Predicting pilot error on the flight deck: Validation of a new methodology and a multiple methods and analysts approach to enhancing error prediction sensitivity

The Human Error Template (HET) is a recently developed methodology for predicting designed induced pilot error. This article describes a validation study undertaken to compare the performance of HET against three contemporary Human Error Identification (HEI) approaches when used to predict pilot errors for an approach and landing task and also to compare individual analyst error predictions to an approach to enhancing error prediction sensitivity: the multiple analysts and methods approach, whereby multiple analyst predictions using a range of HEI technique are pooled. The findings indicate that, of the four methodologies used in isolation, analysts using the HET methodology offered the most accurate error predictions, and also that the multiple analysts and methods approach was more successful overall in terms of error prediction sensitivity than the three other methods but not the HET approach. The results suggest that when predicting design induced error, it is appropriate to use domain specific approaches and also a toolkit of different HEI approaches and multiple analysts in order to heighten error prediction sensitivity

Reducing Runway Incursions: The Role of Collaboration, Education, and Training

Runway incursions are a major threat to aviation safety and can cause major delays and collisions that have significant human and financial implications for airlines. This study investigated how training, education, and collaboration may be improved to reduce the occurrence of runway incursions at airports. Data collection involved interviews, a focus group, and document analysis to explore the participants’ perceptions. The interviews and focus group involved a purposive sample of 12 pilots, air traffic controllers, airport administrators, and ground personnel. The interviews and focus group transcripts were chunked, coded, and patterns sought to form five key themes addressing the research question: exercising key safety practices, effective communication, a greater focus on scenario-based training, need for greater standardization, and more collaboration and partnership among stakeholders. The findings have the potential to influence Federal Aviation Administration’s (FAA) decision-making through resource allocation for improving runway safety, as well as to inform the prevention of runway incursions through improvements to education, training, and collaboration

Carbon Footprint in the Commercial Aviation Industry: Current Situation and Measures to Reduce Emissions Using the Example of Lufthansa

The goal of this thesis is to give an overview of the carbon footprint of the commercial aviation industry and to introduce measures to mitigate emissions. This will be done by taking the German Lufthansa Group as an example. In the first part, relevant theoretical background information will be given. It will be shown that the commercial aviation industry is subject to steady and relatively strong growth. Even though the global share of GHG emissions caused by air traffic is currently relatively low, it is projected to increase in accordance with overall industry growth. In the second part, measures taken by the aviation industry to reduce its emissions are presented using the example of Lufthansa. The measures that are taken are various, reaching from fleet renewal over infrastructural improvements such as airspace management to alternative fuels. It is also shown that the efficiency of an airline depends on different things and hence leads to different performances in the industry. Even though the reduction of emissions is typically related with a reduction of costs for the aviation industry, the progress in some areas is still relatively slow

The Human Factors Analysis and Classification System--HFACS

Human error has been implicated in 70 to 80% of all civil and military aviation accidents. Yet, most accident reporting systems are not designed around any theoretical framework of human error. As a result, most accident databases are not conducive to a traditional human error analysis, making the identification of intervention strategies onerous. What is required is a general human error framework around which new investigative methods can be designed and existing accident databases restructured. Indeed, a comprehensive human factors analysis and classification system (HFACS) has recently been developed to meet those needs. Specifically, the HFACS framework has been used within the military, commercial, and general aviation sectors to systematically examine underlying human causal factors and to improve aviation accident investigations. This paper describes the development and theoretical underpinnings of HFACS in the hope that it will help safety professionals reduce the aviation accident rate through systematic, data-driven investment strategies and objective evaluation of intervention programs

Beyond "Complacency and Panic": Will the NIS Directive Improve the Cybersecurity of Critical National Infrastructure?

This is a pre-copyedited, author-produced version of an article accepted for publication in European Law Review following peer review. The definitive published version Michels, J. and I. Walden. “Beyond “Complacency and Panic”: Will the NIS Directive Improve the Cybersecurity of Critical National Infrastructure?” European Law Review (2020): 25-47. is available online on Westlaw UK

Ultra-Long-Haul Commercial Operations: An Assessment of Current Health and Safety Standards

The international and national authorities, manufacturers, and commercial airlines have invested extensively in-flight crew operational research and aircraft system development in preparation for ULH flights. Conversely, the progress on health and safety and its impact and standards has received limited attention in the industry. Though stringent medical certification requirements by international and national regulatory bodies ensure no deviance in operational safety, less emphasis has been put on other occupational factors that can impact the aircrew while operating these ULH routes. The current studies on the topic are sparse and have only focused on factors such as fatigue, sleep loss, circadian rhythm, and alertness for pilots operating these routes. Concurrently, limited and inconsistent studies have focused on flight attendants\u27 experiences of these factors while operating ULH flights. This thesis research will help determine various regulatory health and safety standards and best practices for aircrew operating ULH routes. The study also reviews the current state of health culture and investigates if it is practiced in the current aviation operational dynamic. Correspondingly, this study also intends to identify and address gaps in the current health and safety regulatory structure that can help form a well-controlled baseline knowledge. Based on the literature on health and safety in aviation, an online survey was developed, which consisted of a mix of open-ended qualitative and close-ended quantitative questions. The sample for this research was drawn from a population of aircrew who currently operate ULH operations. The analysis of the survey data presented significantly different response experiences between pilots and flight attendants. Pilots reported a higher prevalence of cabin air quality and humidity, noise, and vibration concerning the cabin environment. In contrast, the flight attendant reported that in-flight rest facilities significantly affect their health while operating these routes. For in-flight job related, the pilot reported dehydration, improper diet, and lower back pain as the top three health-related factors. Conversely, the flight attendant reported dehydration, deep vein thrombosis, and neck pain as the top three health-related in-flight factors experienced on the ULH flight. Further analysis of this study suggested that the regulatory authorities established very few specific regulations and advisory guidance concerning aircrew health and safety regulations for ULH operations. Most current regulations are prescribed for fatigue and its management, and only limited regulations have been established for other in-flight effects experienced by aircrew. Notably, most of these regulations are pilot-centric, and only a few specific regulations have been established for flight attendants. Due to the small sample size of this study, presenting any conclusion on health culture was challenging. This study has identified that aviation regulators and operators should undertake additional research on a large scale to identify health and safety impact factors for aircrew operating these ULH routes. Lastly, aviation regulators must revise, address and improve many health and safety regulation areas pertaining to flight attendants

