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

An evaluation of NASA's program in human factors research: Aircrew-vehicle system interaction

Research in human factors in the aircraft cockpit and a proposed program augmentation were reviewed. The dramatic growth of microprocessor technology makes it entirely feasible to automate increasingly more functions in the aircraft cockpit; the promise of improved vehicle performance, efficiency, and safety through automation makes highly automated flight inevitable. An organized data base and validated methodology for predicting the effects of automation on human performance and thus on safety are lacking and without such a data base and validated methodology for analyzing human performance, increased automation may introduce new risks. Efforts should be concentrated on developing methods and techniques for analyzing man machine interactions, including human workload and prediction of performance

Assessment of the State-of-the-Art of System-Wide Safety and Assurance Technologies

Since its initiation, the System-wide Safety Assurance Technologies (SSAT) Project has been focused on developing multidisciplinary tools and techniques that are verified and validated to ensure prevention of loss of property and life in NextGen and enable proactive risk management through predictive methods. To this end, four technical challenges have been listed to help realize the goals of SSAT, namely (i) assurance of flight critical systems, (ii) discovery of precursors to safety incidents, (iii) assuring safe human-systems integration, and (iv) prognostic algorithm design for safety assurance. The objective of this report is to provide an extensive survey of SSAT-related research accomplishments by researchers within and outside NASA to get an understanding of what the state-of-the-art is for technologies enabling each of the four technical challenges. We hope that this report will serve as a good resource for anyone interested in gaining an understanding of the SSAT technical challenges, and also be useful in the future for project planning and resource allocation for related research

Considerations in Assuring Safety of Increasingly Autonomous Systems

Recent technological advances have accelerated the development and application of increasingly autonomous (IA) systems in civil and military aviation. IA systems can provide automation of complex mission tasks-ranging across reduced crew operations, air-traffic management, and unmanned, autonomous aircraft-with most applications calling for collaboration and teaming among humans and IA agents. IA systems are expected to provide benefits in terms of safety, reliability, efficiency, affordability, and previously unattainable mission capability. There is also a potential for improving safety by removal of human errors. There are, however, several challenges in the safety assurance of these systems due to the highly adaptive and non-deterministic behavior of these systems, and vulnerabilities due to potential divergence of airplane state awareness between the IA system and humans. These systems must deal with external sensors and actuators, and they must respond in time commensurate with the activities of the system in its environment. One of the main challenges is that safety assurance, currently relying upon authority transfer from an autonomous function to a human to mitigate safety concerns, will need to address their mitigation by automation in a collaborative dynamic context. These challenges have a fundamental, multidimensional impact on the safety assurance methods, system architecture, and V&V capabilities to be employed. The goal of this report is to identify relevant issues to be addressed in these areas, the potential gaps in the current safety assurance techniques, and critical questions that would need to be answered to assure safety of IA systems. We focus on a scenario of reduced crew operation when an IA system is employed which reduces, changes or eliminates a human's role in transition from two-pilot operations

Human Performance Risks and Benefits of Adaptive Systems on the Flight Deck

Objective. Human performance risks and benefits of adaptive systems were identified through a systematic analysis and pilot evaluation of adaptive system component types and characteristics. Background. As flight-deck automation is able to process ever more types of information in sophisticated ways to identify situations, it is becoming more realistic for adaptive systems to adapt behavior based on their own authority. Method. A framework was developed to describe the types and characteristics of adaptive system components and was used to perform a risk/benefit analysis to identify potential issues. Subsequently, eight representative adaptive system storyboards were developed for an evaluation with pilots to augment the analysis results and to explore more detailed issues and potential risk mitigations. Results. Analysis identified the principal drivers of adaptive “triggering conditions” risk as complexity and transparency. It also identified the drivers of adaptations risks/benefits as the task level and the level of control vs. information adaptation. Conclusions. Pilots did not seem to distinguish between adaptive automation and normal automation if the rules were simple and obvious; however, their perception of risk increased when the level of complexity and opacity of triggering conditions reached a point where its behavior was perceived as non-deterministic

Application of flight systems methodologies to the validation of knowledge-based systems

Flight and mission-critical systems are verified, qualified for flight, and validated using well-known and well-established techniques. These techniques define the validation methodology used for such systems. In order to verify, qualify, and validate knowledge-based systems (KBS's), the methodology used for conventional systems must be addressed, and the applicability and limitations of that methodology to KBS's must be identified. The author presents an outline of how this approach to the validation of KBS's is being developed and used at the Dryden Flight Research Facility of the NASA Ames Research Center

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

Engage D1.2 Final Project Results Report

This deliverable summarises the activities and results of Engage, the SESAR 2020 Knowledge Transfer Network (KTN). The KTN initiated and supported multiple activities for SESAR and the European air traffic management (ATM) community, including PhDs, focused catalyst fund projects, thematic workshops, summer schools and the launch of a wiki as the one-stop, go-to source for ATM research and knowledge in Europe. Key throughout was the integration of exploratory and industrial research, thus expediting the innovation pipeline and bringing researchers together. These activities laid valuable foundations for the SESAR Digital Academy