14 research outputs found

    Safe2Ditch Steer-To-Clear Development and Flight Testing

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    This paper describes a series of small unmanned aerial system (sUAS) flights performed at NASA Langley Research Center in April and May of 2019 to test a newly added Steer-to-Clear feature for the Safe2Ditch (S2D) prototype system. S2D is an autonomous crash management system for sUAS. Its function is to detect the onset of an emergency for an autonomous vehicle, and to enable that vehicle in distress to execute safe landings to avoid injuring people on the ground or damaging property. Flight tests were conducted at the City Environment Range for Testing Autonomous Integrated Navigation (CERTAIN) range at NASA Langley. Prior testing of S2D focused on rerouting to an alternate ditch site when an occupant was detected in the primary ditch site. For Steer-to-Clear testing, S2D was limited to a single ditch site option to force engagement of the Steer-to-Clear mode. The implementation of Steer-to-Clear for the flight prototype used a simple method to divide the target ditch site into four quadrants. An RC car was driven in circles in one quadrant to simulate an occupant in that ditch site. A simple implementation of Steer-to- Clear was programmed to land in the opposite quadrant to maximize distance to the occupants quadrant. A successful mission was tallied when this occurred. Out of nineteen flights, thirteen resulted in successful missions. Data logs from the flight vehicle and the RC car indicated that unsuccessful missions were due to geolocation error between the actual location of the RC car and the derived location of it by the Vision Assisted Landing component of S2D on the flight vehicle. Video data indicated that while the Vision Assisted Landing component reliably identified the location of the ditch site occupant in the image frame, the conversion of the occupants location to earth coordinates was sometimes adversely impacted by errors in sensor data needed to perform the transformation. Logged sensor data was analyzed to attempt to identify the primary error sources and their impact on the geolocation accuracy. Three trends were observed in the data evaluation phase. In one trend, errors in geolocation were relatively large at the flight vehicles cruise altitude, but reduced as the vehicle descended. This was the expected behavior and was attributed to sensor errors of the inertial measurement unit (IMU). The second trend showed distinct sinusoidal error for the entire descent that did not always reduce with altitude. The third trend showed high scatter in the data, which did not correlate well with altitude. Possible sources of observed error and compensation techniques are discussed

    Improved Throughput with Cooperating Futuristic Airspace Management Components

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    An experiment was conducted to integrate airspace management tools that would typically be confined to either the en route or the terminal airspace to explore the potential benefits of their communication to improve arrival capacity. A NAS-wide simulation was configured with a new concept component that used the information to reconfigure the terminal airspace to the capacity benefit of the airport. Reconfiguration included a dynamically expanding and contracting TRACON area and a varying number of active arrival runways, both automatically selected to accommodate predicted volume of traffic. ATL and DFW were selected for the study. Results showed significant throughput increase for scenarios that are considered to be over-capacity for current day airport configurations. During periods of sustained demand for ATL 2018, throughput increased by 26 operations per hour (30%) and average delay was reduced from 18 minutes to 8 minutes per flight when using the dynamic TRACON. Similar results were obtained for DFW with 2018 traffic levels and for ATL with 2006 traffic levels, but with lower benefits due to lower demand

    Improvement to Airport Throughput Using Intelligent Arrival Scheduling and an Expanded Planning Horizon

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    The first phase of this study investigated the amount of time a flight can be delayed or expedited within the Terminal Airspace using only speed changes. The Arrival Capacity Calculator analysis tool was used to predict the time adjustment envelope for standard descent arrivals and then for CDA arrivals. Results ranged from 0.77 to 5.38 minutes. STAR routes were configured for the ACES simulation, and a validation of the ACC results was conducted comparing the maximum predicted time adjustments to those seen in ACES. The final phase investigated full runway-to-runway trajectories using ACES. The radial distance used by the arrival scheduler was incrementally increased from 50 to 150 nautical miles (nmi). The increased Planning Horizon radii allowed the arrival scheduler to arrange, path stretch, and speed-adjust flights to more fully load the arrival stream. The average throughput for the high volume portion of the day increased from 30 aircraft per runway for the 50 nmi radius to 40 aircraft per runway for the 150 nmi radius for a traffic set representative of high volume 2018. The recommended radius for the arrival scheduler s Planning Horizon was found to be 130 nmi, which allowed more than 95% loading of the arrival stream

