Experimental Study of Vertical Flight Path Mode Awareness

An experimental simulator study was run to test pilot detection of an error in autopilot mode selection. Active airline air crew were asked to fly landing approaches by commanding the Flight Path Angle mode while monitoring the approach with both a Head Up Display and Head Down Displays. During one approach, the Vertical Speed mode was intentionally triggered by an experimenter instead, causing a high rate of descent below the intended glide path. Of the 12 pilots, 10 were unable to detect the high descent rate prior to significant glide path deviation

Intelligent Pilot Aids for Flight Re-Planning in Emergencies

Effective and safe control of an aircraft may be difficult or nearly impossible for a pilot following an unexpected system failure. Without prior training, the pilot must ascertain on the fly those changes in both manual control technique and procedures that will lead to a safe landing of the aircraft. Sophisticated techniques for determining the required control techniques are now available. Likewise, a body of literature on pilot decision making provides formalisms for examining how pilots approach discrete decisions framed as the selection between options. However, other aspects of behavior, such as the task of route planning and guidance, are not as well studied. Not only is the pilot faced with possible performance changes to the aircraft dynamics, but he or she is also tasked to create a plan of actions that will effectively take the aircraft down to a safe landing. In this plan, the many actions that the pilot can perform are closely intertwined with the trajectory of the aircraft, making it difficult to accurately predict the final outcome. Coupled with the vast number of potential actions to be taken, this problem may seem intractable. This is reflected in the lack of a pre-specified procedure capable of giving pilots the ability to find a resolution for this task. This report summarizes a multi-year effort to examine methods to aid pilots in planning an approach and arrival to an airport following an aircraft systems failure. Ultimately, we hypothesize that automatic assistance to pilots can be provided in real-time in the form of improving pilot control of a damaged aircraft and providing pilots with procedural directives suitable for critical flight conditions; such systems may also benefit pilot training and procedure design. To achieve this result, a systematic, comprehensive research program was followed, building on prior research. This approach included a pencil-and-paper study with airline pilots examining methods of representing a flight route in an immediately understandable manner, and in a manner that would allow the pilot to modify an automatically-generated route and/or detect any inappropriate elements in an automatically-generated route. Likewise, a flight simulator study examined different cockpit systems for the relative merits of providing pilots with any of a variety of automated functions for emergency flight planning. The results provide specific guidance for the design of such systems

Variations in party line information requirements for flight crew situation awareness in the datalink environment

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1994.Includes bibliographical references (leaf 76).by Amy R. Pritchett.M.S

Design of Support Systems for Dynamic Decision Making in Airline Operations

Presented at the Institute of Electrical and Electronics Engineers (IEEE) Systems and Information Engineering Design Symposium, Charlottesville, Virginia, April, 2006 and published in the Proceedings of the 2006 IEEE Systems and Information Engineering Design Symposium. ©2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.To date, there has been very little research conducted on the design of support systems for dynamic decisions environments, such as airline operations. The paper discusses the idea that the regulation of dynamic systems has implications for both "internal" and "external" dynamic systems with respect to the human operator. Hollnagel's Contextual Control Modes are suggested as a framework for designing such support systems, noting that they can identify requirements specific to different contextual control modes

Modeling the Work of Humans and Automation in Complex Operations

Humans have always been the vital components of complex operations, notably including aviation. They remain so even as sophisticated automation systems are introduced, changing -but not eliminating -the role of the human relative to the collective work required to achieve mission performance. Automation designers and certification agencies are interested in methods to predict and model how complex operations can be performed by teams of humans and automated agents. This paper proposes that the combined activities of both human and automation required by a proposed design can best be captured by focusing on modeling the work inherent to a complex operation. As a fundamental first step, the overall concept of operations spanning all the work activities can be examined for its feasibility in nominal and off-nominal conditions. These activities can then also be examined to see whether the demands they place upon the human agents in the system are feasible and facilitate the human's ability to contribute, rather than assuming unreasonable situations such as excessive workload, boredom, incoherent task descriptions, excessive monitoring requirements, etc. Further, trade-offs in distributing these activities across agents (both human and automated) can be evaluated in terms of task-interleaving created by the distribution of activity and in terms of the 'interaction overhead' associated with communication and coordination between agents required for a given distribution. A description of a modeling and simulation framework capable of modeling work is provided along with an analysis framework to evaluate proposed complex operations

