Optimization in the National Airspace System
The contents include: 1) Traffic Flow Management (TFM) Problem; and 2) Future ATM Concepts Evaluation Tool (FACET).
Sridhar, Banavar↗
Engineering topics
Sridhar, Banavar
Publications and source records attributed to Sridhar, Banavar.
Airspace Complexity and its Application in Air Traffic Management
The United States Air Traffic Management (ATM) system provides services to enable safe, orderly and efficient aircraft operations within the airspace over the continental United States and over large portions of the Pacific and Atlantic Oceans, and the Gulf of Mexico. It consists of two components, Air Traffic Control (ATC) and Traffic Flow Management (TFM). The ATC function ensures that the aircraft within the airspace are separated at all times while the TFM function organizes the aircraft into a flow pattern to ensure their safe and efficient movement. In order to accomplish the ATC and TFM functions, the airspace over United States is organized into 22 Air Route Traffic Control Centers (ARTCCs). The Center airspace is stratified into low-altitude, high-altitude and super-high altitude groups of Sectors. Each vertical layer is further partitioned into several horizontal Sectors. A typical ARTCC airspace is partitioned into 20 to 80 Sectors. These Sectors are the basic control units within the ATM system.
Sridhar, Banavar↗
The Taxiway Navigation and Situation Awareness (T-NASA) System
The goal of NASA's Terminal Area Productivity (TAP) Low-Visibility Landing and Surface Operations (LVLASO) subelement is to improve the efficiency of airport surface operations for commercial aircraft operating in weather conditions to Category IIIB while maintaining a high degree of safety. Currently, surface operations are one of the least technologically sophisticated components of the air transport system, being conducted in the 1990's with the same basic technology as in the 1930's. Pilots are given little or no explicit information about their current position, and routing information is limited to ATC communications and airport charts. In TAP/LVLASO, advanced technologies such as satellite navigation systems, digital data communications, advanced information presentation technology, and ground surveillance systems will be integrated into flight deck displays to enable expeditious and safe traffic movement on the airport surface. The cockpit display suite is called the T-NASA (Taxiway Navigation and Situation Awareness) System. This system has three integrated components: 1) Moving Map track-up airport surface display with own-ship, traffic and graphical route guidance 2) Scene-Linked Symbology - route/taxi information virtually projected via a Head-up Display (HUD) onto the forward scene; and, 3) 3-D Audio Ground Collision Avoidance and Navigation system - spatially-localized auditory traffic and navigation alerts. In the current paper, the design philosophy of the T-NASA system will be presented, and the T-NASA system display components described.
Foyle, David C.↗
The Development of an Electronic Aircraft Taxi Navigation Display
This paper describes the development of an electronic aircraft taxi navigation display as part of NASA's Terminal Area Productivity (TAP) Program. The impetus for the development of this specific display, and the TAP program as a whole, is the current bottleneck in surface operations experienced during low-visibility operations. Simply stated, while modern aircraft are equipped to fly and land in low-visibility conditions, they lack the related technology required to allow them to efficiently and safely navigation from the runway to the gate. Pilots under such conditions consequently taxi slower, sometimes get lost and have to stop, and occasionally collide with other aircraft. Based on a review of available display and navigation sensor technologies, and a one-year information requirements study conducted aboard several commercial aircraft flights, it was determined that an electronic aircraft taxi navigation display was the most viable option for improving the efficiency of low-visibility taxi operations. Based on flight deck observations and pilot interviews, previous map display research, other taxi map display efforts, and part-task taxi map research, an advanced taxi navigation display has been developed and is currently being tested. The taxi navigation display is presented as a head-down cockpit display and includes a track-up perspective airport surface view, taxiway, gate and runway labels, ownship position, traffic icons and collision annunciation, graphical route guidance, heading indicator, rotating compass, RVR wedge, stop bars, zoom control, and datalink message window. The development and support for each of the features will be discussed in detail. Additional information is contained in the original extended abstract.
