Pattern-Based Genetic Algorithm for Airborne Conflict Resolution

NASA has developed the Autonomous Operations Planner (AOP) airborne decision support tool to explore advanced air traffic control concepts that include delegating separation authority to aircraft. A key element of the AOP is its strategic conflict resolution (CR) algorithm, which must resolve conflicts while maintaining conformance with traffic flow management constraints. While a previous CR algorithm, which focused on broader flight plan optimization objectives as a part of conflict resolution, had successfully been developed, new research has identified the need for resolution routes the users find more acceptable (i.e., simpler and more intuitive). A new CR algorithm is presented that uses a combination of pattern-based maneuvers and a genetic algorithm to achieve these new objectives. Several lateral and vertical maneuver patterns are defined and the application of the genetic algorithm explained. A new approach to defining a conflicted fitness function using estimates of the local conflict region around a conflicted trajectory is also presented. Preliminary performance characteristics of the implemented algorithm are provided

Costs of Limiting Route Optimization to Published Waypoints in the Traffic Aware Planner

The Traffic Aware Planner (TAP) is an airborne advisory tool that generates optimized, traffic-avoiding routes to support the aircraft crew in making strategic reroute requests to Air Traffic Control (ATC). TAP is derived from a research-prototype self-separation tool, the Autonomous Operations Planner (AOP), in which optimized route modifications that avoid conflicts with traffic and weather, using waypoints at explicit latitudes and longitudes (a technique supported by self-separation concepts), are generated by maneuver patterns applied to the existing route. For use in current-day operations in which trajectory changes must be requested from ATC via voice communication, TAP produces optimized routes described by advisories that use only published waypoints prior to a reconnection waypoint on the existing route. We describe how the relevant algorithms of AOP have been modified to implement this requirement. The modifications include techniques for finding appropriate published waypoints in a maneuver pattern and a method for combining the genetic algorithm of AOP with an exhaustive search of certain types of advisory. We demonstrate methods to investigate the increased computation required by these techniques and to estimate other costs (measured in terms such as time to destination and fuel burned) that may be incurred when only published waypoints are used

David Glaze and Karr La Miller in a Junior Recital

This is the program for the junior piano recital of David Glaze, and the junior voice recital of mezzo-soprano, Karr La Miller, accompanied by Glenda Plummer on piano. The recital was held on April 26, 1968

Autonomous Operations Planner: A Flexible Platform for Research in Flight-Deck Support for Airborne Self-Separation

The Autonomous Operations Planner (AOP), developed by NASA, is a flexible and powerful prototype of a flight-deck automation system to support self-separation of aircraft. The AOP incorporates a variety of algorithms to detect and resolve conflicts between the trajectories of its own aircraft and traffic aircraft while meeting route constraints such as required times of arrival and avoiding airspace hazards such as convective weather and restricted airspace. This integrated suite of algorithms provides flight crew support for strategic and tactical conflict resolutions and conflict-free trajectory planning while en route. The AOP has supported an extensive set of experiments covering various conditions and variations on the self-separation concept, yielding insight into the system s design and resolving various challenges encountered in the exploration of the concept. The design of the AOP will enable it to continue to evolve and support experimentation as the self-separation concept is refined

Experimental Performance of a Genetic Algorithm for Airborne Strategic Conflict Resolution

The Autonomous Operations Planner, a research prototype flight-deck decision support tool to enable airborne self-separation, uses a pattern-based genetic algorithm to resolve predicted conflicts between the ownship and traffic aircraft. Conflicts are resolved by modifying the active route within the ownship s flight management system according to a predefined set of maneuver pattern templates. The performance of this pattern-based genetic algorithm was evaluated in the context of batch-mode Monte Carlo simulations running over 3600 flight hours of autonomous aircraft in en-route airspace under conditions ranging from typical current traffic densities to several times that level. Encountering over 8900 conflicts during two simulation experiments, the genetic algorithm was able to resolve all but three conflicts, while maintaining a required time of arrival constraint for most aircraft. Actual elapsed running time for the algorithm was consistent with conflict resolution in real time. The paper presents details of the genetic algorithm s design, along with mathematical models of the algorithm s performance and observations regarding the effectiveness of using complimentary maneuver patterns when multiple resolutions by the same aircraft were required

Point-Mass Aircraft Trajectory Prediction Using a Hierarchical, Highly-Adaptable Software Design

A highly adaptable and extensible method for predicting four-dimensional trajectories of civil aircraft has been developed. This method, Behavior-Based Trajectory Prediction, is based on taxonomic concepts developed for the description and comparison of trajectory prediction software. A hierarchical approach to the "behavioral" layer of a point-mass model of aircraft flight, a clear separation between the "behavioral" and "mathematical" layers of the model, and an abstraction of the methods of integrating differential equations in the "mathematical" layer have been demonstrated to support aircraft models of different types (in particular, turbojet vs. turboprop aircraft) using performance models at different levels of detail and in different formats, and promise to be easily extensible to other aircraft types and sources of data. The resulting trajectories predict location, altitude, lateral and vertical speeds, and fuel consumption along the flight path of the subject aircraft accurately and quickly, accounting for local conditions of wind and outside air temperature. The Behavior-Based Trajectory Prediction concept was implemented in NASA's Traffic Aware Planner (TAP) flight-optimizing cockpit software application

