computing with wearable and IoT-type sensing To contribute, please go to: https://www.frontiersin.org/research-topics/47467/understanding-the-role-of-humanity-in-responsible-deployment-of-intelligent-technologies-in-socio-te
Project
The 21st century has seen an increased reliance on autonomy to extend human capabilities, creating a growing need to understand and predict human-autonomy interactions. A gap exists in current technologies for explicitly modeling the psychological and physiological mechanisms that drive this interaction, making optimal integration of human-autonomy teams difficult. In these situations, the degree of trust-in-autonomy (TiA) is paramount to maintaining successful cybernetic control and avoiding maladaptive behaviors that correspond with miscalibrated trust states. The objective of this project is to develop a tractable quantitative model of TiA, as it relates to the complex interaction between a human and an autonomous agent during a cooperative driving task, whereby the human’s dynamic impact in collaboration with the agent can be predicted through behavioral and physiological sensor measurements.