Andre, Anthony D.↗
Closed-Loop Hybrid Flight Management Systems
The objective of our research is to develop a methodology for the modeling, design, verification of flight management systems for the next generation of airspace operations. The overall point of view taken is shown schematically by a block diagram.
Meyer, George↗
An Initial Examination of Roll-Lateral Coordination Motion Requirements in Flight Simulation
A piloted simulation that examined the effects of uncoordinated roll-lateral motion cues from a coordinated math model was conducted. The vehicle model represented a typical helicopter with satisfactory handling qualities in the roll-lateral axes. The task was a two-degree-of-freedom horizontal sidestep, where the pilot controlled lateral position through roll angle. The motion platform commands were varied via two motion control system gains. One gain reduced the ratio between platform roll angle to math model (and thus visual) roll angle. The other gain was placed on how much lateral platform movement would result from platform roll attitude in an attempt to align the apparent gravity vector vertically relative to the pilot. Gains from one to zero were examined in both axes. Thus, the true 1:1 motion case, where the motion cues matched the visual cues was evaluated. Pilots subjective ratings of motion fidelity matched well against an earlier developed motion fidelity criteria. Significant differences were noted in the fixed-base versus motion base configurations.
Schroeder, Jeffery A.↗
Natural Displays: Anticipating the Future at NASA
There are two ways in which the human factors discipline is called upon to contribute to the development of new products or systems at NASA Ames Research Center. First, there is the application of known human factors principles in the design of a product. This type of application of human factors expertise can be called upon at any time in the evolution of a system or product, with the probability of success a direct function of how early in the system development cycle that the human factors experts are called in. This dependence on timing is due to two things. First, late in the development cycle many decisions have been made that cannot be unmade, and human factors solutions by necessity take on the nature of work-arounds. Second, in many cases where highly innovative or unusual systems are being proposed, known principles are not sufficient to answer design questions. Since most projects work to deadlines, there is generally not enough time late in a project for time-consuming human factors research efforts. In fact, due to the nature of project management, intermediate deadlines often preclude significant research efforts even when the human factors effort is brought in at the beginning. Therefore, critical research, a second function of the human factors effort at NASA Ames, is needed before projects are initiated. How do we determine the necessary research?
Johnson, Walter W.↗
Helicopter Human Factors
Even under optimal conditions, helicopter flight is a most demanding form of human-machine interaction, imposing continuous manual, visual, communications, and mental demands on pilots. It is made even more challenging by small margins for error created by the close proximity of terrain in NOE flight and missions flown at night and in low visibility. Although technology advances have satisfied some current and proposed requirements, hardware solutions alone are not sufficient to ensure acceptable system performance and pilot workload. However, human factors data needed to improve the design and use of helicopters lag behind advances in sensor, display, and control technology. Thus, it is difficult for designers to consider human capabilities and limitations when making design decisions. This results in costly accidents, design mistakes, unrealistic mission requirements, excessive training costs, and challenge human adaptability. NASA, in collaboration with DOD, industry, and academia, has initiated a program of research to develop scientific data bases and design principles to improve the pilot/vehicle interface, optimize training time and cost, and maintain pilot workload and system performance at an acceptable level. Work performed at Ames, and by other research laboratories, will be reviewed to summarize the most critical helicopter human factors problems and the results of research that has been performed to: (1) Quantify/model pilots use of visual cues for vehicle control; (2) Improve pilots' performance with helmet displays of thermal imagery and night vision goggles for situation awareness and vehicle control; (3) Model the processes by which pilots encode maps and compare them to the visual scene to develop perceptually and cognitively compatible electronic map formats; (4) Evaluate the use of spatially localized auditory displays for geographical orientation, target localization, radio frequency separation; (5) Develop and flight test control/display concepts; (6) Quantify, model, predict, and improve pilots, workload-management strategies; and (7) Design computer-game trainers to reduce training time and cost.
