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Survey of Coordination of En Route Air Traffic
Conflicts Resolution Modelling Methods
Huy-Ho
Abstract— The en-route conflict resolution remains a major concern for Air Traffic Management (ATM), especially in core European airspace where the current Air Traffic Control (ATC) system is approaching its capacity limits. In this paper we discuss the emphasis of the coordination of conflict resolution actions. Indeed, coordination of conflict resolution is required to reach a global solution for clusters involving many aircraft. A number of such models have already been proposed and some of them applied in practice, but there has been no cohesive discussion or comparative evaluation of these approaches. This paper presents a summary of coordination of conflict resolution approaches.
Index Terms— conflict detection and resolution, coordination of conflict resolution.
I. INTRODUCTION
he purpose of Air Traffic Management (ATM) is to enable Tairspace users to meet their schedules according to their
preferred flight profiles without compromising safety levels.
To provide safe and efficient aircraft movements, the current
approach comprises two main activities: Air Traffic Control
(ATC) and Air Traffic Flow Management (ATFM). Both ATC
and ATFM are ground based services. The ATC provides
tactical, safe separation between aircraft and between aircraft
and obstacles. The main goal of ATC is to guarantee security
and to give aircraft optimal trajectories to fly from one airport
to an other. The Air Traffic Flow Management deals with the
allocation of scarce capacity resources such as routes and
terminal operations time slots. In the USA, airport capacity is the main problem. This
problem exists also in Europe on the biggest airport. But in
Europe, and mainly in France, En Route capacity is the critical
point. There is also a problem linked with controller workload
such as monitoring workload (the monitoring of the aircraft in
the controller’s sector), resolution workload (the resolution of
conflict) and coordination workload (a task that each
controller must perform when a aircraft enters or leaves its
sector). Thereby, the tools for air traffic control system, in
particular, for conflict management as well as for ground-
based Collaborative Decision Making (CDM) are necessary to
optimize conflict resolution solutions. In other words, it aims
at increasing capacity of controller.
Huy-Hoang Nguyen is with the Heudiasyc Laboratory, UMR CNRS 6599,
University of Technology of Compiègne, Centre de Recherches de Royallieu,
BP 20 529, F-60205 Compiègne cedex, France and EUROCONTROL
Experimental Centre, Centre de Bois des Bordes, BP15, F-91222 Brétigny sur
Orge cedex, France. (e-mail: huy-hoang.nguyen@eurocontrol.int).
ang Nguy en
Additionally, the steady growth of traffic in core European
airspace could lead to complex situations where separation
standards may be infringed by several aircraft in a transitive
configuration, called clusters of potential conflicts. It is
necessary to treat large cluster of conflicts without inducing
too much the costs of maneuvering to aircraft. Costs typically
include fuel and time. Consequently, solutions to large cluster
of potential conflicts are needed. Accordingly, coordination of
conflict resolution is required to reach a global solution for
clusters involving many aircraft.
This paper provides a summary and evaluation of the
approaches that have been used to perform coordination of
conflict resolution. The objective of the paper is to point out
the advantages and disadvantages of each method.
The paper is organized as follows: Section 2 recalls quickly conflict detection and resolution. In Section 3, we review the approaches that have been proposed for the coordination problem and we discuss some of the most relevant methods.
II. CONFLICT DETECTION &RESOLUTION (CD&R)
The conflict detection and resolution has been a major topic
in ATM research. The air traffic conflict detection and
resolution process consists of several tasks to ensure
separation or avoid collisions depending on the scope of the
system. Firstly, based on the information available, future
position can then be estimated and potential conflicts can be
predicted.
Conflict detection is based on the estimation of future
vehicle position and through the application of predefined
metrics on the situation in order to decide whether or not a
conflict is present. This metric may include a sole parameter
(e.g., distance) or may be a combination of several parameters
(e.g., distance, time and maneuvering cost). After the detection
of a conflict, a conflict resolution phase requires appropriate
maneuver action and information distribution to all aircraft
involved in the conflict.
Following the literature research, an important number of
different modeling approaches (more than 60 methods [1])
have been applied in the past for conflict detection and
resolution in aerospace. These models include a wide variety
of techniques from varying viewpoints, but are all intended to
provide an analytical basis for designing and evaluating
conflict detection and resolution systems.
