In this chapter, we explore the need to develop specific guidance, tailored to consumers of fatigue risk management systems, outlining how to verify that program elements effectively control the incidence of operator fatigue. We advance the notion that without independent proof of efficacy, consumers are left to assume that program implementation and sustainment costs actually yield the desired results. Lacking this information perpetuates losses associated with fatigue-related performance degradation, health issues, and mishaps. Inspection and verification protocols require objective evidence, beyond surveys, to demonstrate that fatigue management program elements control the incidence of operator fatigue in the workplace. Scientific and technological advances facilitate the evaluation of fatigue management programs and the use of objective techniques to test circadian rhythm stability and alertness. However, consumers are yet to incorporate these test protocols and technological advances in their safety management system assurance infrastructure. The prevailing assumption has been that scientific tests and methodologies are beyond the reach of the consumer and fall in the purview of scientists and fatigue management professionals. In this chapter, we propose the use of the design basis plan in safety management systems as the assurance infrastructure to associate program inspection elements, fatigue leading indicators, and specific standards with compulsory review and approval activities. These assurance activities not only provide objective means to identify fatigue management program elements that fail to control the incidence of operator fatigue but also enable consumers to proactively implement necessary modifications.
Transportation operator fatigue is a pervasive cross-modal risk, still largely unmitigated, costly, and underreported. Effectively predicting fatigue risk can help stem this trend and improve transportation safety, performance, and well-being. Not surprisingly, there is growing interest in applying fatigue models to support and evaluate safety-critical initiatives, such as scheduling, accident investigation, and hours-of-service rule making and compliance. Yet there is limited empirical data about whether current fatigue models are used as intended, how effectively they predict fatigue, and how they might be improved. Though current models typically focus on two or three biological processes that impact fatigue, the literature presents many internal and external variables that influence fatigue, and current models largely neglect this more comprehensive suite of contributing factors needed to assess individual employee risk across variable work environments. The U.S. Department of Transportation Safety Council has recognized the need to assess the strengths and weaknesses of existing biomathematical fatigue models and to explore how to maximize efficacy, reliability, and validity. In this chapter, we review a sample of current fatigue models, identify performance gaps, and describe an overarching framework to guide next-generation fatigue model development. The proposed eight-state model offers a novel systems-based approach to integrate contributing internal and external fatigue factors and better measure, predict, and manage fatigue risk across transportation and other safety-critical operations.
Fatigue is a physiological state of reduced performance capability resulting from sleep loss or extended wakefulness, circadian phase, or workload (mental and/or physical activity) that can impair a transport worker’s alertness and ability to work safely. Fatigue is affected by all waking activities, not only those that are work related. Consequently, fatigue management must be a shared responsibility of regulators, employers, and employees. Prescriptive hours-of-service limits, the traditional regulatory approach for managing fatigue, are increasingly being challenged with regard to their effectiveness in delivering safety and their cost to industry. Fatigue risk management systems (FRMSs) are a new regulatory approach that combines advances in the understanding of worker fatigue and accident causation with advances in safety management. FRMSs are data driven, are based on combined scientific and operational expertise, and include processes for monitoring their safety performance and for continuous improvement. Prescriptive hours-of-work limits are familiar and are arguably adequate in circumstances where fatigue-related safety risk is low. On the other hand, economic pressures are expected to continue to push transport companies to maximize use of vehicles/locomotives/vessels/aircraft with minimum safe manning levels. These pressures will drive the need for more tailored and flexible approaches to fatigue management, such as FRMSs.
Sleep debt and time of day/night (circadian rhythm) exert substantial effects on commercial motor vehicle (CMV) operator (e.g. truck and bus/motor coach, railroad engineer, aviation pilot) performance—and, therefore, safety. In this chapter, the influence of sleep debt and circadian effects on operator performance are described. Efficacy of various countermeasures is reviewed, and the influence of individual operator traits (genetic factors) is briefly discussed. It is concluded that sleep (napping) remains the best strategy for restoring and maintaining CMV operator neurobehavioral performance. Results from ongoing research will lead to occupation-specific and individualized strategies for managing sleepiness and fatigue in operational environments.