Handling Trajectory Uncertainties for Airborne Conflict Management

Airborne conflict management is an enabling capability for NASA's Distributed Air-Ground Traffic Management (DAG-TM) concept. DAGTM has the goal of significantly increasing capacity within the National Airspace System, while maintaining or improving safety. Under DAG-TM, autonomous aircraft maintain separation from each other and from managed aircraft unequipped for autonomous flight. NASA Langley Research Center has developed the Autonomous Operations Planner (AOP), an onboard decision support system that provides airborne conflict management (ACM) and strategic flight planning support for autonomous aircraft pilots. The AOP performs conflict detection, prevention, and resolution from nearby traffic aircraft and area hazards. Traffic trajectory information is assumed to be provided by Automatic Dependent Surveillance Broadcast (ADS-B). Reliable trajectory prediction is a key capability for providing effective ACM functions. Trajectory uncertainties due to environmental effects, differences in aircraft systems and performance, and unknown intent information lead to prediction errors that can adversely affect AOP performance. To accommodate these uncertainties, the AOP has been enhanced to create cross-track, vertical, and along-track buffers along the predicted trajectories of both ownship and traffic aircraft. These buffers will be structured based on prediction errors noted from previous simulations such as a recent Joint Experiment between NASA Ames and Langley Research Centers and from other outside studies. Currently defined ADS-B parameters related to navigation capability, trajectory type, and path conformance will be used to support the algorithms that generate the buffers

Increased synaptic microtubules and altered synapse development in Drosophila sec8 mutants

BACKGROUND: Sec8 is highly expressed in mammalian nervous systems and has been proposed to play a role in several aspects of neural development and function, including neurite outgrowth, calcium-dependent neurotransmitter secretion, trafficking of ionotropic glutamate receptors and regulation of neuronal microtubule assembly. However, these models have never been tested in vivo. Nervous system development and function have not been described after mutation of sec8 in any organism. RESULTS: We identified lethal sec8 mutants in an unbiased forward genetic screen for mutations causing defects in development of glutamatergic Drosophila neuromuscular junctions (NMJs). The Drosophila NMJ is genetically malleable and accessible throughout development to electrophysiology and immunocytochemistry, making it ideal for examination of the sec8 mutant synaptic phenotype. We developed antibodies to Drosophila Sec8 and showed that Sec8 is abundant at the NMJ. In our sec8 null mutants, in which the sec8 gene is specifically deleted, Sec8 immunoreactivity at the NMJ is eliminated but immunoblots reveal substantial maternal contribution in the rest of the animal. Contrary to the hypothesis that Sec8 is required for neurite outgrowth or synaptic terminal growth, immunocytochemical examination revealed that sec8 mutant NMJs developed more branches and presynaptic terminals during larval development, compared to controls. Synaptic electrophysiology showed no evidence that Sec8 is required for basal neurotransmission, though glutamate receptor trafficking was mildly disrupted in sec8 mutants. The most dramatic NMJ phenotype in sec8 mutants was an increase in synaptic microtubule density, which was approximately doubled compared to controls. CONCLUSION: Sec8 is abundant in the Drosophila NMJ. Sec8 is required in vivo for regulation of synaptic microtubule formation, and (probably secondarily) regulation of synaptic growth and glutamate receptor trafficking. We did not find any evidence that Sec8 is required for basal neurotransmission

Emission-line Helium Abundances in Highly Obscured Nebulae

This paper outlines a way to determine the ICF using only infrared data. We identify four line pairs, [NeIII] 36\micron/[NeII] 12.8\micron, [NeIII]~15.6\micron /[NeII] 12.8\micron, [ArIII] 9\micron/[ArII] 6.9\micron, and [ArIII] 21\micron/[ArII] 6.9\micron, that are sensitive to the He ICF. This happens because the ions cover a wide range of ionization, the line pairs are not sensitive to electron temperature, they have similar critical densities, and are formed within the He$^+$/H$^+$ region of the nebula. We compute a very wide range of photoionization models appropriate for galactic HII regions. The models cover a wide range of densities, ionization parameters, stellar temperatures, and use continua from four very different stellar atmospheres. The results show that each line pair has a critical intensity ratio above which the He ICF is always small. Below these values the ICF depends very strongly on details of the models for three of the ratios, and so other information would be needed to determine the helium abundance. The [Ar III] 9\micron/[ArII] 6.9\micron ratio can indicate the ICF directly due to the near exact match in the critical densities of the two lines. Finally, continua predicted by the latest generation of stellar atmospheres are sufficiently hard that they routinely produce significantly negative ICFs.Comment: Accepted by PASP. Scheduled for the October 1999 issue. 11 pages, 5 figure