Search NASA⌕ Search

SEARCH · Search NASA

Results for “Trafficability”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14

The Monotonic Lagrangian Grid for Rapid Air-Traffic Evaluation

The Air Traffic Monotonic Lagrangian Grid (ATMLG) is presented as a tool to evaluate new air traffic system concepts. The model, based on an algorithm called the Monotonic Lagrangian Grid (MLG), can quickly sort, track, and update positions of many aircraft, both on the ground (at airports) and in the air. The underlying data structure is based on the MLG, which is used for sorting and ordering positions and other data needed to describe N moving bodies and their interactions. Aircraft that are close to each other in physical space are always near neighbors in the MLG data arrays, resulting in a fast nearest-neighbor interaction algorithm that scales as N. Recent upgrades to ATMLG include adding blank place-holders within the MLG data structure, which makes it possible to dynamically change the MLG size and also improves the quality of the MLG grid. Additional upgrades include adding FAA flight plan data, such as way-points and arrival and departure times from the Enhanced Traffic Management System (ETMS), and combining the MLG with the state-of-the-art strategic and tactical conflict detection and resolution algorithms from the NASA-developed Stratway software. In this paper, we present results from our early efforts to couple ATMLG with the Stratway software, and we demonstrate that it can be used to quickly simulate air traffic flow for a very large ETMS dataset.

Kaplan, Carolyn↗

Expanding Regional Airport Usage to Accommodate Increased Air Traffic Demand

Small regional airports present an underutilized source of capacity in the national air transportation system. This study sought to determine whether a 50 percent increase in national operations could be achieved by limiting demand growth at large hub airports and instead growing traffic levels at the surrounding regional airports. This demand scenario for future air traffic in the United States was generated and used as input to a 24-hour simulation of the national airspace system. Results of the demand generation process and metrics predicting the simulation results are presented, in addition to the actual simulation results. The demand generation process showed that sufficient runway capacity exists at regional airports to offload a significant portion of traffic from hub airports. Predictive metrics forecast a large reduction of delays at most major airports when demand is shifted. The simulation results then show that offloading hub traffic can significantly reduce nationwide delays.

Russell, Carl R.↗

Integrated Traffic Flow Management Decision Making

A generalized approach is proposed to support integrated traffic flow management decision making studies at both the U.S. national and regional levels. It can consider tradeoffs between alternative optimization and heuristic based models, strategic versus tactical flight controls, and system versus fleet preferences. Preliminary testing was accomplished by implementing thirteen unique traffic flow management models, which included all of the key components of the system and conducting 85, six-hour fast-time simulation experiments. These experiments considered variations in the strategic planning look-ahead times, the replanning intervals, and the types of traffic flow management control strategies. Initial testing indicates that longer strategic planning look-ahead times and re-planning intervals result in steadily decreasing levels of sector congestion for a fixed delay level. This applies when accurate estimates of the air traffic demand, airport capacities and airspace capacities are available. In general, the distribution of the delays amongst the users was found to be most equitable when scheduling flights using a heuristic scheduling algorithm, such as ration-by-distance. On the other hand, equity was the worst when using scheduling algorithms that took into account the number of seats aboard each flight. Though the scheduling algorithms were effective at alleviating sector congestion, the tactical rerouting algorithm was the primary control for avoiding en route weather hazards. Finally, the modeled levels of sector congestion, the number of weather incursions, and the total system delays, were found to be in fair agreement with the values that were operationally observed on both good and bad weather days.