A golden age of research in the fields of sleep, circadian rhythms, and shift work has arrived. Each of these seemingly independent scientific disciplines has rendered tremendous progress over the past few decades that converge into a core body of research with direct applications for mitigating transportation fatigue and fatigue-related accidents. A common understanding now exists regarding key factors associated with transportation fatigue and related accidents across transportation domains. A variety of validated countermeasures and practical tools known to mitigate fatigue and accident risk have been developed. Despite this common knowledge of fatigue risk factors and known effective countermeasures among the research community, numerous challenges remain in bridging the gap between transportation fatigue research and effective real-world practice. Tracing the history of evaluation in response to the federal mandate for evaluation, including its roles, theories and methods, and evidence from the 2009 International Conference on Fatigue Management in Transportation, we propose the transdiscipline of evaluation as a mechanism for bridging this gap. Each chapter in this volume of Reviews of Human Factors and Ergonomics was reviewed using an evaluative framework that focused on five broad evaluative question areas: (a) authors’ main points, arguments, and conclusions with respect to context, program design, implementation, and impact; (b) authors’ key recommendations; (c) gaps and deficiencies, if any, in authors’ recommendations; (d) the most promising approaches for practical use; and (e) evaluation considerations for facilitating research use and practical applications. These evaluative question areas then were synthesized across chapters for common themes, gaps and deficiencies, and most promising approaches. The extent to which chapters respond to the federal evaluation mandate with respect to context, program design, implementation, and impact is discussed. In conclusion, drawing from the vast knowledge and experience in the evaluation field, a case is made for using five key evaluation principles to help bridge the gap between transportation fatigue research and effective practice, including core evaluation questions, stakeholder engagement, utilization-focused data and information gathering, valid and relevant findings, and targeted reporting.
The experience of fatigue is common to all human beings, since fatigue is a naturally occurring state of being. In occupational settings, fatigue can pose a threat to people, equipment, the environment, and corporate reputations. Although significant progress has been made in terms of understanding the causes of, and solutions for, worker fatigue, a great deal of complexity remains. This complexity is partly related to the fact that individuals are different in many ways (e.g., in terms of their genetically determined sleep need) and because of the general biological, psychological, and social components of personal fatigue. This chapter focuses on key fatigue-related principles, terminology, example frameworks, and key issues now and in the foreseeable future. The challenges for industry relate to both opportunities and potential threats, such as automation, fatigue-monitoring technologies, staffing levels, cultural differences within the workforce, and the remote locations of many operations. With evidence-based program development and evaluation, enhanced fatigue management can deliver improvements in safety, compliance, operational flexibility, worker satisfaction, and other relevant metrics.
The detrimental effects of fatigue on the safe operation of vehicles or the execution of critical tasks in transportation systems (e.g., monitoring pipeline systems or maintaining vehicles) have been well established. However, estimates of the percentage of transportation accidents attributed to fatigue has varied greatly, and much of that variability can be attributed to the methods used to investigate and document accident causes or risk factors. In addition, using research findings in accident investigation can be very difficult, and establishing that fatigue played a role in an accident illustrates very well the challenges of relating research to practice. In this chapter we will discuss how fatigue research has informed accident investigation and how findings from accidents and incidents can guide future research and policy decisions. The chapter will (a) establish the seriousness of the fatigue problem in transportation accidents and incidents; (b) provide insights into the difficulties associated in determining whether fatigue is a contributing or causal factor in an event; (c) describe, in detail, a methodology that can be used to identify fatigue factors in accident investigation; and (d) illustrate how accident investigations where fatigue is well documented can inform the research community and lead to design and policy changes that will mitigate fatigue and help improve transportation safety.
Sleep deficiency, which can be caused by acute sleep deprivation, chronic insufficient sleep, untreated sleep disorders, disruption of circadian timing, and other factors, is endemic in the U.S., including among professional and non-professional drivers and operators. Vigilance and attention are critical for safe transportation operations, but fatigue and sleepiness compromise vigilance and attention by slowing reaction times and impairing judgment and decision-making abilities. Research studies, polls, and accident investigations indicate that many Americans drive a motor vehicle or operate an aircraft, train or marine vessel while drowsy, putting themselves and others at risk for error and accident. In this chapter, we will outline some of the factors that contribute to sleepiness, present evidence from laboratory and field studies demonstrating how sleepiness impacts transportation safety, review how sleepiness is measured in laboratory and field settings, describe what is known about interventions for sleepiness in transportation settings, and summarize what we believe are important gaps in our knowledge of sleepiness and transportation safety.