EXPLORING THE POTENTIAL OF A MACHINE TEAMMATE

Artificial intelligence has been in use for decades. It is already deployed in manned formations and will continue to be fielded to military units over the next several years. Current strategies and operational concepts call for increased use of artificial-intelligence capabilities across the defense enterprise—from senior leaders to the tactical edge. Unfortunately, artificial intelligence and the warriors that they support will not be compatible "out of the box." Simply bolting an artificial intelligence into teams of humans will not ensure success. The Department of Defense must pay careful attention to how it is deploying artificial intelligences alongside humans. This is especially true in teams where the structure of the team and the behaviors of its members can make or break performance. Because humans and machines work differently, teams should be designed to leverage the strengths of each partner. Team designs should account for the inherent strengths of the machine partner and use them to shore up human weaknesses. This study contributes to the body of knowledge by submitting novel conceptual models that capture the desired team behaviors of humans and machines when operating in human-machine teaming constructs. These models may inform the design of human-machine teams in ways that improve team performance and agility.NPS_Cruser, Monterey, CA 93943Outstanding ThesisMajor, United States Marine CorpsMajor, United States Marine CorpsApproved for public release. Distribution is unlimited

The UAVs threat to airport security: risk analysis and mitigation

Purpose: This research studies the UAV incidents in the vicinity of worldwide airports in order to deliver a quantitative and qualitative analysis of this phaenomenon, to analyse the risks associated to this threat and propose mitigation measures that brings this risk to an ‘acceptable’ level. Methodology: A population of 139 ‘serious UAV incidents in the vicinity of worldwide airports’ has been constituted on the basis of the FAA and NASA databases and articles published on the Web by online media. This phaenomenon has then been analysed quantitatively using descriptive statistics techniques and qualitatively by analysing in-depth some representative incidents. A risk analysis has then been performed based on the FAA Safety Risk Management 5-steps process to identify the hazards i.e. the root causes of those UAV incidents, determine their outcome i.e. negative consequences that jeopardize airports objectives and assign them a severity level and likelihood i.e. frequency level. Analysed risks have then been assessed based on FAA ARP Risk Matrix. Mitigation measures (prevention, deterrence, denial, detection, neutralisation) have been identified following a ‘Defence-in-Depth’ approach. Findings: The findings of the study are that those UAV incidents are more numerous than anticipated and happen higher and further from the airports than expected: they happen not only in CTRs but also in TMAs. This has an impact on the mitigation measures that shall not only be deployed at airports side but also be on-boarded in manned aircrafts. Originality: To our knowledge, no study has combined different sources to constitute such a population focused on ‘serious’ UAVs incidents around airports worldwide, has applied the official FAA Safety Risk Management process to assess this risk and followed a structured ‘Defence-in-Depth’ approach typically used in Cybersecurity to mitigate this risk.Peer Reviewe

A First Look at the Evolution of Flight Crew Requirements for Emerging Market Aircraft

This is an exciting time for aviation. New vehicle and airspace technologies promise large increases in the number of aircraft in operation. One critical technology for these emerging markets is the increased use of automated systems to reduce pilot skill, training, and proficiency requirements. While the use of these systems promises to reduce or eliminate pilot functions in the long-term, the technology development for the required functions will necessitate a phased transition. The transition to, and adoption of automated systems will generate new safety challenges. This paper is a first look at a model to help frame flight crew functions for evaluation of future operational requirements. The model is intended to provide required flight crew functions regardless of whether the functions are performed by human or artificial agent. It is hoped that the model will be useful in identifying safety challenges and enabling a safe transition for the new aviation markets. The paper presents some background for a model for framing the flight crew function model and some thoughts about next steps

Trajectory-Based, Probabilistic Risk Model for UAS Operations

To enable the safe integration of Unmanned Aircraft System (UAS) into the civil airspace, the European Aviation Safety Agency (EASA) has elaborated a new regulatory framework that is operation-centric and risk-based. Based on this principle, gaining authorization to conduct certain types of operations depends on a safety risk assessment. To harmonize this process, the Joint Authorities for Rulemaking on Unmanned Systems (JARUS) released a qualitative methodology called Specific Operation Risk Assessment (SORA). However, SORA is not a complete safety assessment tool since, in some cases, a quantitative risk analysis is still required. This work develops a probabilistic risk model that extends SORA to evaluate the ground risk and the air risk components along a specified UAS trajectory quantitatively. The proposed model is supplied with illustrative data and is validated in a representative UAS mission. In the future, the risk model will be exploited to develop a decision tool for determining the minimum-risk trajectory when multiple, alternative routes are available