Grabbe, Shon R.↗

Interaction Between Strategic and Local Traffic Flow Controls

The loosely coordinated sets of traffic flow management initiatives that are operationally implemented at the national- and local-levels have the potential to under, over, and inconsistently control flights. This study is designed to explore these interactions through fast-time simulations with an emphasis on identifying inequitable situations in which flights receive multiple uncoordinated delays. Two operationally derived scenarios were considered in which flights arriving into the Dallas/Fort Worth International Airport were first controlled at the national-level, either with a Ground Delay Program or a playbook reroute. These flights were subsequently controlled at the local level. The Traffic Management Advisor assigned them arrival scheduling delays. For the Ground Delay Program scenarios, between 51% and 53% of all arrivals experience both pre-departure delays from the Ground Delay Program and arrival scheduling delays from the Traffic Management Advisor. Of the subset of flights that received multiple delays, between 5.7% and 6.4% of the internal departures were first assigned a pre-departure delay by the Ground Delay Program, followed by a second pre-departure delay as a result of the arrival scheduling. For the playbook reroute scenario, Dallas/Fort Worth International Airport arrivals were first assigned pre-departure reroutes based on the MW_2_DALLAS playbook plan, and were subsequently assigned arrival scheduling delays by the Traffic Management Advisor. Since the airport was operating well below capacity when the playbook reroute was in effect, only 7% of the arrivals were observed to receive both rerouting and arrival scheduling delays. Findings from these initial experiments confirm field observations that Ground Delay Programs operated in conjunction with arrival scheduling can result in inequitable situations in which flights receive multiple uncoordinated delays.

Grabbe, Son↗

Factors Influencing the Decisions and Actions of Pilots and Air Traffic Controllers in Three Plausible NextGen Environments

In the current air traffic management (ATM) system, pilots and air traffic controllers have well-established roles and responsibilities: pilots fly aircraft and are concerned with energy management, fuel efficiency, and passenger comfort; controllers separate aircraft and are concerned with safety and management of traffic flows. Despite having different goals and obligations, both groups must be able to effectively communicate and interact with each other for the ATM system to work. This interaction will become even more challenging as traffic volume increases dramatically in the near future. To accommodate this increase, by 2025 the national air transportation system in the U.S. will go through a transformation that will modernize the ATM system and make it safer, more effective, and more efficient. This new system, NextGen, will change how pilots and controllers perform their tasks by incorporating advanced technologies and employing new procedures. It will also distribute responsibility between pilots, controllers and automation over such tasks as maintaining aircraft separation. The present chapter describes three plausible concepts of operations that allocate different ATM responsibilities to these groups. We describe how each concept changes the role of each operator and the types of decisions and actions performed by them.

Vu, Kim-Phuong L.↗

Software for Simulating Air Traffic

Future Air Traffic Management Concepts Evaluation Tool (FACET) is a system of software for performing computational simulations for evaluating advanced concepts of advanced air-traffic management. FACET includes a program that generates a graphical user interface plus programs and databases that implement computational models of weather, airspace, airports, navigation aids, aircraft performance, and aircraft trajectories. Examples of concepts studied by use of FACET include aircraft self-separation for free flight; prediction of air-traffic-controller workload; decision support for direct routing; integration of spacecraft-launch operations into the U.S. national airspace system; and traffic- flow-management using rerouting, metering, and ground delays. Aircraft can be modeled as flying along either flight-plan routes or great-circle routes as they climb, cruise, and descend according to their individual performance models. The FACET software is modular and is written in the Java and C programming languages. The architecture of FACET strikes a balance between flexibility and fidelity; as a consequence, FACET can be used to model systemwide airspace operations over the contiguous U.S., involving as many as 10,000 aircraft, all on a single desktop or laptop computer running any of a variety of operating systems. Two notable applications of FACET include: (1) reroute conformance monitoring algorithms that have been implemented in one of the Federal Aviation Administration s nationally deployed, real-time, operational systems; and (2) the licensing and integration of FACET with the commercially available Flight Explorer, which is an Internet- based, real-time flight-tracking system.