Knowledge of the factors that make the operator become fatigued is a founding pillar of fatigue risk management. In this chapter, we introduce a model of the fatigue-inducing factors especially in the context of road transportation. In addition to the person, organization, and industry- and society-related factors that may exacerbate fatigue, we include in the model some pivotal factors that modify the effects and consequences of operator fatigue. Examples of these modifying factors are individual resilience to sleep restriction and organizational resilience to performance errors made by fatigued operators. The main outcome of the analysis of the fatigue-exacerbating factors is that many of them are amenable to change, such as operators’ health status and health-related lifestyle, shift and route scheduling, organizational resilience to operator fatigue, and organizational safety culture. In the key role is organizational safety culture, as it largely determines whether the company’s management and staff try to keep on-the-job-fatigue hidden or take mitigating actions.
In this chapter, we survey the current state of the art in space telerobots. We begin by defining relevant terms and describing applications. We then examine the design issues for space telerobotics, including common requirements, operational constraints, and design elements. A discussion follows of the reasons space telerobotics presents unique challenges beyond terrestrial systems. We then present case studies of several different space telerobots, examining key aspects of design and human–robot interaction. Next, we describe telerobots and concepts of operations for future space exploration missions. Finally, we discuss the various ways in which space telerobots can be evaluated in order to characterize and improve performance.
Robotic systems have been developed to handle very small objects, but their use remains complex and necessitates long-duration training. Simulators, such as molecular simulators, can provide access to large amounts of raw data, but only highly trained users can interpret the results of such systems. Haptic feedback in teleoperation, which provides force feedback to an operator, appears to be a promising solution for interaction with such systems, as it allows intuitiveness and flexibility. However, several issues arise while implementing teleoperation schemes at the micro- and nanoscale, owing to complex force fields that must be transmitted to users and scaling differences between the haptic device and the manipulated objects. Major advances in such technology have been made in recent years. In this chapter, we review the main systems in this area and highlight how some fundamental issues in teleoperation for micro- and nanoscale applications have been addressed. We consider three types of teleoperation, including (a) direct (manipulation of real objects), (b) virtual (use of simulators), and (c) augmented (combining real robotic systems and simulators). Remaining issues that must be addressed for further advances in teleoperation for micro- and nanoworlds are also discussed, including (a) comprehension of phenomena that dictate very small object (<500 micrometers) behavior and (b) design of intuitive 3-D manipulation systems. Design guidelines to realize an intuitive haptic feedback teleoperation system at the micro- and nanoscale level are proposed.
Safety and quality of health care depend on collaborative efforts of multiprofessional and multidisciplinary teams of care providers. Team research in aviation and the military has produced a wealth of knowledge in terms of concepts and intervention strategies to improve team performance. Research on collaborative work in health care in the past 20 years has uncovered unique characteristics and requirements of teams in hospitals and other health care settings and has provided early assessment of the utility of the theoretical concepts, methodologies, and interventions developed outside health care. In this chapter, we review a set of concepts that have been used in characterizing teams in health care and in improving teamwork. These concepts include the organizational shell to capture the sociotechnical environment in which teams reside as well as nontechnical skills, team leadership, team mental models, and so on. We will review a number of leading interventions to enhance team performance, such as teamwork training (e.g., TeamSTEPPS) and structured communication (e.g., SBAR). Future directions are suggested on better understanding of the interdependencies between teams and their organizational shell, such as standardization of operating procedures and training, and to focus on the patient in terms of teamwork improvement.
Human performance plays an important role in system performance and is influenced by a wide set of internal, organizational, and environmental factors. Human–robot systems are being developed for a large number of domains, including in-home care, military deployments, emergency response, industrial robots, and therapeutic applications. Human performance modeling provides the opportunity to investigate multiple system prototypes and theories regarding human performance that can be further evaluated in human-in-the-loop experiments, to quickly adapt to rapidly changing robotic technology, and to represent human behavior in extreme conditions. Interacting with robots also influences human performance, and models of the human–robot system provide an avenue to investigate the impact on human performance that the human–robot teaming elicits. This chapter provides an overview of examples representing common methods for assessing human performance in human–robot systems. The topics are summarized in Table 3.2 and include a description of human performance modeling, a summary of commonly used human performance modeling tools, examples of human performance modeling with a focus on its application in human–robot systems, information regarding the validation of models, and guidelines for implementing human performance modeling techniques for robotics.