Hart, Sandra G.↗
Prototype Videodisk-Based Part-Task Thermal Imaging Trainer
Thermal images, or infrared images, are representations of the world based on heat, instead of visible light. Research has shown that the resulting thermal image results in perceptual differences leading to difficulties in interpretation (e.g., the determination of slope angle, concavity/convexity), or increased identification latencies. A joint research project between the United States (NASA and U.S. Army) and Israel (Ministry of Defense and Israel Air Force) has resulted in the development of a prototype part-task trainer for the acquisition of perceptual skills associated with thermal imaging usage. This prototype system is videodisk-based under computer control, using recordings of thermal images. A lesson section introduces declarative knowledge, in which the basic physics and heuristics of thermal imagery are taught. An exercise section teaches procedural knowledge, with the user viewing dynamic, actual imagery, with an interactive detection/location determination task. The general philosophy and design of the trainer will be demonstrated.
Brickner, Michael S.↗
Attentional Capture by Superimposed Symbology: Boundary Conditions
We report new results from an ongoing set of experiments in which subjects view a computer-generated display consisting of a set of stationary symbols (e.g., a "HUD") superimposed on a dynamic view of a runway as it appears to the pilot during final approach. Previous work (McCann, Foyle, & Johnston, 1993) has shown that when subjects process a cueing stimulus and then identify a geometric target, performance is slower when the cue appears on the HUD and the target appears on the runway surface, compared to a control condition where the cue and target are both on the runway surface. This "shift cost" was taken as evidence that the HUD captures attention, which then has to be shifted to the "out-the-world" scene before the target can be identified. New experiments show that the shift cost is eliminated when the cue occupies a known, fixed location on the HUD. Implications for the conditions that produce attentional tunneling are discussed.
McCann, Robert S.↗
Model-Based Obstacle Detention From Image Sequences
This paper proposes a method for detecting obstacles on a runway from monocular image sequences. The surface of the runway is modeled as a plane and the model flow field corresponding to the runway is described by 8 coefficients. The set of 8 coefficients describing the initial model flow field is given by the data from Inertial Navigation System (INS). The uncertainties of this initial model flow field are estimated and used to obtain the accurate model flow field. The residual flow field after warping images by the accurate model flow field is computed by solving over determined gradient-based optical flow equations using a singular value decomposition (SVD). This SVD gives us a new insight of the uncertainties inherent in the optical flow computation. Those pixels with large residual flow vectors are considered as obstacles. Experimental results for two real image sequences are presented.
Sull, Sanghoon↗
Model Based Vision for Aircraft Position Determination
This paper investigates the use of imaging sensors to estimate the position of an aircraft with respect to the runway during landing. Passive vision techniques to estimate aircraft position during landing rely on the known runway model, images acquired by onboard imaging sensor, orientation information provided by the inertial navigation system and the position estimate provided by devices such as the global positioning system. Point features in the runway model are compared with the onboard sensor images of the features and the difference between the two is used to correct the aircraft position and orientation. In this paper the sensitivity of point features is examined as a means of determining the accuracy of such position estimation techniques. Expressions are derived for the sensitivity of image point to errors in the position and orientation of the sensor. Using these, the sensitivity of the image to aircraft position and orientation errors along a typical landing glide path is studied. A least squares technique based on this sensitivity analysis is described for the correction of position and orientation estimates. The final version of the paper will include results from the application of this analysis to real image sequences collected in flight.
Sridhar, Banavar↗
Multiple-camera/motion stereoscopy for range estimation in helicopter flight
Aiding the pilot to improve safety and reduce pilot workload by detecting obstacles and planning obstacle-free flight paths during low-altitude helicopter flight is desirable. Computer vision techniques provide an attractive method of obstacle detection and range estimation for objects within a large field of view ahead of the helicopter. Previous research has had considerable success by using an image sequence from a single moving camera to solving this problem. The major limitations of single camera approaches are that no range information can be obtained near the instantaneous direction of motion or in the absence of motion. These limitations can be overcome through the use of multiple cameras. This paper presents a hybrid motion/stereo algorithm which allows range refinement through recursive range estimation while avoiding loss of range information in the direction of travel. A feature-based approach is used to track objects between image frames. An extended Kalman filter combines knowledge of the camera motion and measurements of a feature's image location to recursively estimate the feature's range and to predict its location in future images. Performance of the algorithm will be illustrated using an image sequence, motion information, and independent range measurements from a low-altitude helicopter flight experiment.
