Rinehart D.,Sensis Corporation |
Smith P.,Ohio State University |
Spencer A.,Cognitive Systems Engineering, Inc.
AIAA/IEEE Digital Avionics Systems Conference - Proceedings | Year: 2014
Trends in aviation systems continue a natural progression towards certain characteristics: autonomy, complexity, safety-criticality. These trends are largely inevitable, as new technology offers new capabilities (e.g. advanced sensors, fast processing, and ubiquitous connectivity at low cost and high availability). However, these trends drastically intensify certain verification and validation (V&V) challenges. Conventional design and test processes, which focus on the primary and intended usages, could miss vitally important 'corner cases.' It is our view that increasing levels of autonomy and complexity - along with the need to maintain or improve safety - call for new methods of analysis, verification, and validation to assure system performance and safety. Here we introduce a new method, SME-Defined Scenarios for Autonomy (SDSA), which maximizes the utilization of scenarios and Subject Matter Experts (SMEs). In our view, both of these elements (scenarios and SMEs) warrant more effective, more efficient, and more systematic utilization in complex system V&V. SDSA synthesizes and extends numerous prior methods including scenario/use case development, storyboards, cognitive walkthroughs, and risk assessment. To further tune our method to concerns specific to authority and autonomy (A&A), SDSA incorporates custom 'probes' to highlight certain patterns and contributing factors that have led to past failures, with the effect of stimulating SMEs to identify similar patterns in new contexts. Our 'structured scenario' format facilitates the exploration and management of complex scenario trees. SDSA can be used early in the design of a system (or system of systems), including the conceptual stage, and can also be used to identify new safety or efficiency concerns in both prototype and fielded systems. This paper introduces the details of SDSA as a nascent method. Following that introduction, we present an initial example recently completed (SDSA applied to landing automation) to illustrate how we can successfully identify detailed, relevant scenario paths of concern. © 2014 IEEE. Source
Agency: National Aeronautics and Space Administration | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 99.51K | Year: 2011
Two critical requirements for an effective airport surface management system are:Â? The need to adapt plans both strategically and tactically because of time-varying uncertainty. Â? The need to support coordination and collaboration among a number of different individuals, including controllers in the ATC Tower (ATCT), traffic managers in the ATCT, ARTCCs, TRACONs and ATCSCC, dispatchers and air traffic control coordinators at Flight Operations Centers, and ramp controllers/supervisors at airports. NASA has developed algorithms to support such strategic and tactical adaptive planning for airport surface management. This proposal seeks to complement and support this line of research and development through the definition of roles, responsibilities and procedures for coordination and collaboration among these individuals as they adapt airport departure queues at spots and runways to deal with evolving conditions. It further seeks to design and complete formativeevaluations for interface designs that make use of NASA's adaptive planning algorithms.
Agency: National Aeronautics and Space Administration | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 69.64K | Year: 2004
Decision support tools that make use of surface surveillance technologies data can potentially make it possible to increase airport throughput, better accommodate NAS user needs and improve safety. Currently, the major emphasis of tools like NASA?s Surface Management System and the FAA?s Departure Spacing Program has been on improving the performance of the FAA. However, to fully achieve the potential benefits, corresponding tools must be made available to NAS users. To this end, we propose to develop a sophisticated suite of tools for the NAS users that make integrated use of data about airport surface and airspace operations, and that will allow them to work more effectively in coordination with FAA staff. Two classes of tools will be explored under this SBIR. The first class will consist of programmable alerts and critiquing functions that monitor for important events. The second will focus on the design of advanced algorithms that assist with departure planning and execution. Phase I will result in the development of a prototype system that demonstrates the capabilities of these tools, along with appropriate formative evaluations. Phase II would result in the completion of an operational suite of tools.