ENRI Int. Workshop on ATM/CNS. Tokyo, Japan. (EIWAC 2010)!"#$%%&'()(*+,-,-./0(,1(23(/+0$-24-5426()5+/,+-(703-0+08(96,:(;232<0=03-(!"#$%&'()*)+'

E. Rehwald*, P. Hecker*, +S. Marx**, K. Nachtigall**, K. Schwenteck****Institute of Flight GuidanceTechnische Universität Braunschweig
Braunschweig, Germany[e.rehwald | p.hecker]@tu-bs.de**Institute of Logistics and Aviation, Chair of Traffic Flow Science
Technische Universität Dresden
Dresden, Germany[Steffen.Marx | Karl.Nachtigall]@tu-dresden.de***Department Research and Development
DFS GmbH – German Air Navigation Services
Langen, Germany
katharina.schwenteck@dfs.de
Abstract: As hub airports become larger and larger, it is vital that available runway capacity is used optimally to prevent
them turning into air traffic bottlenecks. This paper presents the concept and technical background of the Cooperative Local
Resource Planner (CLOU), which has been developed as a prototype to assist in “airport-centered flow management”. An
overview of the working principle of CLOU is given. CLOU provides a proposal of the optimal runway-use strategy andsupports the decision-making between Tower supervisors and Approach supervisors. Furthermore, an insight into the usedflow management algorithm Flow Manager (FMAN) will be addressed. Among others, the implementation concept, thelinear optimization model, and program components are described. Finally, results of validation of the CLOU-FMANcluster will be presented. An outlook shows the planned developments being objected at the further improvement of theusability of the prototype.
Keywords: airport centered flow management, CLOU, air traffic managementthat capacity bottlenecks will remain an issue, at least at
traffic peaks (compare [4]).

1. INTRODUCTION

In order to achieve and support an optimal runway-use,a prototype of a Flow Management System as a
Cooperative Local Resource Planner (CLOU) has beendeveloped at the German Aeronautical Research
Program sponsored by the Federal Ministry of
Economics and Technology of the German Government.
DFS GmbH – German Air Navigation Services – acts asclient. Research fellows are the Institute of Flight
Guidance, Technische Universität Braunschweig, andInstitute of Logistics and Aviation, Chair of Traffic
Flow Science, Technische Universität Dresden. The
development takes place for Frankfurt Airport (EDDF)
and Munich Airport (EDDM).

Nowadays the European central hub airports often
operate at their capacity limits (compare [1] and [2]).
More and more, they are becoming the bottlenecks of
the air transport network. Even today, a small incident(which might either be a reduction of available capacity
or a shift in demand) at a hub airport can cause hugedelays and adversely impact operating efficiency. These
impacts are not limited to the operations of a single
airport, but can negatively affect the European airspacein terms of a “reactionary delay” (compare [3]).
Expanding a hub airport often results in complex
runway systems, with complex interdependencies
between the traffic on the runways. These
interdependencies result either from mixed-mode
operations or from interactions with the adjacent
airspace. Despite such expansions, it can be assumed

CLOU provides suggestions for the chronology of
runway-use strategies based on demand and capacity
prognoses. The results are represented on an HMI.

335

E.Rehwald, P. Hecker, S. Marx, K. Nachtigall, K. Schwenteck
In addition to the underlying idea behind the concept offlow management of complex runway systems, thispaper also presents the technical background for
implementing such a supporting tool.
2. CLASSIFICATION
The general concept of “balancing of demand andcapacity” is not new at all. The Central Flow
Management Unit (CFMU) by Eurocontrol aims to
avoid overload within en-route sectors. From it, the
CFMU is a pre-tactical network planning system withno special focus on airports. Flights are assigned withslots but no update is carried out during traffic handling.

Fig. 1: Phases of balancing demand and capacity

CLOU extracts flight information of the Stanly_CDM
system, as well as from INFO+ (via CAPMAN and only
at Frankfurt Airport).

However, Arrival Manager (AMAN) and Departure
Manager (DMAN) are tactical local systems,
concentrated on minimizing separation, as well as on
the coordination between air traffic controllers. Thesesystems are only arrival- and departure-oriented,
respectively.

3.2 Runway-use strategy
At airports with a multi-runway system, it is usuallypossible to handle flights over different runways.
However, as a rule, all departures with the sameStandard Instrument Departure route (SID) leave fromthe same runway and all arrivals coming from the sameStandard Terminal Arrival Route (STAR) touch downon the same runway, since non-systematic runway
assignment can quickly result in confusing situations in
the airspace and increased workload for the controller.

Concerning an airport the main difference between pretactical and tactical planning is the increasing accuracyof the boundary conditions and hence improved
planning quality.
CLOU fills a gap both between pre-tactical network andtactical local systems (as shown in Fig. 1), as well as inrespect of coordination of the interaction between inand outbound traffic at an aerodrome. It distributes thedemand among the available runways and assigns
priorities between in- and outbound traffic. By keeping
the system updated with the newest traffic information,
CLOU ensures a permanent ongoing balancing of
demand and capacity.