Reducing Aggressive Responses to TCAS: Evaluation of a TCAS Training Program

The Traffic alert and Collision Avoidance System (TCAS) is an aircraft collision avoidance system designed to prevent mid-air collisions. While responding to a TCAS advisory is generally the safe course of action, instances of overly aggressive responses have resulted in injuries to crew members and passengers as well as disruptions in air traffic operations. However, current training standards do not address the need to mitigate overly aggressive responses. This paper details the design and evaluation of a training program for TCAS which incorporated a learning objective related to mitigating aggressive responses to advisories. The impact of the training program was evaluated by comparing the results of two flight simulator experiments. These experiments examined “trained” and “untrained” pilot responses to TCAS advisories in an integrated flight deck-Air Traffic Control simulator. Overall, the training program had a significant impact on the pilots’ behavior and aggressive responses to TCAS advisories were decreased

Supporting Multiple Cognitive Processing Styles Using Tailored Support Systems

According to theories of cognitive processing style or cognitive control mode, human performance is more effective when an individual’s cognitive state (e.g., intuition/scramble vs. deliberate/strategic) matches his/her ecological constraints or context (e.g., utilize intuition to strive for a "good-enough" response instead of deliberating for the "best" response under high time pressure). Ill-mapping between cognitive state and ecological constraints are believed to lead to degraded task performance. Consequently, incorporating support systems which are designed to specifically address multiple cognitive and functional states e.g., high workload, stress, boredom, and initiate appropriate mitigation strategies (e.g., reduce information load) is essential to reduce plant risk. Utilizing the concept of Cognitive Control Models, this paper will discuss the importance of tailoring support systems to match an operator's cognitive state, and will further discuss the importance of these ecological constraints in selecting and implementing mitigation strategies for safe and effective system performance. An example from the nuclear power plant industry illustrating how a support system might be tailored to support different cognitive states is included

A Simulation Engine to Predict Multi-Agent Work in Complex, Dynamic, Heterogeneous Systems

©2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.DOI: 10.1109/COGSIMA.2011.5753432This paper documents a simulation engine developed to accurately and efficiently simulate work by multiple agents in complex dynamic systems. Agents (human or mechanical) are modeled as responding to, and changing, their environment by executing the actions that get and set the value of resources in the environment. Each action comprises the processes that need to be evaluated at the same time by the same agent, which are used to reference (get) resources, consider them according to simple or complicated processes, and then interact back on the environment by setting resources appropriately. This paper specifically addresses timing within the simulation. The simplest approach would update all actions at the smallest unit of conceivable time, an approach that is not only computationally inefficient, but also not an accurate representation of situated behavior. Instead, every action declares its next update time as required to accurately model its internal dynamics and the simulation engine executes them asynchronously. Thus, an action and the resources it ’gets’ from the environment are not inherently contemporary; instead, each action also specifies, for each resource value that it gets, the quality of service required in terms of its temporal currency. This reflects dynamics of the real processes being simulated: when, in actual operations, would the environment be sampled, and how accurately must its state be known? Additionally, this also reflects dynamics of environmental resources how often (or how fast) does each inherently change? Using these constructs, the list of actions to be simulated are sorted by the simulation engine according to their next update time. Each action, when its time comes, is given to their agent model to be executed, and then is sorted back into the action list according to its self-reported next update time. Thus, actions are each updated when they need to be. In situations where, for example, action Y needs to get a resource which, because action X has not set it recently, does not meet action Ys required Quality of Service. The simulation engine will invoke action X immediately before action Y, mimicking cases in the real system where one process calls on another to establish the conditions it needs. The presented simulation engine is a complete redevelopment, designed and written from scratch at the Cognitive Engineering Center at the Georgia Institute of Technology

Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic. Methods: The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic. Findings: Global DALYs increased from 2·63 billion (95% UI 2·44–2·85) in 2010 to 2·88 billion (2·64–3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7–17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8–6·3) in 2020 and 7·2% (4·7–10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0–234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7–198·3]), neonatal disorders (186·3 million [162·3–214·9]), and stroke (160·4 million [148·0–171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3–51·7) and for diarrhoeal diseases decreased by 47·0% (39·9–52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54–1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5–9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0–19·8]), depressive disorders (16·4% [11·9–21·3]), and diabetes (14·0% [10·0–17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7–27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6–63·6) in 2010 to 62·2 years (59·4–64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6–2·9) between 2019 and 2021. Interpretation: Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades. Funding: Bill & Melinda Gates Foundation