Dynamic allocation and benefit assessment of NextGen flow corridors

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Abstract

A flow-based modeling approach is proposed to identify candidate airspace for high-density flow corridors. The input to the model is a set of projected user-preferred, wind optimal, and unconstrained 4D trajectories (4DTs). We compute Velocity Vector Fields (VVFs) in the 4D space-time and cluster the velocity vectors both in time and space to define flow of aircraft when they fly their preferred trajectories under high capacity conditions. A sliding time window is implemented to dynamically create and optimize corridors’ coordinates based on the changes in preferred trajectories. From this process we compute a NAS-wide corridor network that mimics the dynamics of user preferred trajectories. In operational setting, flights will have the option of joining a corridor that is closest to their optimal trajectory. Using NAS-wide simulation, we asses the benefit of corridor network by comparing efficiency gained by joining the corridor network against extra distance traveled to join the network. We show that much of the overall corridors benefit may be gained by creating very few corridors.

Highlights

► Develop a method for dynamic allocation of high volume corridors in the sky. ► Corridors are efficient and provide more airspace capacity than regular sectors. ► Compare system-wide recovered delay versus length of the corridor network. ► Show that utilizing 10 coast-to-coast corridors delivers much of the benefit in US.

Introduction

Recent advances in Communication, Navigation and Surveillance (CNS) technologies are changing operating conditions for Air Traffic Controllers (ATCs) (Corker et al., 2000, Kopardekar et al., 2009). Today, with the use of advanced data links, one controller can track an aircraft and communicate with a pilot all the way from origin to destination. Advanced navigation equipment and data links such as Airborne Separation Assurance System (ASAS), Automated Dependent Surveillance Broadcasting (ADS-B) and Cockpit Display of Traffic Information (CDTI) enables pilots to conduct self-separation (Hoekstra et al., 2000). These new features provide flexibility for airspace designers to implement new classes of airspace that are capable of accommodating multiple times more traffic than the current airspace structures allow (Kopardekar et al., 2008).

One of the new classes of airspace introduced within NextGen is Corridors-in-the-Sky (Concept of Operations for the Next Generation Air Transportation System, 2007). These are regions of airspace, generally a long and narrow pathway, in which aircraft move in a common direction or trajectory and along parallel lanes. Strictly speaking, by this definition, today’s jet routes qualify as corridors with their capacity determined based on minimum separation distances in different dimensions. Corridors can be reserved airspace within which ATC provides neither separation services nor authorization to enter. Those two functions are available only in the transitional areas, near the entry and egress points of the corridor.

The term corridor covers a range of operational concepts proposed by researchers, including High Volume Tube Shaped Sectors (HTS) (Yousefi et al., 2004), tubes (Sheth et al., 2008, Sridhar et al., 2006, Xue and Kopardekar, 2008, Hoffman and Prete, 2008), highways-in-the-sky (Alipio et al., 2003), and Dynamic Multi-track Airways (DMA) (Wing et al., 2008). Similar to NextGen, the concept of “Freeway Airspace” has been proposed as part of Europe’s “Single Sky” as isolated airspace at high altitude. This airpsace implements special rules that accommodate parts of core intercontinental traffic and parts of long haul domestic traffic in Europe (Hering, 2005).

Four of the prominent characteristics of NextGen corridors that would distinguish them from today’s airways are:

  • Allowance for multiple (parallel) lanes of traffic.

  • Capitalization on advanced CNS technology to enable changes in methods of separation, such as self-separation that potentially reduces separation standards within the corridor, or enables flying in formation.

  • Dynamic activation rules to add or remove corridor structures, as needed, throughout a day.

  • While corridors do not have to be restricted to high altitudes, they find their most natural home in high-altitude airspace.

A well-designed corridor may reduce the airspace complexity and increase airspace capacity by minimizing interference from crossing traffic. In the corridor, there might be several parallel lanes to increase its capacity, breakdown lanes to accommodate avionics failures, and passing lanes to accommodate aircraft with different performance characteristics operating in the same corridor. These features benefit the corridor users directly by enabling them to use tighter separation between aircraft safely, boosting the capacity of the corridor, and providing more flexibility in choice of slots for prospective corridor users.

Offsetting these benefits is the possibility that corridor implementation may create additional workload for controllers. In particular, coordination of entering and exiting traffic into and out of the corridors may create additional task-load for controllers in conventional sectors. Additionally, the presence of a segregated self-separated airspace in the middle of a sector may degrade a controller’s situational awareness. Human-In-The-Loop (HITL) studies are underway to study these adverse effects (Yousefi et al., 2010, Yousefi et al., 2009).

A corridor can be static or dynamic. Dynamic corridors may be shifted to avoid severe weather or to take advantage of favorable winds. Moreover, they may be utilized only during certain times of the day or in response to certain triggers. In a dynamic corridor, the 3D trajectory of its centerline is a function of time and the corridor’s length may stretch or shrink during the day. Hence, the start and end of the corridor may change during the corridor’s lifetime. The Air Navigation Service Provider (ANSP) must feed this information to the aircraft flying that corridor. For instance, whenever a large number of flights are scheduled to be traveling from New York to Chicago within an hour, a pre-defined corridor might be turned ON and used to speed their journey, then deactivated for the rest of the day.

