Traffic Management Advisor Research Articles

Improvement of the Aircraft Traffic Management Advisor Optimization Using a Hybrid Genetic Algorithm

AbstractDuring the last decade, problems regarding the Traffic Management Advisor(TMA) has become a concerning matter. A novel hybrid Genetic Algorithm(GA) for the goal of seeking best possible alignment has been presented in this paper. This simple and yet very thorough method benefits from low computational burden, higher convergence rate and lower overall delays. Comprehensive simulations and implementation of the imbedded specially designed rearrangement operator, have shown the effectiveness of the proposed method in comparison with previous literatures and classic GA.

Experimental approach to NextGen benefits estimation: A case of single-airline Aircraft Arrival Management System

The Next Generation Air Transportation System (NextGen) embraces multiple operational and technological improvements that enable efficiencies for users and service providers. In managing the development of NextGen, the Federal Aviation Administration (FAA) is assessing initiatives and potential components of the future system. One component is software that jointly optimizes the timing of arriving traffic to streamline flight arrivals at congested airports (Aircraft Arrival Management Systems or AAMS). Since most of the proposed NextGen improvements are not yet implemented, their evaluations typically are conducted through modeling, simulation, and/or subject matter expert surveys. In contrast, this study utilizes experimental settings in a real-time operating environment to examine potential benefits of the AAMS. During the experiment, a number of system performance variables were recorded in two data collection periods: a passive period, when the system was operating without the AAMS, and an active period, when the AAMS optimized arriving traffic of a dominant airline. Due to confounding data issues, the results indicate that with only 6.5 percent of arriving traffic optimized, there are no observable improvements in the overall system performance. However, the study documents tangible benefits for optimized flights and a positive interaction effect between the FAA's Traffic Management Advisor and the AAMS.

Traffic Flow Management Impact on Delay and Fuel Consumption: an Atlanta Case Study

In 2010, the FAA investigated the use of a capability called a Traffic Management Advisor Flow Programs to control flights destined for capacity-limited airports. This study explores through fast-time simulations the impact of this new capability on Hartsfield-Jackson Atlanta International Airport arrival operations. The emphasis of this study is on examining the distribution of delays and emissions for flights included and exempted from this new capability. To determine the “best” flow rate to select when developing a Traffic Management Advisor Flow Program, a simulation-based approach is presented. This approach depends on the arrival demand, airport configuration, acceptance rate, and program goals. When the goal was to balance delays between flights included and exempt from the program, then a flow rate of 60 aircraft per hour was recommended. When the goal was to minimize overall system delays, however, then a flow rate that was 33% higher was recommended. Complementing the flow rate recommendation analysis was an activity designed to assess the environmental impacts of first scheduling Atlanta arrivals with a Traffic Management Advisor Flow Program and subsequently by the Traffic Management Advisor. A strong correlation between the Traffic Management Advisor Flow Program flow rate and the fuel burn and emissions associated with the Traffic Management Advisor delays was observed. When the Traffic Management Advisor Flow Program flow rate was increased from 54 aircraft per hour to 80 aircraft per hour, the fuel burn and emissions associated with airborne holding was found to increase by over 100%. This increase in fuel burn or emissions, in general, represents a small percent of the total fuel burn and emissions associated with the entire flight’s trajectory, and only a percent of all arrivals were assigned airborne holding. Aviation’s impact on the environment is a pressing matter, and the design of Traffic Flow Management control strategies will require considering the delays as well as the emissions resulting from them.

Predictive Weather Display in ATC: Implications for Research and Training

Two systems are central to the Next Generation Air Transportation System (NextGen) air traffic management program - Traffic Management Advisor (TMA) and En Route Automation Modernization (ERAM). One purpose of both systems is to reduce air traffic control (ATC) delay. The present study reports on an exploratory integration of convective weather, a major source of delay, into the ATC systems to allow early re-route around weather in order to reduce delay. Pseudo-controllers ran a series of simulation-based scenarios with screen capture and video collection to assess delay and safety performance. Results provide evidence that delay was reduced by early rerouting in response to convective weather predictions. Implications for training and research are discussed.

The Design of a Distributed Scheduling System for Multi-Center Time-Based Metering of Air Traffic into Congested Resources

A distributed scheduling system has been developed and implemented within NASA’s Multi-center Traffic Management Advisor (McTMA) proto-type research system. This paper describes the design and operation of the distributed scheduling system, its testing, and potential future use. The distributed scheduler is a loosely-coupled network of schedulers, each operating over short distances to deconflict aircraft merging into local points of congestion, while informing all other networked schedulers of its constraints. This architecture coordinates aircraft arrivals into congested resources by allocating delay over long distances while being robust to uncertainties in long-range estimates of arrival times. The system reduced airborne delay by 20–42% (without a comparable increase in ground delay), reduced airborne holding by 90%, reduced vectoring, and resulted in a shorter final approach in field tests at four FAA Air Route Traffic Control Centers, the Philadelphia Terminal Radar Approach Control facility, and the FAA’s Air Traffic Control System Command Center. The FAA is currently incorporating technology from the distributed scheduler into its nationwide deployment of the Traffic Management Advisor system.

Creating effective collaboration tools: Lessons from the Multi-center Traffic Management Advisor

The emphasis on network-centric operations for the next generation air traffic system presages an important opportunity for collaborative work. However, there is no clear design guidance for collaborative work across such a large and complex network of users and operators. In this paper we will describe the Multicenter Traffic Management Advisor, a system which can enable collaboration on regional air traffic problems. We will describe specific findings regarding collaborative work from a four-year testing period with six separate air traffic facilities, including a design feature we believe was crucial for improving collaborative work. This work has important implications regarding the future collaborative environment of the U.S. air traffic system as well as for collaborative work across large, complex organizations.