Sridhar, Banavar↗

Long-Range Emergency Preemption of Traffic Lights

A forwarding system could prove beneficial as an addition to an electronic communication-and-control system that automatically modifies the switching of traffic lights to give priority to emergency vehicles. A system to which the forwarding system could be added could be any of a variety of emergency traffic-signal-preemption systems: these include systems now used in some municipalities as well as advanced developmental systems described in several NASA Tech Briefs articles in recent years. Because of a variety of physical and design limitations, emergency traffic-signal- preemption systems now in use are often limited in range to only one intersection at a time: in a typical system, only the next, closest intersection is preempted for an emergency vehicle. Simulations of gridlock have shown that such systems offer minimal advantages and can even cause additional delays. In analogy to what happens in fluid dynamics, the forwarding system insures that flow at a given location is sustained by guaranteeing downstream flow along the predicted route (typically a main artery) and intersecting routes (typically, side streets). In simplest terms, the forwarding system starts by taking note of any preemption issued by the preemption system to which it has been added. The forwarding system predicts which other intersections could be encountered by the emergency vehicle downstream of the newly preempted intersection. The system then forwards preemption triggers to those intersections. Beyond affording a right of way for the emergency vehicle at every intersection that lies ahead along any likely route from the current position of the vehicle, the forwarding system also affords the benefit of clearing congested roads far ahead of the vehicle. In a metropolitan environment with heavy road traffic, forwarding of preemption triggers could greatly enhance the performance of a pre-existing preemption system.

Bachelder, Aaron↗

Evaluation of the Monotonic Lagrangian Grid and Lat-Long Grid for Air Traffic Management

The Air Traffic Monotonic Lagrangian Grid (ATMLG) is used to simulate a 24 hour period of air traffic flow in the National Airspace System (NAS). During this time period, there are 41,594 flights over the United States, and the flight plan information (departure and arrival airports and times, and waypoints along the way) are obtained from an Federal Aviation Administration (FAA) Enhanced Traffic Management System (ETMS) dataset. Two simulation procedures are tested and compared: one based on the Monotonic Lagrangian Grid (MLG), and the other based on the stationary Latitude-Longitude (Lat- Long) grid. Simulating one full day of air traffic over the United States required the following amounts of CPU time on a single processor of an SGI Altix: 88 s for the MLG method, and 163 s for the Lat-Long grid method. We present a discussion of the amount of CPU time required for each of the simulation processes (updating aircraft trajectories, sorting, conflict detection and resolution, etc.), and show that the main advantage of the MLG method is that it is a general sorting algorithm that can sort on multiple properties. We discuss how many MLG neighbors must be considered in the separation assurance procedure in order to ensure a five-mile separation buffer between aircraft, and we investigate the effect of removing waypoints from aircraft trajectories. When aircraft choose their own trajectory, there are more flights with shorter duration times and fewer CD&R maneuvers, resulting in significant fuel savings.

Kaplan, Carolyn↗

Integration of Weather Avoidance and Traffic Separation

This paper describes a dynamic convective weather avoidance concept that compensates for weather motion uncertainties; the integration of this weather avoidance concept into a prototype 4-D trajectory-based Airborne Separation Assurance System (ASAS) application; and test results from a batch (non-piloted) simulation of the integrated application with high traffic densities and a dynamic convective weather model. The weather model can simulate a number of pseudo-random hazardous weather patterns, such as slow- or fast-moving cells and opening or closing weather gaps, and also allows for modeling of onboard weather radar limitations in range and azimuth. The weather avoidance concept employs nested "core" and "avoid" polygons around convective weather cells, and the simulations assess the effectiveness of various avoid polygon sizes in the presence of different weather patterns, using traffic scenarios representing approximately two times the current traffic density in en-route airspace. Results from the simulation experiment show that the weather avoidance concept is effective over a wide range of weather patterns and cell speeds. Avoid polygons that are only 2-3 miles larger than their core polygons are sufficient to account for weather uncertainties in almost all cases, and traffic separation performance does not appear to degrade with the addition of weather polygon avoidance. Additional "lessons learned" from the batch simulation study are discussed in the paper, along with insights for improving the weather avoidance concept. Introduction