Yousefi et al. (2004) performed statistical analysis of city-pair traffic, and showed that 33% of the total scheduled flights are operated between about 10% of the city-pairs. These city-pairs were identified as backbones of the airspace system, and it was concluded that increasing the capacity of these routes could significantly improve the total system capacity. Additionally, the authors modeled the air traffic as a fluid flow such that aircraft are the particles of the fluid. Velocity vectors for small volumes of airspace were then calculated as the resultant velocity vectors for individual aircraft. Accordingly, vector fields of the fluid velocity were created. It was proposed that the analysis of vector fields’ topology can be used to determine the geometry and location of potential corridors. In our research we extend the velocity vector field methodology proposed by Yousefi et al.

Sridhar et al. (2006) used clustering techniques using today’s traffic to group the airports in close proximity of each other and construct corridors by connecting these groups of airports via great circle routes. Xue and Kopardekar (2008) used Hough transformations to cluster the great circle routes between city-pairs into corridors, and performed analysis of NAS-wide deviation from great circle routes required to join the corridor network. Hoffman and Prete (2008) constructed a corridor network by connecting major metroplex airports. Finally, Wing et al. (2008) performed regional pooling of airports using different distance criteria, and constructed DMAs by connecting pools of airports via great-circle routes.

The previous design methodologies generally did not consider the corridors dynamics due to the changes in wind direction and convective weather. In this paper, we attempt to analyze the dynamics of corridor networks, and include those dynamics in our design methodology. Specifically, we predict the periods during which corridors should be active, or how their centerline should dynamically change in response to changes in demand profiles and weather disruptions. We develop a method that dynamically identifies high-density sections of the airspace that can benefit from new corridors. Similar to the proposal by Yousefi et al. (2004) we model the aircraft flow, group the major traffic flows based on a predetermined set of proximity parameters, and finally insert corridors along the flows’ center of gravity. Furthermore, through simulating twice-normal traffic loads in the NAS (2.0X traffic), we perform benefit assessment of corridor networks in terms of system-wide recovered delay.

The paper is organized as follows: Section 2 presents the steps and the mathematical model for designing a dynamic corridor backbone over a desired section of airspace. Section 3 discusses the cost/benefit analysis in terms of the total length of corridors implemented and the percentage of NAS-wide delay recovered. Finally, Section 4 summarizes conclusions, briefly describes the possible implementation scenarios, and indicates next research steps.

Section snippets

Corridor allocation methodology

We seek to include in our methodology the following design criteria:

  • A corridor is expected to be the principal and best route between two en route points and therefore its location should roughly align with user-preferred and wind-optimized trajectories.

  • We assume that aircraft inside corridors do not observe en route delay. This may be possible if we design corridors with sufficient lanes to accommodate the assigned traffic.

  • Technically, the more corridors we place in the system, the more delay

Results and discussions

In this section we use a sample traffic forecast and generate corridor networks using the defined processes. Furthermore, we assess the tradeoff between NAS-wide delay reduction as a result of employing efficient corridors, against the extra distance flown to join the corridor network.

Conclusion and future work

The issue of ATC workload as a critical capacity constraint is apparent. Without a revolutionary change, the ATM system will not efficiently handle the future growth in air traffic. Recent advances in avionics and data links provide capabilities for new concepts of operation. Corridors-in-the-Sky is one such concept that is proposed within the NextGen ConOps.

Objective methodologies are needed to dynamically compute the topology of the corridors. We modeled the air traffic similar to flow of a

Acknowledgments

This research was sponsored by the NextGen Airspace Program at NASA Ames Research Center under the order number NNA08BA50D. The authors wish to thank Mrs. Shannon Zelinski at NASA Ames Research Center as well as Dr. Ali Tafazzoli and Dr. Girishkumar Sabhnani of Metron Aviation Inc. for their contribution to this research. The authors also wish to thank four referees of the journal for their excellent and constructive comments.

References (20)

  • Corker, K., Gore, B., Flemming, K., Lane, J., 2000. Free flight and the context of control: experiments and modeling to...
  • Kopardekar, P., Smith, N., Lee, K., Aweiss, A., Lee, P., Prevot, T., Mercer, J., Homola, J., Mainini, M., 2009....
  • Hoekstra, J., Ruigrok, R., van Gent, R., Visser, J., Gijsbers, B., Clari, M.V., Heesbeen, W., Hilburn, B., Groeneweg,...
  • P. Kopardekar et al.

    Airspace configuration concepts for next generation air transporation

    Air Traffic Control Quarterly

    (2008)
  • Concept of Operations for the Next Generation Air Transportation System, 2007. Tech. Rep. Joint Planning and...
  • Yousefi, A., Donohue, G., Sherry, L., 2004. High volume tube shaped sectors (HTS): a network of high-capacity ribbons...
  • Sheth, K., Islam, T., Kopardekar, P., 2008. Analysis of airspace tube structures. In: 27th Digital Avionics System...
  • Sridhar, B., Grabbe, S., Sheth, K., Bilimoria, K., 2006. Initial study of tube networks for flexible airspace...
  • Xue, M., Kopardekar, P., 2008. High-capacity tube network design using the Hough transform. In: Proceeding of AIAA...
  • Hoffman, R., Prete, J., 2008. Principles of airspace tube design for dynamic airspace configuration. In: AIAA-ATIO...
There are more references available in the full text version of this article.

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