Operational Evaluation of Traffic Management Advisor Using Statistical Performance Metrics and Simulation Approach

The Traffic Management Advisor (TMA) is an air traffic management automation tool designed to allow more aircraft to land during the peak arrival periods by increasing the airspace capacity and minimizing delay via better scheduling, spacing, sequencing, and runway allocation of arrival traffic. This paper evaluates the TMA’s operational performance at George Bush Intercontinental airport in Houston over three daily selected rush-hour periods in the pre- and post-TMA deployments, using both the conventional and newly proposed performance metrics. The performance metrics used for the statistical analysis include: flight distances flown during transition from en route to terminal airspace, runway arrival distributions, and airport arrival traffic distributions. The results obtained from the analysis show that TMA improves the characteristics of arrival air traffic by better runway balancing, improved airport arrival throughput, and more evenly distributed airport arrivals. In addition to the statistical analysis, a model is developed to simulate aircraft transit between arrival arcs and meter fixes, queuing, and runway arrivals during a selected rush hour period in the post-TMA era.

Common Trajectory Modeling for National Airspace System: Decision Support Tools

Federal Aviation Administration air traffic operations utilize several types of Decision Support Tools (DSTs) to provide for separation and management of air traffic in the National Airspace System (NAS). Some DSTs include the Enhanced Traffic Management System (ETMS), User Request Evaluation Tool (URET), and the Center-TRACON Automation System (CTAS) Traffic Management Advisor (TMA). A common element of these DSTs is a trajectory modeling function that predicts flight status (e.g., aircraft position and altitude) over time. Modeling techniques vary among the tools because modelers were custom made for the tools, which have different operational requirements.Despite differences in operational requirements, there are some common functional components within these trajectory modeling functions. Flight plan route processing, for example, is performed similarly among the DSTs. Airspace adaptation data, such as airway definitions, are used by all DSTs. Identification of the common functional components and underlying data elements opens the potential for their consolidation as common services in a NAS infrastructure that supports all DST applications, or at least more than a single tool. Common services and data are expected to provide several benefits to subscribing DSTs, including compatible decisions, increased interoperability, and development and maintenance cost savings.Research was conducted to identify common trajectory modeling components within a selected set of NAS DSTs. This paper reports the results of the research. The paper introduces the topic of common trajectory modeling; identifies a set of trajectory modeling services, characteristics, and data found to be common across the DSTs studied; presents architectural alternatives for implementing the common services; and defines a process for selecting a common approach for implementing the services.

Throughput Effect of Time-Based Metering at Los Angeles International Airport

The throughput effect of Traffic Management Advisor (TMA) metering for Los Angeles International Airport was estimated with censored regression. Under TMA metering, traffic management coordinators receive advisories about when individual flights should be scheduled to enter the terminal area, accounting for the unimpeded time and constraints related to separation requirements and capacity constraints. Tests of TMA metering at Los Angeles began in spring 2002; mandatory use during the morning peak period started in November 2002. This analysis focuses on observed counts during periods when metering is and is not in effect and takes into account other relevant factors such as weather, visibility, and demand. Demand is used as a censoring variable that places an upper limit on the observed count. A significant increase in achievable arrival throughput under instrument conditions was found in the morning peak period, but a significant decrease was observed under visual conditions. These results are consistent with field reports, which suggest that under visual meteorological conditions, TMA was assigning unnecessary metering delays. The success of the censored regression methodology in capturing these effects suggests that it would be useful for various other applications in which the effect of some event on airport capacity must be ascertained.

Potential Information Integration of a Surface Management System Concept with Other Air Traffic Systems

NASA and FAA have identified the need for future air traffic control (ATC) automation tools to integrate with other existing or planned automation tools. Issues such as complementary decision support features (i.e. combining departure and arrival planning tools), limited display space in the FAA facilities, and the potential for performance benefits of integrating systems have driven the need to examine integration. NASA is currently leading the research and development of the Surface Management System (SMS). SMS is an information and decision support tool designed to aid ATC controllers and traffic managers in managing surface operations. This document provides an initial examination of the potential integration of the SMS concept to integrate with the Airport Surface Detection Equipment X-band (ASDE-X) and the Traffic Management Advisor (TMA).

Effect of T-TMA on Capacity and Delay at Los Angeles International Airport

Free Flight Phase 1 (FFP1) is an FAA program for improving the performance of the National Airspace System (NAS) through the deployment of advanced technologies for air traffic management. In addition to the deployment activities, FFP1 includes a significant evaluation component, which faces a significant hurdle. A plethora of factors—weather, demand, enhancements to the NAS infrastructure not related to FFP1, facility outages, and so on—may also cause changes in NAS performance. It is necessary to normalize for these factors in order to determine the effect of FFP1. Normalization procedures to isolate the impact of the implementation of an FFP1 technology—the Terminal Area Traffic Management Advisor (T-TMA)—are documented at the Southern California TRACON, where it is used for controlling traffic into Los Angeles International Airport. Two examples of normalization are presented. One examines the effect of T-TMA on airport arrival capacity, and the other looks at arrival delay. The results, although preliminary given the short time since implementation, are consistent: it appears that capacities have increased and delays decreased as a result of the deployment of the tool. Moreover, the magnitudes of the delay reductions and capacity increases are consistent.