Consiglio, Maria C.↗

Evaluation of High Density Air Traffic Operations with Automation for Separation Assurance, Weather Avoidance and Schedule Conformance

In this paper we discuss the development and evaluation of our prototype technologies and procedures for far-term air traffic control operations with automation for separation assurance, weather avoidance and schedule conformance. Controller-in-the-loop simulations in the Airspace Operations Laboratory at the NASA Ames Research Center in 2010 have shown very promising results. We found the operations to provide high airspace throughput, excellent efficiency and schedule conformance. The simulation also highlighted areas for improvements: Short-term conflict situations sometimes resulted in separation violations, particularly for transitioning aircraft in complex traffic flows. The combination of heavy metering and growing weather resulted in an increased number of aircraft penetrating convective weather cells. To address these shortcomings technologies and procedures have been improved and the operations are being re-evaluated with the same scenarios. In this paper we will first describe the concept and technologies for automating separation assurance, weather avoidance, and schedule conformance. Second, the results from the 2010 simulation will be reviewed. We report human-systems integration aspects, safety and efficiency results as well as airspace throughput, workload, and operational acceptability. Next, improvements will be discussed that were made to address identified shortcomings. We conclude that, with further refinements, air traffic control operations with ground-based automated separation assurance can routinely provide currently unachievable levels of traffic throughput in the en route airspace.

Prevot, Thomas↗

Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations

Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.

Sridhar, Banavar↗

Air Traffic Management Research at NASA Ames

The Aviation Systems Division at the NASA Ames Research Center conducts leading edge research in air traffic management concepts and technologies. This overview will present concepts and simulation results for research in traffic flow management, safe and efficient airport surface operations, super density terminal area operations, separation assurance and system wide modeling and simulation. A brief review of the ongoing air traffic management technology demonstration (ATD-1) will also be presented. A panel discussion, with Mr. Davis serving as a panelist, on air traffic research will follow the briefing.

Davis, Thomas J.↗

A Perspective on NASA Ames Air Traffic Management Research

This paper describes past and present air-traffic-management research at NASA Ames Research Center. The descriptions emerge from the perspective of a technical manager who supervised the majority of this research for the last four years. Past research contributions built a foundation for calculating accurate flight trajectories to enable efficient airspace management in time. That foundation led to two predominant research activities that continue to this day - one in automatically separating aircraft and the other in optimizing traffic flows. Today s national airspace uses many of the applications resulting from research at Ames. These applications include the nationwide deployment of the Traffic Management Advisor, new procedures enabling continuous descent arrivals, cooperation with industry to permit more direct flights to downstream way-points, a surface management system in use by two cargo carriers, and software to evaluate how well flights conform to national traffic management initiatives. The paper concludes with suggestions for prioritized research in the upcoming years. These priorities include: enabling more first-look operational evaluations, improving conflict detection and resolution for climbing or descending aircraft, and focusing additional attention on the underpinning safety critical items such as a reliable datalink.

Schroeder, Jeffery A.↗

Traffic Aware Strategic Aircrew Requests (TASAR) Concept of Operations

Aircrews submit trajectory change requests to air traffic control (ATC) to better achieve the operator's preferred business trajectory. Requests are currently made with limited information and are often denied because the change is not compatible with traffic. Also, request opportunities can be overlooked due to lack of automation that advises aircrews of trajectory changes that improve flight time, fuel burn, and other objectives. The Traffic Aware Strategic Aircrew Requests (TASAR) concept leverages Automatic Dependent Surveillance-Broadcast (ADS-B) surveillance information to advise the aircrew of beneficial trajectory changes that are probed for traffic compatibility prior to issuing the request to ATC. This document describes the features, benefits, and limitations of TASAR automation hosted on an Electronic Flight Bag. TASAR has two modes: (1) auto mode that continuously assesses opportunities for improving the performance of the flight and (2) manual mode that probes trajectory changes entered by aircrews for conflicts and performance objectives. The roles and procedures of the aircrew and ATC remain unchanged under TASAR.

