Traveler Trustworthy Autonomy
This technology is a software framework that bounds the behavior of an untrusted system.
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This technology is a software framework that bounds the behavior of an untrusted system.
This poster addresses a multi-monitor RTA approach to safety bound behavior.
This presentation discusses key accomplishments of the MM-RTA project.
Machine intelligence is improving rapidly based on advances in big data analytics, deep learning algorithms, networked operations, and continuing exponential growth in computing power (Moores Law). This growth in the power and applicability of increasingly intelligent systems will change the roles humans, shifting them to tasks where adaptive problem solving, reasoning and decision-making is required. This talk will address the challenges involved in engineering autonomous systems that function effectively with humans in aeronautics domains.
Machine intelligence is improving rapidly based on advances in big data analytics, deep learning algorithms, networked operations, and continuing exponential growth in computing power (Moores Law). This growth in the power and applicability of increasingly intelligent systems will change the roles humans, shifting them to tasks where adaptive problem solving, reasoning and decision-making is required. This talk will address the challenges involved in engineering autonomous systems that function effectively with humans in aeronautics domains.
This presentation is a technical update for the NATO-STO HFM-247 working group. Our progress on four goals will be discussed. For Goal 1, a conceptual model of HAT is presented. HAT looks to make automation act as more of a teammate, by having it communicate with human operators in a more human, goal-directed, manner which provides transparency into the reasoning behind automated recommendations and actions. This, in turn, permits more trust in the automation when it is appropriate, and less when it is not, allowing a more targeted supervision of automated functions. For Goal 2, we wanted to test these concepts and principles. We present findings from a recent simulation and describe two in progress. Goal 3 was to develop pattern(s) of HAT solution(s). These were originally presented at HCII 2016 and are reviewed. Goal 4 is to develop a re-usable HAT software agent. This is an ongoing effort to be delivered October 2017.
For the first time in a spaceflight operational environment, our team enabled an ISS (International Space Station) crewmember to plan, reschedule, and execute their activities in real-time while abiding by flight and scheduling constraints. The Crew Autonomous Scheduling Test (CAST) investigated the novel concept of operations: allowing crew to manage their own timeline.
Overview of Workshop terms and goals for Enabling Autonomous Flight and Operations in the National Airspace.
Improved real-time decision-making capabilities in both civil transport avionics and airline dispatcher workstations are helping to improve commercial aviation operations in many ways. One emerging capability is the automated derivation of alternate flight plans that yield both flight cost savings and smoother workflow. This emerging capability may be complemented with automated trajectory negotiation capabilities. Here we explore such automated trajectory negotiation capabilities, potential benefit mechanisms, and the required tools, procedures, and architectures.
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Explore the source record for details and available documents.
Explore the source record for details and available documents.
Workshop Description: NASA hosts an annual technology transfer workshop to facilitate the transfer of OSAM technologies to U.S. industry. Due to precautions surrounding COVID-19, the fifth OSAM Technology Transfer Workshop will be held virtually on September 22-23. Workshop attendees will enjoy access to an updated technology catalog, information about the latest developments from NASA subject matter experts, and a tour of NASA facilities.
Within the domain of human spaceflight, crew scheduling for International Space Station (ISS) remains a human-driven planning task. Large teams of flight controllers (called Ops Planners) spend weeks creating violation-free schedules for all crewmembers. As NASA considers long-duration exploration missions, the necessary shift of scheduling and planning management from Ops Planners to crew members requires significant research and investigation of crew performance to complete these scheduling tasks. This pilot study was conducted to evaluate non-expert human performance for the task of planning and scheduling, focusing on scheduling problems that increased in complexity based on the number of activities to be scheduled and the number of planning constraints. Nine non-expert planners were recruited to complete scheduling tasks using Playbook, a scheduling software. The results of this pilot study show that scheduling performance decreased as scheduling workload (i.e. number of activities and percent of activities with planning constraints) increased. This paper provides evidence towards developing a model for scheduling task difficulty and identifies potential implications for future automated aids for flight crew scheduling.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Within the domain of human spaceflight, crew scheduling for International Space Station (ISS) remains a human-driven planning task. Large teams of flight controllers (called Ops Planners) spend weeks creating violation-free schedules for all crewmembers. As NASA considers long-duration exploration missions, the necessary shift of scheduling and planning management from Ops Planners to crew members requires significant research and investigation of crew performance to complete these scheduling tasks. This pilot study was conducted to evaluate non-expert human performance for the task of planning and scheduling, focusing on scheduling problems that increased in complexity based on the number of activities to be scheduled and the number of planning constraints. Nine non-expert planners were recruited to complete scheduling tasks using Playbook, a scheduling software. The results of this pilot study show that scheduling performance decreased as scheduling workload (i.e. number of activities and percent of activities with planning constraints) increased. This paper provides evidence towards developing a model for scheduling task difficulty and identifies potential implications for future automated aids for flight crew scheduling.