Diagnostic reasoning and medical decision making have been focal areas of research in the fields of medical education, cognition, and artificial intelligence in medicine. Drawing on several decades worth of research, we propose an integrated summary of prior research on diagnostic reasoning and decision making—in terms of both historical development and theoretical shifts. We also characterize the changes in research and theory resulting from the incorporation and adoption of health information technology in the clinical work place. In this paper, we differentiate between the various forms of diagnostic reasoning and trace the evolution of the various models of reasoning, including knowledge-based, exemplar-based, and visual strategies. We also discuss the effect of clinical expertise on reasoning processes. Within the medical decision-making research, we delineate the various approaches highlighting decision-making errors that arise due to the nature of heuristics and biases and other factors. Although there has been significant progress in our understanding, there is still a need for greater theoretical integration of disparate empirical phenomena. Specifically, there is a need to reconcile the various characterizations of reasoning and to evaluate the similarity and differences in the context of current health care practice. Finally, we discuss the role of human factors research in the study of clinical environments and also in relation to devising approaches and methodologies for understanding, evaluating, and supporting the diagnostic reasoning and decision processes.
In this review, we explore how teleoperation could potentially be applied to the management of humanoid robots, with an emphasis on humanoid robots that are used in assistive roles, including clinical therapies. Since there are very few examples of the remote operation of a full humanoid, the review emphasizes technologies that are potentially relevant to teleoperation of humanoids. Teleoperation of humanoid robots faces many of the same practical challenges associated with (a) traditional teleoperation, including latency and telepresence, and (b) teleoperating manipulators and other robots with high degrees of freedom. Teleoperation systems for humanoid robots must also address unique challenges triggered by strong emotional and social responses to humanoids—responses of both the operator and any humans who may interact with the humanoid. These challenges trigger new opportunities for redefining teleoperation to include scripting, programming by demonstration, speech production, and Wizard of Oz interaction. The challenges also provide opportunities to specialize existing modes of interaction and unique opportunities to develop humanoid-specific forms of teleoperation, such as controlling humanoids via exoskeleton-based or inertial sensors. We include in this review a survey of enabling technologies, a taxonomy of practical uses, and a list of emerging themes and approaches to teleoperating humanoid robots.
In this chapter, we address issues related to using mobile telepresence robotics for social interaction between people in different locations. We examine this problem space from three perspectives: (a) designing for the robot user, who is in a remote location; (b) designing for people near the robot, who are interacting with the user; and (c) designing so that the conversation is not hampered by the technology. We identify and review a number of mobile telepresence robots that have been designed for such social interactions across a variety of applications, including business, education, and healthcare. Finally, we discuss areas for future research and development in mobile telepresence robots for social applications.
In this chapter, we discuss the application of human factors and ergonomics to developing effective simulation training in health care. Simulation provides a safe, effective method for training and assessing human performance. In aviation, simulation-based training and assessment has been widely used, significantly improving safety. This progress would have been impossible without the involvement of human factors and ergonomics. Although aviation and health care have similarities, there also are differences that complicate the widespread implementation of simulation in health care.
In this chapter, I review research involving remote human supervision of multiple unmanned vehicles (UVs) using command complexity as an organizing construct. Multi-UV tasks range from foraging, requiring little coordination among UVs, to formation following, in which UVs must function as a cohesive unit. Command complexity, the degree to which operator effort increases with the number of supervised UVs, is used to categorize human interaction with multiple UVs. For systems in which each UV requires the same form of attention (O( n)), effort increases linearly with the number of UVs. For systems in which the control of one UV is dependent upon another (O(> n)), additional UVs impose greater than linear increases due to the expense of coordination. For other systems, an operator interacts with an autonomously coordinating group, and effort is unaffected by group size (O(1)). Studies of human/multi-UV interaction can be roughly grouped into O( n) supervision, involving one-to-one control of individual UVs, or O(1) commanding, in which higher-level commands are directed to a group. Research in O( n) command has centered on round-robin control, neglect tolerance, and attention switching. Approaches to O(1) command are divided into systems using autonomous path planning only, plan libraries, human-steered planners, and swarms. Each type of system has its advantages. Less complete work in scalable displays for multiple UVs is reviewed. Mixing levels of command is probably necessary to supervise multiple UVs performing realistic tasks. Research in O( n) control is mature and can provide quantitative and qualitative guidance for design. Interaction with planners and swarms is less mature but more critical to developing effective multi-UV systems capable of performing complex tasks.