Henderson, Jeffrey↗

How do Air Traffic Controllers Use Automation and Tools Differently During High Demand Situations?

In a human-in-the-loop simulation, two air traffic controllers managed identical airspace while burdened with higher than average workload, and while using advanced tools and automation designed to assist with scheduling aircraft on multiple arrival flows to a single meter fix. This paper compares the strategies employed by each controller, and investigates how the controllers' strategies change while managing their airspace under more normal workload conditions and a higher workload condition. Each controller engaged in different methods of maneuvering aircraft to arrive on schedule, and adapted their strategies to cope with the increased workload in different ways. Based on the conclusions three suggestions are made: that quickly providing air traffic controllers with recommendations and information to assist with maneuvering and scheduling aircraft when burdened with increased workload will improve the air traffic controller's effectiveness, that the tools should adapt to the strategy currently employed by a controller, and that training should emphasize which traffic management strategies are most effective given specific airspace demands.

ATC↗

Designing Scenarios for Controller-in-the-Loop Air Traffic Simulations

Well prepared traffic scenarios contribute greatly to the success of controller-in-the-loop simulations. This paper describes each stage in the design process of realistic scenarios based on real-world traffic, to be used in the Airspace Operations Laboratory for simulations within the Air Traffic Management Technology Demonstration 1 effort. The steps from the initial analysis of real-world traffic, to the editing of individual aircraft records in the scenario file, until the final testing of the scenarios before the simulation conduct, are all described. The iterative nature of the design process and the various efforts necessary to reach the required fidelity, as well as the applied design strategies, challenges, and tools used during this process are also discussed.

ATD1↗

Development of Increasingly Autonomous Traffic Data Manager Using Pilot Relevancy and Ranking Data

NASA's Safe Autonomous Systems Operations (SASO) project goal is to define and safely enable all future airspace operations by justifiable and optimal autonomy for advanced air, ground, and connected capabilities. This work showcases how Increasingly Autonomous Systems (IAS) could create operational transformations beneficial to the enhancement of civil aviation safety and efficiency. One such IAS under development is the Traffic Data Manager (TDM). This concept is a prototype 'intelligent party-line' system that would declutter and parse out non-relevant air traffic, displaying only relevant air traffic to the aircrew in a digital data communications (Data Comm) environment. As an initial step, over 22,000 data points were gathered from 31 Airline Transport Pilots to train the machine learning algorithms designed to mimic human experts and expertise. The test collection used an analog of the Navigation Display. Pilots were asked to rate the relevancy of the displayed traffic using an interactive tablet application. Pilots were also asked to rank the order of importance of the information given, to better weight the variables within the algorithm. They were also asked if the information given was enough data, and more importantly the "right" data to best inform the algorithm. The paper will describe the findings and their impact to the further development of the algorithm for TDM and, in general, address the issue of how can we train supervised machine learning algorithms, critical to increasingly autonomous systems, with the knowledge and expertise of expert human pilots.

Le Vie, Lisa R.↗

A Cockpit-Based Application for Traffic Aware Trajectory Optimization

The Traffic Aware Planner (TAP) is a cockpit-based advisory tool designed to be hosted on a Class 2 Electronic Flight Bag and developed to enable the concept of Traffic Aware Strategic Aircrew Requests (TASAR). This near-term concept provides pilots with optimized route changes that reduce fuel burn or flight time, avoids interactions with known traffic, weather and restricted airspace, and may be used by the pilots to request a trajectory change from air traffic control. TAP's internal architecture and algorithms are derived from the Autonomous Operations Planner, a flight-deck automation system developed by NASA to support research into aircraft self-separation. This paper reviews the architecture, functionality and operation of TAP.

TASAR↗