Unfortunately, this may mean that one runway isoverloaded, while there is unused spare capacity on
another one. A better balance of demand and capacity
can be achieved by shifting departures or arrivals among
runways, as well as by prioritization.
Prioritization defines the ratio between in- and outboundtraffic, which is performed on a runway. An operation
procedure defines the flow of traffic handling at the
runway system with capacity ratios both between inand outbound, as well as between runways. Operation
procedures could be demand-dependent or weatherdependent (for example CAT II and CAT III condition)and exist for all possible operation directions. Operation
procedure and operation direction make up the runwayuse strategy.

3. WORKING PRINCIPLE
The purpose of CLOU is to optimize the traffic flow ofan airport’s runway system in order to minimize delay
and increase punctuality. These aims will be achievedby providing an optimized runway-use strategy, thepoint in time to change strategy, and target time
management. Furthermore, CLOU supports coordinateddecision-making between Tower and Approach as
regards the prioritization of both arrival and departure
traffic.

CLOU provides suggestions for optimal runway-use
strategy and the point in time to change strategy (except
the point in time to change an operation direction, thiswill be done in further work). This result will bepresented at Tower and Approach among other things.

3.1 Input data
The results of CLOU are based on demand and capacity
forecast.

3.3 Decision-making support
The supervisors on duty take the decision to relocate an
operation procedure based on a personal assessment of
the situation. However, as a rule, this decision is not thattrivial. An assessment must be made as to whether any
resulting delay from new operation procedure is indeed
less than the delay from using the previous operation
procedure. Furthermore, shifting departures or arrivals

Only at Frankfurt Airport capacity information isdelivered via Capacity Manager (CAPMAN) by
Fraport AG, which calculates and forecasts the available
airport capacity. In case of unavailable CAPMAN,
default values are used. Air traffic controller can modify
all capacity values.

336

ENRI Int. Workshop on ATM/CNS. Tokyo, Japan. (EIWAC 2010)
requires a lead-time up to one hour (depends on airport
conditions). A change of prioritization can be performed
faster, usually.
The decision-making process is further complicated by
the necessary negotiations between Tower supervisors
and Approach supervisors. Naturally, Tower supervisorsshow the tendency to focus on departures during
departure peaks, whereas Approach supervisors trend toprioritize arrivals. Currently, there is no system
available to support supervisors in their decisionmaking process.
From it CLOU supports coordinated decision-making
between Tower and Approach as regards theprioritization of both arrival and departure traffic withthe help of visualization of the optimal runway-use
strategy and different decision criteria like runway
workload, caused delay, and delay improvement(compare [5]).
3.4 Target times management
Target times represent a binding time, which have tocomply with those involved, as for instance air traffic
controller or pilots. In case of an unpredictable failure,target times need to be updated. Reliable planning of
departure and arrival times is essential for the future 4D trajectory management since beginning and end of a
trajectory are defined by these target times.

Fig. 2: Schematic view of FMAN

is connected to the CLOU system by a databaseinterface. All interaction between CLOU and FMAN
works within this database interface.
FMAN has two optimization program parts: BVOpti to
optimize the use of operation procedures andFlowLPOpti to optimize target times management andrunway allocation (as shown in Fig. 2). The CapNet is a
capacity network, which describes the capacity usage ofthe underlying airport.

For every flight CLOU generates a target time, tominimize delay and increase punctuality. Due to the factthat CLOU influences arrivals starting at departure
airport, target times will be useful with a new air traffic
management infrastructure given in SESAR.

4.1 CapNet Model
Overall airport capacity is usually characterized by threelimiting bounds, the maximum number Amax ofarrivals, the maximum number Dmax for departures anda bound for the number of total movements with
A + D ! tot (compare Fig. 3).

In order to be able to use CLOU without SESAR,
CLOU points out flow optimized target times, whichrefer to the Terminal Maneuvering Area (TMA), as well
as a natural result (first-come-first-serve solution basedon optimal runway-use strategy).

Airspace capacity must be carefully distributed among
the runway system and between arriving and departing
streams. To do this, FMAN uses a network, which iscalled capacity resource counter network. Each node

3.5 Cycle of planning
Every five minutes CLOU performs a planning to takeactual, updated flight information into account. This
cycle can only be interrupted by a manually input.
When received an input, CLOU restarts a planning
automatically. After a planning all CLOU HMI (Human
Machine Interfaces, compare [5]) will be updated.
CLOU will run in parallel with the other systems,
without the need for extra inputs from the air traffic
controller.
4. TECHNICAL BACKGROUND
The Flow Manager (FMAN) represents the core of
CLOU. It is an independent optimization kernel fromthe pre-tactical planning system. This part describes thesystemic modeling of FMAN in CLOU context. FMAN

Fig. 3: Capacity limits of an airport337

E.Rehwald, P. Hecker, S. Marx, K. Nachtigall, K. Schwenteck!# 1, if flight f takes route R with target time T %#x Rf ,T = "&0, else#$#'(1)

To define 'counter' capacity appropriately time
discretization is applied, for example time is divided
into a partition of periods I1, …, In at which for each an
integer valued capacity c(Ij) !! is defined. Using theprevious explained time transformation 'calculated time
until', the left hand of the sum in (2) counts all flights,
which are planned to use capacity resource r during thetime period Ij.

