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At least 163 records · Page 9

A new traffic control design method for large networks with signalized intersections

The paper presents a traffic control design technique for application to large traffic networks with signalized intersections. It is shown that the design method adopts a macroscopic viewpoint to establish a new traffic modelling procedure in which vehicle platoons are subdivided into main stream queues and turning queues. Optimization of the signal splits minimizes queue lengths in the steady state condition and improves traffic flow conditions, from the viewpoint of the traveling public. Finally, an application of the design method to a traffic network with thirty-three signalized intersections is used to demonstrate the effectiveness of the proposed technique.

Leininger, G. G.↗

A Conceptual Design of a Departure Planner Decision Aid

Terminal area Air Traffic Management handles both arriving and departing traffic. To date, research work on terminal area operations has focused primarily on the arrival flow and typically departures are taken into account only in an approximate manner. However, arrivals and departures are highly coupled processes especially in the terminal airspace, with complex interactions and sharing of the same airport resources between arrivals and departures taking place in practically every important terminal area. Therefore, the addition of automation aids for departures, possibly in co-operation with existing arrival flow automation systems, could have a profound contribution in enhancing the overall efficiency of airport operations. This paper presents the conceptual system architecture for such an automation aid, the Departure Planner (DP). This architecture can be used as a core in the development of decision-aiding systems to assist air traffic controllers in improving the performance of departure operations and optimize runway time allocation among different operations at major congested airports. The design of such systems is expected to increase the overall efficiency of terminal area operations and yield benefits for all stakeholders involved in Air Traffic Management (ATM) operations, users as well as service providers.

Anagnostakis, Ioannis↗

Application of optimization techniques to near terminal area sequencing and flow control.

Development of an arrival air-traffic management system for a single runway. Traffic is segregated throughout most of the near terminal area according to performance characteristics. Nominal approach routes for each class of aircraft are determined by an optimization procedure. In this fashion, the nominal approach routes are dependent upon and, hence, determined by the near terminal area operating capabilities of each class of aircraft. The landing order and spacing of aircraft on the common approach path are determined so that a measure of total system deviation from the nominal landing times is minimized and safety standards are met. Delay maneuvers required to satisfy sequencing needs are then carried out in a manner dependent upon the particular class of aircraft being maneuvered. Finally, results are presented to illustrate the effects of the rate of arrivals upon a one-runway system serving three different classes of aircraft employing several different sequencing strategies and measures of total system deviation.

Straeter, T. A.↗

It's time to reinvent the general aviation airplane

Current designs for general aviation airplanes have become obsolete, and avenues for major redesign must be considered. New designs should incorporate recent advances in electronics, aerodynamics, structures, materials, and propulsion. Future airplanes should be optimized to operate satisfactorily in a positive air traffic control environment, to afford safety and comfort for point-to-point transportation, and to take advantage of automated manufacturing techniques and high production rates. These requirements have broad implications for airplane design and flying qualities, leading to a concept for the Modern Equipment General Aviation (MEGA) airplane. Synergistic improvements in design, production, and operation can provide a much needed fresh start for the general aviation industry and the traveling public. In this investigation a small four place airplane is taken as the reference, although the proposed philosophy applies across the entire spectrum of general aviation.

Stengel, Robert F.↗

Fe(3): An Evaluation Tool for Low-Altitude Air Traffic Operations

The concepts of unmanned aircraft system traffic management (UTM) and urban air mobility (UAM) are introducing high-density operations in low altitude airspace in closer proximity to populated areas than conventional high-altitude air traffic. The Flexible engine for Fast-time Evaluation of Flight Environments (Fe (sup 3)) provides the capability of statistically analyzing the high-density, high-fidelity, and low-altitude traffic system under numerous scenarios, such that stake holders can study impacts of factors in the low-altitude high-density traffic system and define requirements, policies, and protocols needed to support a safe yet efficient traffic system, and even assess operational risks and optimize flight schedules without conducting infeasible and cost-prohibitive flight tests that involve a large volume of aerial vehicles. This work provides an introduction to this simulation tool including its architecture and various models involved. Its performance and sample application in UAM and UTM are also presented.

Collision Avoidance↗

Fe3: An Evaluation Tool for Low-Altitude Air Traffic Operations

The concepts of unmanned aircraft system traffic management (UTM) and urban air mobility (UAM) are introducing high-density operations in low altitude airspace in closer proximity to populated areas than conventional high-altitude air traffic. The Flexible engine for Fast-time Evaluation of Flight Environments (Fe (sup 3)) provides the capability of statistically analyzing the high-density, high-fidelity, and low-altitude traffic system under numerous scenarios, such that stake holders can study impacts of factors in the low-altitude high-density traffic system and define requirements, policies, and protocols needed to support a safe yet efficient traffic system, and even assess operational risks and optimize flight schedules without conducting infeasible and cost-prohibitive flight tests that involve a large volume of aerial vehicles. This work provides an introduction to this simulation tool including its architecture and various models involved. Its performance and sample application in UAM and UTM are also presented.

