Characterization of Days Based on Analysis of National Airspace System Performance Metrics

2013 Aviation Technology, Integration, and Operations Conference

Zheng

2013

This paper is devoted to the development and evaluation of wheels-off time estimation and selection of airports without advanced automation that could benefit from wheels-off time estimation. After eliminating non-hub, small-hub, and airports with Airport Surface Detection Equipment Model-X, 29 airports were selected for further analysis. Using taxi-out delay, traffic management initiative delay counts and commercial operation counts as metrics in a multiple-metric K-Means method, these airports were organized into three groups. San Jose International, Cleveland-Hopkins International and San Francisco International are recommended for development and testing of wheels-off time estimation methods as they are suitable representatives of these three groups. The second part of the paper is devoted to wheels-off time estimation using a simulation procedure that uses kinematic models of different types of aircraft and a node-link graph to simulate surface traffic. The central idea is to integrate the aircraft equations of motion along the path in the node-link graph while complying with separation constraints and rules for waiting to cross intersections and active runways. While the intent was to apply the wheels-off estimation method to San Jose, the geometry data and the surveillance data were not received in time for this study. Therefore, modeling, simulation and tests were done with Dallas-Fort Worth traffic for which the needed data were available. Of the two approaches described in the paper, the data-driven approach, which uses historical taxi-times, can be readily applied to airports like San Jose, Cleveland and San Francisco.

Section: Selection Of Non-asde-x Airportsmentioning

confidence: 99%

“…This method is described in Ref. 10. Table 8 lists the airport grouping with composite ID constructed based on Tables 1, 2 and 3.…”

Section: Group Idmentioning

confidence: 99%

Wheels-Off Time Estimation at Non-ASDE-X Equipped Airports

2013 Aviation Technology, Integration, and Operations Conference

Zheng

2013

“…Following the K-Means algorithm described in Ref. 19, all days from 2011 were organized into groups based on traffic volume and total delay on each day, using data obtained from OPSNET. Three levels of traffic volume -low, medium, and high -were considered, as well as three levels of delay.…”

Section: B Selection Of Reference Daysmentioning

confidence: 99%

Arrival Delay Absorption using Extended Metering with Speed Control

Nikoleris

12th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference and 14th AIAA/ISSMO Multidisciplinary Analysis And

Almog

et al. 2012

Self Cite

It is often the case that due to demand-capacity imbalance at an airport, flights are assigned by air traffic controllers an amount of delay that they must absorb before their expected arrival at the airport. This paper investigates the distance needed by aircraft to absorb such delays through a speed reduction of up to 10% with respect to their nominal speed. Thirty five representative days of operations with distinct traffic volume and delay characteristics are considered for the analysis. For each day, a simulation of traffic in the NAS is conducted in the absence of any constraints on sector or airport capacity thereby resulting in delay-free aircraft landing times. Flights are assigned delays due to demandcapacity imbalances at forty major US airports, which are computed through a first-comefirst-served scheduler. Distances from the airport where flights should reduce speed in order to absorb their assigned delay are computed through an aircraft trajectory generator. Analysis focuses on jet aircraft reaching their top-of-climb point at least 250 nautical miles from their destination airport. Out of all aircraft assigned delays, on average 73% were able to absorb that delay entirely through speed control. Of these aircraft, on average 93.5% of flights were able to absorb their assigned delay by reducing speed in either the same or an adjacent Air Route Traffic Control Center (ARTCC) from their arrival airport. ARTCCs that issue the highest number of advisories for speed reduction are Washington (ZDC), Atlanta (ZTL), and Chicago (ZAU). Finally, results are also provided for the specific cases of Las Vegas (LAS) and Phoenix (PHX) airports.

“…This period is representative of high-traffic-volume, low-weather-delay days in the entire National Airspace System (NAS) and was selected using the cluster analysis described in Ref. 12. Out of a total of 50,333 flights in the dataset, 1,357 flights were destined for Atlanta.…”

Section: A Miles-in-trail Constraint At Meimentioning

confidence: 99%

Benefit Assessment of Precision Departure Release Capability Concept

Palopo

11th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference

Lee

2011

Self Cite

A Precision Departure Release Capability concept is being evaluated by both the National Aeronautics and Space Administration and the Federal Aviation Administration as part of a larger goal of improving throughput, efficiency and capacity in integrated departure, arrival and surface operations. The concept is believed to have the potential of increasing flight efficiency and throughput by avoiding missing assigned slots and minimizing speed increase or path stretch to recover the slot. The main thrust of the paper is determining the impact of early and late departures from the departure runway when an aircraft has a slot assigned either at a meter fix or at the arrival airport. Results reported in the paper are for two scenarios. The first scenario considers flights out of Dallas/Fort Worth destined for Hartsfield-Jackson International Airport in Atlanta flying through the Meridian meter-fix in the Memphis Center with miles-in-trail constraints. The second scenario considers flights destined to George Bush Intercontinental/Houston Airport with specified airport arrival rate constraint. Results show that delay reduction can be achieved by allowing reasonable speed changes in scheduling. It was determined that the traffic volume between Dallas/Fort Worth and Atlanta via the Meridian fix is low and the departures times are spread enough that large departure schedule uncertainty can be tolerated. Flights can depart early or late within 90 minutes without accruing much more delay due to miles-in-trail constraint at the Meridian fix. In the Houston scenario, 808 arrivals from 174 airports were considered. Results show that delay experienced by the 16 Dallas/Fort Worth departures is higher if initial schedules of the remaining 792 flights are kept unaltered while they are rescheduled. Analysis shows that the probability of getting the initially assigned slot back after perturbation and rescheduling decreases with increasing standard deviation of the departure delay distributions. Results show that most Houston arrivals can be expected to be on time based on the assumed zero-mean Normal departure delay distributions achievable by Precision Departure Release Capability. In the current system, airport-departure delay, which is the sum of gate-departure delay and taxi-out delay, is observed at the airports. This delay acts as a bias, which can be reduced by Precision Departure Release Capability.