3,710 research outputs found
Air Traffic Safety: continued evolution or a new Paradigm.
The context here is Transport Risk Management. Is the philosophy of Air Traffic Safety different from other modes of transport? â yes, in many ways, it is. The focus is on Air Traffic Management (ATM), covering (eg) air traffic control and airspace structures, which is the part of the aviation system that is most likely to be developed through new paradigms. The primary goal of the ATM system is to control accident risk. ATM safety has improved over the decades for many reasons, from better equipment to additional safety defences. But ATM safety targets, improving on current performance, are now extremely demanding. What are the past and current methodologies for ATM risk assessment; and will they work effectively for the kinds of future systems that people are now imagining and planning? The title contrasts âContinued Evolutionâ and a âNew Paradigmâ. How will system designers/operators assure safety with traffic growth and operational/technical changes that are more than continued evolution from the current system? What are the design implications for ânew paradigmsâ, such as the USAâs âNext Generation Air Transportation Systemâ (NextGen) and Europeâs Single European Sky ATM Research Programme (SESAR)? Achieving and proving safety for NextGen and SESAR is an enormously tough challenge. For example, it will need to cover system resilience, human/automation issues, software/hardware performance/ground/air protection systems. There will be a need for confidence building programmes regarding system design/resilience, eg Human-in-the-Loop simulations with âseeded errorsâ
Air Traffic Management Safety Challenges
The primary goal of the Air Traffic Management (ATM) system is to control accident risk. ATM
safety has improved over the decades for many reasons, from better equipment to additional
safety defences. But ATM safety targets, improving on current performance, are now extremely
demanding. Safety analysts and aviation decision-makers have to make safety assessments
based on statistically incomplete evidence. If future risks cannot be estimated with precision,
then how is safety to be assured with traffic growth and operational/technical changes? What
are the design implications for the USAâs âNext Generation Air Transportation Systemâ
(NextGen) and Europeâs Single European Sky ATM Research Programme (SESAR)? ATM
accident precursors arise from (eg) pilot/controller workload, miscommunication, and lack of upto-
date information. Can these accident precursors confidently be âdesigned outâ by (eg) better
system knowledge across ATM participants, automatic safety checks, and machine rather than
voice communication? Future potentially hazardous situations could be as âmessyâ in system
terms as the Ăberlingen mid-air collision. Are ATM safety regulation policies fit for purpose: is it
more and more difficult to innovate, to introduce new technologies and novel operational
concepts? Must regulators be more active, eg more inspections and monitoring of real
operational and organisational practices
Interpretable Categorization of Heterogeneous Time Series Data
Understanding heterogeneous multivariate time series data is important in
many applications ranging from smart homes to aviation. Learning models of
heterogeneous multivariate time series that are also human-interpretable is
challenging and not adequately addressed by the existing literature. We propose
grammar-based decision trees (GBDTs) and an algorithm for learning them. GBDTs
extend decision trees with a grammar framework. Logical expressions derived
from a context-free grammar are used for branching in place of simple
thresholds on attributes. The added expressivity enables support for a wide
range of data types while retaining the interpretability of decision trees. In
particular, when a grammar based on temporal logic is used, we show that GBDTs
can be used for the interpretable classi cation of high-dimensional and
heterogeneous time series data. Furthermore, we show how GBDTs can also be used
for categorization, which is a combination of clustering and generating
interpretable explanations for each cluster. We apply GBDTs to analyze the
classic Australian Sign Language dataset as well as data on near mid-air
collisions (NMACs). The NMAC data comes from aircraft simulations used in the
development of the next-generation Airborne Collision Avoidance System (ACAS
X).Comment: 9 pages, 5 figures, 2 tables, SIAM International Conference on Data
Mining (SDM) 201
Adaptive Airborne Separation to Enable UAM Autonomy in Mixed Airspace
The excitement and promise generated by Urban Air Mobility (UAM) concepts have inspired both new entrants and large aerospace companies throughout the world to invest hundreds of millions in research and development of air vehicles, both piloted and unpiloted, to fulfill these dreams. The management and separation of all these new aircraft have received much less attention, however, and even though NASAs lead is advancing some promising concepts for Unmanned Aircraft Systems (UAS) Traffic Management (UTM), most operations today are limited to line of sight with the vehicle, airspace reservation and geofencing of individual flights. Various schemes have been proposed to control this new traffic, some modeled after conventional air traffic control and some proposing fully automatic management, either from a ground-based entity or carried out on board among the vehicles themselves. Previous work has examined vehicle-based traffic management in the very low altitude airspace within a metroplex called UTM airspace in which piloted traffic is rare. A management scheme was proposed in that work that takes advantage of the homogeneous nature of the traffic operating in UTM airspace. This paper expands that concept to include a traffic management plan usable at all altitudes desired for electric Vertical Takeoff and Landing urban and short-distance, inter-city transportation. The interactions with piloted aircraft operating under both visual and instrument flight rules are analyzed, and the role of Air Traffic Control services in the postulated mixed traffic environment is covered. Separation values that adapt to each type of traffic encounter are proposed, and the relationship between required airborne surveillance range and closure speed is given. Finally, realistic scenarios are presented illustrating how this concept can reliably handle the density and traffic mix that fully implemented and successful UAM operations would entail
Air Traffic Control Safety Indicators: What is Achievable?