Trajectory Modeling↗

A Markov Decision Process Framework for Optimal Airport Reconfiguration

The airport runway configuration is defined as a combination set of runways for arrivals and departures used at a point during operation of the airport. An optimal configuration of these runways depends on a number of factors, including traffic demand, wind magnitude and direction, other adverse weather conditions, and noise restrictions, among others. Based on the current state of these factors and predictions of traffic demand and weather conditions, runway configuration changes are made and coordinated between tower controller, other air traffic control facilities, pilots, and ground personnel. Reconfigurations can be quite disruptive to airport operations; minimizing their frequency and scheduling them well in advance is essential for mitigating some of the added workload for controllers and pilots. Unfortunately, deciding on an appropriate time to change is challenging for human decision makers. Not only do multiple factors need to be evaluated, but the uncertainty in their forecasts must also be considered. Previous optimization methods, such as mixed linear integer programming, have been proposed. Although these methods can reason over a large set of variables, they do not systematically handle the uncertainty associated with weather movement, traffic demands, and other variables. In this work, we introduce a Markov Decision Process (MDP)-based decision making framework which can reason effectively over the inherent uncertainties and make optimal decisions on if/when to change the airport configuration. In a prototype implementation, we present a single runway with three aircraft and utilize knowledge of the forecasted wind speed and direction to determine whether to keep or change the current runway configuration. Our aim through this work is to present a framework for airport reconfiguration which can be scalable to additional aircraft, multiple runways, and various input parameters. This technique will optimize the airport reconfiguration procedure by providing a proactive approach, optimizing not just at the next optimal opportunity for a reconfiguration based on varying atmospheric and traffic conditions in the terminal airspace, but also anticipating future necessary reconfigurations. This will eliminate the inefficiencies of frequent changes currently associated with runway reconfiguration procedures.

runway reconfiguration↗

Trajectory Planning by Preserving Flexibility: Metrics and Analysis

In order to support traffic management functions, such as mitigating traffic complexity, ground and airborne systems may benefit from preserving or optimizing trajectory flexibility. To help support this hypothesis trajectory flexibility metrics have been defined in previous work to represent the trajectory robustness and adaptability to the risk of violating safety and traffic management constraints. In this paper these metrics are instantiated in the case of planning a trajectory with the heading degree of freedom. A metric estimation method is presented based on simplifying assumptions, namely discrete time and heading maneuvers. A case is analyzed to demonstrate the estimation method and its use in trajectory planning in a situation involving meeting a time constraint and avoiding loss of separation with nearby traffic. The case involves comparing path-stretch trajectories, in terms of adaptability and robustness along each, deduced from a map of estimated flexibility metrics over the solution space. The case demonstrated anecdotally that preserving flexibility may result in enhancing certain factors that contribute to traffic complexity, namely reducing proximity and confrontation.

Idris, Husni R.↗

Transforming the NAS: The Next Generation Air Traffic Control System

The next-generation air traffic control system must be designed to safely and efficiently accommodate the large growth of traffic expected in the near future. It should be sufficiently scalable to contend with the factor of 2 or more increase in demand expected by the year 2020. Analysis has shown that the current method of controlling air traffic cannot be scaled up to provide such levels of capacity. Therefore, to achieve a large increase in capacity while also giving pilots increased freedom to optimize their flight trajectories requires a fundamental change in the way air traffic is controlled. The key to achieving a factor of 2 or more increase in airspace capacity is to automate separation monitoring and control and to use an air-ground data link to send trajectories and clearances directly between ground-based and airborne systems. In addition to increasing capacity and offering greater flexibility in the selection of trajectories, this approach also has the potential to increase safety by reducing controller and pilot errors that occur in routine monitoring and voice communication tasks.