    Simulating Fleet Noise for Notional UAM Vehicles and Operations in New York

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    This paper presents the results of systems-level simulations using Metrosim that were conducted for notional Urban Air Mobility (UAM)-style vehicles analyzed for two different scenarios for New York (NY). UAM is an aviation industry term for passenger or cargo-carrying air transportation services, which are often automated, operating in an urban/city environment. UAM-style vehicles are expected to use vertical takeoff and landing with fixed wing cruise flight. Metrosim is a metroplex-wide route and airport planning tool that can also be used in standalone mode as a simulation tool. The scenarios described and reported in this paper were used to evaluate a fleet noise prediction capability for this tool. The work was a collaborative effort between the National Aeronautics and Space Administration (NASA), Intelligent Automation, Inc (IAI), and the Port Authority of New York and New Jersey (PANYNJ). One scenario was designed to represent an expanded air-taxi operation from existing helipads around Manhattan to the major New York airports. The other case represented a farther term vision case with commuters using personal air vehicles to hub locations just outside New York, with an air-taxi service running frequent connector trips to a few key locations inside Manhattan. For both scenarios, the trajectories created for the entire fleet were passed to the Aircraft Environmental Design Tool (AEDT) to generate Day-Night Level (DNL) noise contours for inspection. Without data for actual UAM vehicles available, surrogate AEDT empirical Noise-Power-Distance (NPD) tables used a similar sized current day helicopter as the Baseline, and a version of that same data linearly scaled as a first guess at possible UAM noise data. Details are provided for each of the two scenario configurations, and the output noise contours are presented for the Baseline and reduced noise DNL cases

    Air Traffic Simulation Technology for High-Population Metroplexes

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    IAI's MetroSim optimizes air traffic by simulating departures, arrivals, and activity in air and onthe ground in busy metroplexes, where flights impact each other at a single airport and among traffic at nearby airports. MetroSim evolved out of several NASA SBIR/STTR Awards and has since been used by NASA for flight simulation analysis. MetroSim has also been integrated with FAA and DOT technology, has produced studies for the Port Authority of New York and New Jersey, and is under development to support the Nav

    Safe2Ditch Autonomous Crash Management System for Small Unmanned Aerial Systems: Concept Definition and Flight Test Results

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    Small unmanned aerial systems (sUAS) have the potential for a large array of highly-beneficial applications. These applications are too numerous to comprehensively list, but include search and rescue, fire spotting, precision agriculture, etc. to name a few. Typically sUAS vehicles weigh less than 55 lbs and will be performing flight operations in the National Air Space (NAS). Certain sUAS applications, such as package delivery, will include operations in the close proximity of the general public. The full benefit from sUAS is contingent upon the resolution of several technological areas in order to provide an acceptable level of risk for widespread sUAS operations. Operations of sUAS vehicles pose risks to people and property on the ground as well as manned aviation. Several of the more significant sUAS technological areas include, but are not limited to: autonomous sense and avoid and deconfliction of sUAS from other sUAS and manned aircraft, communications and interfaces between the vehicle and human operators, and the overall reliability of the sUAS and constituent subsystems. While all of the technological areas listed contribute significantly to the safe execution of the sUAS flight operations, contingency or emergency systems can greatly contribute to sUAS risk mitigations to manage situations where the vehicle is in distress. The Safe2Ditch (S2D) system is an autonomous crash management system for sUAS. Its function is to enable sUAS to execute emergency landings and avoid injuring people on the ground, damaging property, and lastly preserving the sUAS and payload. A sUAS flight test effort was performed to test the integration of sub-elements of the S2D system with a representative sUAS multi-rotor