Smith, Phillip N.↗
Multirate and event-driven Kalman filters for helicopter flight
A vision-based obstacle detection system that provides information about objects as a function of azimuth and elevation is discussed. The range map is computed using a sequence of images from a passive sensor, and an extended Kalman filter is used to estimate range to obstacles. The magnitude of the optical flow that provides measurements for each Kalman filter varies significantly over the image depending on the helicopter motion and object location. In a standard Kalman filter, the measurement update takes place at fixed intervals. It may be necessary to use a different measurement update rate in different parts of the image in order to maintain the same signal to noise ratio in the optical flow calculations. A range estimation scheme that accepts the measurement only under certain conditions is presented. The estimation results from the standard Kalman filter are compared with results from a multirate Kalman filter and an event-driven Kalman filter for a sequence of helicopter flight images.
Sridhar, Banavar↗
Electro-optical navigation for aircraft
Low altitude flight is extremely demanding on the rotorcraft pilots. This fact has motivated the research in automating various components of low altitude rotorcraft flight operations. Concurrent with the development of guidance laws, efforts are underway to develop systems for locating the terrain and the obstacles using inputs from passive electro-optical sensors such as TV cameras and infrared imagers. A passive obstacle location algorithm that uses image sequences from cameras undergoing translational and rotational motion is developed. The algorithm is in a general form and can operate in multicamera imaging environments. Performance results using an image sequence from an airborne camera are given.
Menon, P. K. A.↗
Technologies for automating rotorcraft nap-of-the-earth flight
Explore the source record for details and available documents.
Cheng, Victor H. L.↗
Scene segmentation of natural images using texture measures and back-propagation
Knowledge of the three-dimensional world is essential for many guidance and navigation applications. A sequence of images from an electro-optical sensor can be processed using optical flow algorithms to provide a sparse set of ranges as a function of azimuth and elevation. A natural way to enhance the range map is by interpolation. However, this should be undertaken with care since interpolation assumes continuity of range. The range is continuous in certain parts of the image and can jump at object boundaries. In such situations, the ability to detect homogeneous object regions by scene segmentation can be used to determine regions in the range map that can be enhanced by interpolation. The use of scalar features derived from the spatial gray-level dependence matrix for texture segmentation is explored. Thresholding of histograms of scalar texture features is done for several images to select scalar features which result in a meaningful segmentation of the images. Next, the selected scalar features are used with a neural net to automate the segmentation procedure. Back-propagation is used to train the feed forward neural network. The generalization of the network approach to subsequent images in the sequence is examined. It is shown that the use of multiple scalar features as input to the neural network result in a superior segmentation when compared with a single scalar feature. It is also shown that the scalar features, which are not useful individually, result in a good segmentation when used together. The methodology is applied to both indoor and outdoor images.
Sridhar, Banavar↗
A parallel implementation of a multisensor feature-based range-estimation method
There are many proposed vision based methods to perform obstacle detection and avoidance for autonomous or semi-autonomous vehicles. All methods, however, will require very high processing rates to achieve real time performance. A system capable of supporting autonomous helicopter navigation will need to extract obstacle information from imagery at rates varying from ten frames per second to thirty or more frames per second depending on the vehicle speed. Such a system will need to sustain billions of operations per second. To reach such high processing rates using current technology, a parallel implementation of the obstacle detection/ranging method is required. This paper describes an efficient and flexible parallel implementation of a multisensor feature-based range-estimation algorithm, targeted for helicopter flight, realized on both a distributed-memory and shared-memory parallel computer.
Suorsa, Raymond E.↗