Erzberger, Heinz↗

Systems Engineering Management Plan NASA Traffic Aware Planner Integration Into P-180 Airborne Test-Bed

NASA's Traffic Aware Planner (TAP) is a cockpit decision support tool that provides aircrew with vertical and lateral flight-path optimizations with the intent of achieving significant fuel and time savings, while automatically avoiding traffic, weather, and restricted airspace conflicts. A key step towards the maturation and deployment of TAP concerned its operational evaluation in a representative flight environment. This Systems Engineering Management Plan (SEMP) addresses the test-vehicle design, systems integration, and flight-test planning for the first TAP operational flight evaluations, which were successfully completed in November 2013. The trial outcomes are documented in the Traffic Aware Planner (TAP) flight evaluation paper presented at the 14th AIAA Aviation Technology, Integration, and Operations Conference, Atlanta, GA. (AIAA-2014-2166, Maris, J. M., Haynes, M. A., Wing, D. J., Burke, K. A., Henderson, J., & Woods, S. E., 2014).

Maris, John↗

Usability Evaluation of Spot and Runway Departure Advisor (SARDA) Concept in Dallas/Fort Worth Airport Tower Simulation

Spot and Runway Departure Advisor (SARDA) is a proposed decision-support tool for air traffic control tower controllers for reducing taxi delay and optimizing the departure sequence. In the present study, the tool's usability was evaluated to ensure that its claimed performance benefits are not being realized at the cost of increasing the work burden on controllers. For the evaluation, workload ratings and questionnaire responses collected during a human-in-the-loop simulation experiment were analyzed to assess the SARDA advisories' effects on the controllers' ratings on cognitive resources (e.g., workload, spare attention) and satisfaction. The results showed that SARDA reduced the controllers' workload and increased their spare attention. It also made workload and attention levels less susceptible to the effects of increases in the traffic load. The questionnaire responses suggested that the controllers generally were satisfied with the ease of use of the tool and the objectives of the SARDA concept, but with some caution. To gain more trust from controllers, the the reasoning behind advisories may need to be made more transparent to them.

human factors↗

Weather Design Considerations for the TASAR Traffic Aware Planner

The Traffic Aware Planner (TAP) is a decision support automation tool for trajectory planning and optimization intended for use on today’s flight deck. Drawing from a variety of on- and off-board data sources, TAP employs a sophisticated trajectory optimization algorithm that provides the aircrew with fuel- and time-saving reroute recommendations that are free of known conflicts with traffic, special use airspace, and severe convective weather. As this kind of weather is a significant part of the pilot’s decision-making process while planning trajectory changes en route, a series of investigations has been conducted into the integration of weather data and associated functionality into the TAP software. This paper reviews the weather data sources and functionality that have been incorporated into TAP to date, along with experience gathered in the course of the design process.

Lewis, Timothy A.↗

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

airport surface traffic↗

Three-Dimensional Trajectory Design for Reducing Climate Impact of Trans-Atlantic Flights

The impact of aircraft emissions and contrails on the environment adds an additional aspect to aircraft trajectory optimization. This study developed a three-dimensional trajectory optimization algorithm for trans-Atlantic flights in cruise to generate aircraft trajectories that minimize environmental impacts due to CO2 emissions and contrails in the presence of winds. The climate-optimal trajectory is developed using dynamic programming that adjusts a wind-optimal aircraft heading while determining the optimal locations, altitudes and times for en-route step climbs. Flying wind-optimal routes minimize aircraft travel time, fuel burn and associated emissions during cruise while adjusting aircraft heading and en-route step climbs at the optimal locations and times minimize climate impact of contrails. This capability integrates an air traffic management simulation with aircraft fuel burn and emissions models, contrail formation and dispersion models, simplified climate response models, and a common climate metric. A study was conducted to evaluate the potential cost and benefits of flying climate-optimal routes in North Atlantic Airspace and their impacts to the Organized Track System design based on the trans-Atlantic air traffic during a day, July 12, 2012. Results show eastbound flights achieved a larger environmental benefit with less additional fuel burn than westbound flights that operated in strong headwinds that caused more additional fuel burn and aircraft emissions to avoid traversing contrails favorable regions.

climate impact of aviation↗

Branch strategies - Modeling and optimization

The authors provide a common platform for modeling different schemes for reducing the branch-delay penalty in pipelined processors as well as evaluating the associated increased instruction bandwidth. Their objective is twofold: to develop a model for different approaches to the branch problem and to help select an optimal strategy after taking into account additional i-traffic generated by branch strategies. The model presented provides a flexible tool for comparing different branch strategies in terms of the reduction it offers in average branch delay and also in terms of the associated cost of wasted instruction fetches. This additional criterion turns out to be a valuable consideration in choosing between two strategies that perform almost equally. More importantly, it provides a better insight into the expected overall system performance. Simple compiler-support-based low-implementation-cost strategies can be very effective under certain conditions. An active branch prediction scheme based on loop buffers can be as competitive as a branch-target-buffer based strategy.