    Benefits of a unified LaSRS++ simulation for NAS-wide and high-fidelity modeling

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    The LaSRS++ high-fidelity vehicle simulation was extended in 2012 to support a NAS-wide simulation mode. Since the initial proof-of-concept, the LaSRS++ NAS-wide simulation is maturing into a research-ready tool. A primary benefit of this new capability is the consolidation of the two modeling paradigms under a single framework to save cost, facilitate iterative concept testing between the two tools, and to promote communication and model sharing between user communities at Langley. Specific benefits of each type of modeling are discussed along with the expected benefits of the unified framework. Current capability details of the LaSRS++ NAS-wide simulations are provided, including the visualization tool, live data interface, trajectory generators, terminal routing for arrivals and departures, maneuvering, re-routing, navigation, winds, and turbulence. The plan for future development is also described

    Piloted Simulation Study of the Effects of High-Lift Aerodynamics on the Takeoff Noise of a Representative High-Speed Civil Transport

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    As part of an effort between NASA and private industry to reduce airport-community noise for high-speed civil transport (HSCT) concepts, a piloted simulation study was initiated for the purpose of predicting the noise reduction benefits that could result from improved low-speed high-lift aerodynamic performance for a typical HSCT configuration during takeoff and initial climb. Flight profile and engine information from the piloted simulation were coupled with the NASA Langley Aircraft Noise Prediction Program (ANOPP) to estimate jet engine noise and to propagate the resulting source noise to ground observer stations. A baseline aircraft configuration, which also incorporated different levels of projected improvements in low-speed high-lift aerodynamic performance, was simulated to investigate effects of increased lift and lift-to-drag ratio on takeoff noise levels. Simulated takeoff flights were performed with the pilots following a specified procedure in which either a single thrust cutback was performed at selected altitudes ranging from 400 to 2000 ft, or a multiple-cutback procedure was performed where thrust was reduced by a two-step process. Results show that improved low-speed high-lift aerodynamic performance provides at least a 4 to 6 dB reduction in effective perceived noise level at the FAA downrange flyover measurement station for either cutback procedure. However, improved low-speed high-lift aerodynamic performance reduced maximum sideline noise levels only when using the multiple-cutback procedures

    Piloted Simulation Study of a Dual Thrust-Cutback Procedure for Reducing High-Speed Civil Transport Takeoff Noise Levels

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    A piloted simulation study was performed for the purpose of indicating the noise reduction benefits and piloting performance that could occur for a typical 4-engine high-Speed Civil Transport (HSCT) configuration during takeoff when a dual thrust-cutback procedure was employed with throttle operation under direct computer control. Two thrust cutbacks were employed with the first cutback performed while the vehicle was accelerating on the run-way and the second cutback performed at a distance farther downrange. Added vehicle performance improvements included the incorporation of high-lift increments into the aerodynamic database of the vehicle and the use of limited engine oversizing. Four single-stream turbine bypass engines that had no noise suppression of any kind were used with this configuration. This approach permitted establishing the additional noise suppression level that was needed to meet Federal Air Regulation Part 36 Stage 3 noise levels for subsonic commercial jet aircraft. Noise level results were calculated with the jet mixing and shock noise modules of the Aircraft Noise Prediction Program (ANOPP)

    Shadow Mode Assessment Using Realistic Technologies for the National Airspace System (SMART NAS) Test Bed Development

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    This paper is devoted to describing the development of a new NASA air traffic management simulation and testing system called the Shadow Mode Assessment using Realistic Technologies for the National Airspace System (SMART NAS) test bed. The test bed is a major activity of NASAs air traffic management research portfolio and fills important gaps in the air traffic communitys simulation and testing needs for allowing more efficient acceleration and acceptance of NextGen and far-term concepts and technologies. The test bed will allow testing and validation in a realistic environment and provide rapid near-real-time what-if capability for air traffic management and airline decision support based on comprehensive real-time data feeds. The vision, requirements of the SMART NAS test bed and the effort for developing the test bed architecture are discussed. Finally, the five-year development plan is outlined
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