European Air Traffic Control is extremely safe. The drawback to this safety
record is that it is very difficult to estimate what the âunderlyingâ accident rate for mid-air
collisions is now, or to detect any changes over time. The aim is to see if it possible to
construct simple ATC safety indicators that correlate with this underlying accident rate. A
perfect indicator would be simple to comprehend and capable of being calculated by a
checklist process. An important concept is that of âsystem controlâ: the ability to
determine the outcome against reasonably foreseen changes and variations of system
parameters. A promising indicator is âIncident Not Resolved by ATCâ, INRA, incidents
in which the ground ATC defences have been âused upâ. The key question is: if someone
says he or she knows how to make a good estimate of the underlying accident rate, then
how could this claim be tested? If it correlates very well with INRA, then what would be
the argument for saying that it is a better indicator
Aircraft Loss-of-Control: Analysis and Requirements for Future Safety-Critical Systems and Their Validation
Loss of control remains one of the largest contributors to fatal aircraft accidents worldwide. Aircraft loss-of-control accidents are complex, resulting from numerous causal and contributing factors acting alone or more often in combination. Hence, there is no single intervention strategy to prevent these accidents. This paper summarizes recent analysis results in identifying worst-case combinations of loss-of-control accident precursors and their time sequences, a holistic approach to preventing loss-of-control accidents in the future, and key requirements for validating the associated technologies
Future Integrated Systems Concept for Preventing Aircraft Loss-of-Control Accidents
Loss of control remains one of the largest contributors to aircraft fatal accidents worldwide. Aircraft loss-of-control accidents are highly complex in that they can result from numerous causal and contributing factors acting alone or (more often) in combination. Hence, there is no single intervention strategy to prevent these accidents. This paper presents future system concepts and research directions for preventing aircraft loss-of-control accidents
Considerations for the design of an onboard air traffic situation display
The basic concept of remoting information to the cockpit is used to design and develop a computerized airborne traffic situation display device that automatically selects and presents segments of a controller's scope to the aircraft pilot via a narrow band digital data link. These data are integrated with aircraft heading and navigation information to provide a display useful in congested air space. The display can include alphanumerical symbols, air route maps, and controller instructions
UAS Surveillance Criticality
The integration of unmanned aircraft systems (UAS) into the national airspace system (NAS) poses considerable challenges. Maintaining human safety is perhaps chief among these challenges as UAS remote pilots will need to interact with other UAS, piloted aircraft, and other conditions associated with flight. A research team of 6 leading UAS research universities was formed to respond to a set of surveillance criticality research questions. Five analysis tools were selected following a literature review to evaluate airborne surveillance technology performance. The analysis tools included: Fault Trees, Monte Carlo Simulations, Hazard Analysis, Design of Experiments (DOE), and Human-in-the-Loop Simulations. The Surveillance Criticality research team used results from these analyses to address three primary research questions and provide recommendations for UAS detect-and-avoid mitigation and areas for further research
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