Dubey, Pradeep K.↗

Optimization of Airport Runway Configuration with Forecast-Augmented Offline Reinforcement Learning

Runway configuration Management (RCM) governs the optimal utilization of runways based on variables such as traffic and meteorological conditions, making it a daunting task in air traffic management due to its dependency on volatile operational and environmental factors. This paper improves upon our previous work [1] on using offline model-free reinforcement learning for creating a Runway Configuration Assistance (RCA) decision-support tool. A novel integration of forecast data from LAMP (Localized Aviation Model Output Statistics Program) and TAF (Terminal Area Forecast) is introduced, enhancing the tool’s accuracy and also its adaptability to quick wind changes. The performance is evaluated using two major US airports, Charlotte Douglas International Airport (CLT) and Denver International Airport (DEN). To counter scalability issues presented by the addition of discrete forecast variables, we transitioned to a continuous state space model, ensuring scalability and inclusion of longer forecast data. The results of our experiments reflect significant improvements in the RCA tool’s prediction accuracy.

Sumanth Nethi↗

In-Flight Evaluation of the Traffic Aware Planner on the NASA HU-25A Guardian Aircraft

NASA’s Traffic Aware Planner (TAP) software is a research-prototype decision support tool that provides pilots with time- and fuel-saving route recommendations that optimize their current trajectory. The software runs on a first-of-a-kind system architecture onboard three aircraft in revenue service conducting operational evaluations with a major domestic airline. Therefore, significant NASA-internal testing is required prior to releasing the software to the partner airline. This paper describes a flight test plan that exercises the functionality of the TAP software in a representative operational environment, describes the system architecture developed and implemented for the NASA Langley HU-25A Guardian aircraft to support the test objectives, presents outcomes of the flight test campaign, and discusses use cases that demonstrate the value of flight testing for this activity.Research into flight path optimization of transport aircraft conducted by the National Aeronautics and SpaceAdministration (NASA) has produced an operational concept known as Traffic Aware Strategic Aircrew Requests(TASAR) [1, 2]. This near-term concept [3] provides the aircrew with a flight deck decision support tool known asthe Traffic Aware Planner (TAP). The TAP software leverages a growing number of information sources on the flightdeck to make time- and fuel-saving route optimization recommendations to the aircrew while en route. The aircrewcan then use the suggestions provided by the tool to make route change requests with a greater likelihood of acceptanceby air traffic control (ATC). Since TASAR is a concept intended for the current operational environment, it isintentionally designed to have no safety-critical impact or require any changes to current Federal AviationAdministration (FAA) rules and procedures [4, 5].The research prototype TAP system [6–8], explained further in Section III.C, continually incorporates up-to-dateaircraft state data from onboard avionics, as well as the latest position of surrounding traffic, the most recent windforecast, and the most recent convective weather forecast, in order to calculate candidate trajectory modifications thatimprove upon the current active route. These trajectories account for user-selectable objective functions [3] of reducedfuel burn, reduced flight time, or an airline-derived combination of factors known as trip cost. Previous analyses andsimulations have estimated substantial savings for airlines employing this technique within the U.S. National AirspaceSystem (NAS) [9–11]. Operational evaluations with Alaska Airlines seek to validate these projected benefits usingmeasured data while simultaneously providing benefits to the airline [12, 13].The TAP software has undergone a number of human-in-the-loop simulations [14] and flight test activities[15–17] in order to validate the operational concept, evaluate human factors considerations (e.g., workload, usability,distraction, etc.), and to assess the ability of the software to function in a representative operational environment (e.g.,connected to live avionics data, using in-flight internet connectivity, etc.). However, these simulations and flight testcampaigns did not account for the hardware architecture implemented on the three aircraft for Alaska Airlines’operational evaluations of the TAP software. Therefore, a need was identified to thoroughly test the functionality ofthe software in a similar hardware architecture to that of the partner airline’s aircraft. Information regarding testapparatus and environments used to evaluate TAP prior to testing on the HU-25A can be found in reference [18].A campaign of flight trials on a NASA aircraft, the HU-25A Guardian, was conducted to ensure that the researchprototype TAP system functions well in a configuration similar to the Alaska Airlines aircraft prior to deployment.This airborne, networked environment enables an assessment of the operational factors unique to the flight environment. Additionally, this activity evaluated the effectiveness and benefit of new TAP functionality andoperation in a relevant flight environment while allowing the rapid prototyping of new concepts and features.This paper is organized as follows: Section II discusses the details of the flight test plan, flight profiles, and theduties of personnel involved with conducting flight operations. Section III describes the test platform, avionicsequipage, and system architecture. Section IV presents a discussion of results, and Section V contains concludingremarks.

Underwood, Matthew C.↗