Time-Based Flow Management Research Articles

Robust identification of air traffic flow patterns in Metroplex terminal areas under demand uncertainty

Multi-Airport Systems (MAS), or Metroplexes, serve air traffic demand in cities with two or more airports. Due to the spatial proximity and operational interdependency of the airports, Metroplex airspaces are characterized by high complexity, and current system structures fail to provide satisfactory utilization of the available airspace resources. In order to support system-level design and management towards increased operational efficiency in such systems, an accurate depiction of major demand patterns is a prerequisite. This paper proposes a framework for the robust identification of significant air traffic flow patterns in Metroplex systems, which is aligned with the dynamic route service policy for the effective management of Metroplex operations. We first characterize deterministic demand through a spatio-temporal clustering algorithm that takes into account changes in the traffic flows over the planning horizon. Then, in order to handle uncertainties in the demand, a Distributionally Robust Optimization (DRO) approach is proposed, which takes into account demand variations and prediction errors in a robust way to ensure the reliability of the demand identification. The DRO-based approach is applied on pre-tactical (i.e. one-day planning) as well as operational levels (i.e. 2-h rolling horizon). The framework is applied to Time Based Flow Management (TBFM) data from the New York Metroplex. The framework and results are validated by Subject Matter Experts (SMEs).

Development of Approach and Departure Aircraft Speed Profiles

Information on the suggested aircraft airspeeds can be obtained from flight manuals, but the actual airspeeds flown by an aircraft will vary based on the aircraft landing weight, airport altitude, wind conditions, and other Air-Traffic-Control related factors. The recent advent of new tools and an abundance of new, highly accurate aircraft surveillance data have enabled a reevaluation of past airspeed profile assumptions. The resulting analysis provides a stronger representation for airspeeds flown on final approach and initial departure by the aircraft types comprising a large percentage of U.S. Instrument Flight Rules operations. Furthermore, the time to fly is calculated to determine how long it takes the trailer aircraft to fly the distance to the point where the leader generates a particular portion of the wake. Although this work is performed to provide improved inputs for Recategorization Phase II analyses, the airspeed profiles derived from aircraft surveillance data will also be valuable to other Air Traffic Control applications (such as the Advanced Traffic Proximity Alert, the Interval Management-Paired Approach, Time-Based Flow Management, and the Integrated Departure Arrival Capability) that require accurate knowledge of how aircraft approach and departure airspeeds vary in actual operations.

Measuring the impact of traffic flow management on interarrival duration: An application of autoregressive conditional duration

The Federal Aviation Administration has several tools in its arsenal to manage traffic flows. However, it is very difficult to assess with certainty the impact of traffic flow management procedures such as Time-Based Flow Management (TBFM) or Traffic Management Initiatives (TMI) on airport performance because operational data are not readily available to analysts. This study uses the case of Fort Lauderdale–Hollywood International Airport (FLL) where traffic flow management procedures have been implemented to manage a reduction of airport capacity due to runway constructions. Based on an Autoregressive Conditional Duration (ACD) model, the analysis shows that the use of traffic flow management procedures contributed to reducing the volatility of interarrival duration whether separation relies on time-metering (TBFM) or distance between aircraft (TMI). The lessons learned from this case study may have important implications for airports whose available capacity is severely constrained.