A. Conflict Detection
In order to ensure safety of aircraft traffic operations,
adequate separation must be maintained. A conflict occurs
1
when an aircraft’s protected zone is violated. The protected
zone is currently defined by en route ATC standards as a
circular zone of 5 nautical mile radius and a height of 2000 ft
altitude (-1000 ft to +1000ft). In other words, a conflict
between two aircraft is called effective if at some instant of
time, the minimal distance between these two aircraft called
Closest Point of Approach (CPA) is inferior to the minimal
separation standard (see Figure 1). The conflict detection phase, permits to detect conflicts only
with aircraft for which an intrusion of the protected zone takes
place in the near future, which is defined by using a fixed
look-ahead time for T minutes [2]. A new conflict is detected
when an intrusion of the protected zone is predicted, and the
time of this intrusion is within the look-ahead time. The
conflict detection uses the current state (position and altitude)
and trend vector (ground speed, track and vertical speed) to
Aircraft 1 Aircraft 2
Figure 1. A Conflict
detect conflicts. For a global resolution of case of more than two aircraft
simultaneously in conflicts, clusters of aircraft involved in
these conflicts will be determined and identified during the
look-ahead time. Recall that a cluster [3] is the transitive
closure on all aircraft pairs involved in a conflict during the
look-ahead time; that mean if A conflicts with B, and B
conflicts with both A and C, then the cluster consists of A, B
and C (see Figure 2).
B. Conflict Resolution
Once a conflict is detected it must also be resolved.
Generally, a conflict situation will be resolved by maneuvering
horizontally (heading change) or maneuvering vertically
(altitude change) or speed change of aircraft. Over the years,
various methods for resolving conflict situations have been
proposed. Some methods use force field techniques, others use
genetic algorithms, rule-based methods, or optimization
techniques. Kuchar and Yang [1] have also given an overview
of various approaches to conflict detection and resolution
problem. Force field approaches model each aircraft as a changed
The protected zone is also often referred to as Protected Airspace Zone,
which is a definition that originates from Radio Technical Commission for
Aeronautics (RTCA)
A C
B
Figure 2. Cluster of three aircraft involving in conflicts {A, B, C}
particle and use modified electrostatic equations to determine
resolution maneuvers. The repulsive forces between aircraft
are used to define the maneuver each performs to avoid a
collision [4], [7]. Optimized conflict resolution can involve a rule-based
decision [5], [6] or determining which of several avoidance
options minimizes a given cost function. The Traffic Alert and
Collision Avoidance System (TCAS), for example, searches
through a set of potential climb or descend maneuvers and
chooses the least-aggressive maneuver that still provides
adequate protection. Algorithms for resolving three-
dimensional conflicts involving multiple aircraft are presented
in [21]. These algorithms are based on trajectory optimization
methods and provide resolution actions that minimize a certain
cost function. Krozel et al. [14] have used an approach based
on optimal control theory (OCT). They have developed an
algorithm for the resolution of conflicts involving two aircraft.
This algorithm is based on the maximization of the inter-
aircraft distance at the Point of Closest Approach. Game
theory (Game) is used for conflict resolution by Tomlin et al.
[18]. Recently, Nicolas Durand [3] describes a mathematical
programming model using a heuristic method based on genetic
algorithms (GA) to optimally resolve conflict whereby the
global optimization function aims at minimizing the overall
cost incurred.
III. THE COORDINATION PROBLEM
En Route capacity is a problem mainly in Europe. Airspace
is divided in control sectors, each sector being managed by
two air traffic controllers. However, the capacity of a sector is
limited. A controller can not handle more than a certain
number of aircraft in its sector. Additionally, as air traffic
keeps increasing, a controller must be able to manage clusters
of conflicts. And then, a global solution to clusters involving
many aircraft in conflicts, more than two aircraft, is needed.
Consequently, the coordination problem of conflict resolution
appears and must be solved.
REFERENCES
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[2] M.S.V. V. Clari, R.C.J. Ruigrok, J.M. Hoekstra and H.G. Visser, “Cost-Benefit Study of Free Flight With Airborne Separation Assurance”, Air Traffic Control Quarterly, Vol. 9 (4) pp. 287-309, 2001.
[3] N. Durand, . Optimisation des Trajectoires pour la Résolution de Conflits En-Route ., Ph.D Thesis, INPT, Toulouse, France 1996.
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TERMINOLOGY AND ABBREVIATIONS
ADS-B Automatic Dependent Surveillance - Broadcast ATC Air Traffic Control ATM Air Traffic Management ATFM Air Traffic Flow Management CDM Collaborative Decision Making CD&R Conflict Detection and Resolution CPA Closest Point of Approach DAI Distributed Artificial Intelligence EFR Extended Flight Rules FREER Free-Route Experimental Encounter Resolution GA Genetic Algorithms OCT Optimal Control Theory RTCA Radio Technical Commission for Aeronautics TCAS Traffic Alert and Collision Avoidance System VFR Visual Flight Rules
BIOGRAPHY
Huy-Hoang Nguyen obtained an Engineering degree in Computer Science
from the Polytechnic University of Ho Chi Minh City, a Master degree in
Computer Science from the Institut de la Francophonie pour l’Informatique,
and is currently a Ph.D. candidate at the University of Technology of
Compiègne, France. His interests include operations research, and in
particular, scheduling and optimization problems.
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