$

x Rf ,T ! c jr"R#ctu fj ,r (T )"I j(2)

This load number is limited by the capacity cj. The
collection of all flow constraints (including all different
counters) is denoted by the set FC and indexed by
j ! FC .

Fig. 4: FMAN capacity network for the upcoming runway layout at
Frankfurt Airport

The cost coefficients ! Rf (T ) define the costs forscheduling flight f with target time T on route R. Note,that this general model allows arbitrary complex costfunction.

represents a partial amount of capacity, which isallowed to be used by only departures, only arrivals, orboth types of flights. The task of each such node is
twofold: on the one hand it has to control, that only
flights of the correct type (arrivals and/or departures)are allowed to use this capacity resource and on theother hand it has a counter function for watching thelimited capacity, which is distributed over time.

After operation mode optimization the optimization of
the target times starts for all flights. The basic models
following the LP Model in (3).

totalcost = # ! Rf (T )x Rf ,T " min( f ,T ,R)(3)(3) subjects to (a), (b), and (c).

Each flight allocates capacity by using a certain route orpath through this network (compare Fig. 4 as an
example for the upcoming runway layout at Frankfurt
Airport). This path starts at the source node, which isthe counter for the total airport movements (C-Total)
and terminates at one of the possible sink nodes in the
network. For departing flights, the definition of thesinks is done by significant waypoints of the different
departing routes within the airport surrounding area. By
differentiating the permeability of the counter nodes by
the departure destination directions, this network modelis flexible enough to cover operational rules used inpractice.

!f " F

$

( )

( )

T "# f ,R"R f!j " FC$( )x Rf ,T = 1(a)x Rf ,T # c j(b)r"R,ctu fj ,r T "I j

{ }x Rf ,T ! 0,1(c)

Constraints of type (a) guarantee, that each flight will beassigned with exactly one resource route R and one
target time T. The inequalities (b) define the capacity
constraints, which allow a maximum number cj of
movements for each time period and each resource
counter j. The left hand sum of (b) counts the number offlights, which allocate capacity during the consideredtime period. Subject (c) defines the binary variable xRf,T.
The function !Rf (T) represents the cost function of
CLOU-FMAN-cluster and contains various functions in
part.

4.2 Operation procedure optimization
The first optimization module of FMAN tries to find thebest operation procedure with respect to total delay.
Demand depending operation procedures must be
maintained for at least 40 minutes so that the proposal isrealizable for the controllers. The optimization task issolved by a dynamic program approach and finds an
optimal configuration of operating procedures.
4.3 Flow Optimization
For the flow optimization time- and route-indexedbinary decision variables are used as in (1).

4338

ENRI Int. Workshop on ATM/CNS. Tokyo, Japan. (EIWAC 2010)
5. VALIDATION

arise between in- and outbound traffic. As aconsequence, new operation procedures need to
implemented and validated.

Since 2007 CLOU is running in shadow mode at the
research center of the DFS GmbH to evaluate and to
improve the airport centered flow management system.

From the controllers point of view the CAPMANCLOU-coupling has a high potential as a supporting
tool for the traffic handling on the upcoming runway
system.

In September 2008, in June 2009, and in July 2010 tests
were carried out within the operational environment ofFrankfurt Airport. Further field tests are scheduled. Oneof the aims of the field tests is to allow supervisors ofTower and Approach to evaluate the usability of CLOU
in an operational environment. Furthermore, it hasdetermined additional requirements that are still lacking
from the supervisors’ point of view.

Likewise, an adaption to the upcoming runway layout at
Munich Airport is envisaged.
7.2 Use by another stakeholders
Particularly in the case of major problems in traffic
handling (reduced capacity or shift in demand), airlines
and airports will be better informed about the effects ofsuch disturbances with regard to delay and punctuality.
They will thus be in a position to plan their processes(aircraft turnarounds, parking positions, etc.) withlonger lead times in a proactive instead of a reactive
manner.

Presenting target times and single flight information has
been faded from the spotlight. Focus has been put to thesuggestion of the operation procedure. Due to the factthat CLOU is a prototype, all supervisors and air traffic
controller were asked to have a look at CLOU during
field tests and review the results with their own
expertise. From it, they are free to follow the suggestionof runway-use strategy and to prove it.

7.3 Coupling of AMAN/DMAN
Combining the systems CLOU and the sequenceoriented planning of AMAN and DMAN can further
optimize traffic handling. As a basis for the AMAN
flow calculation CLOU can predefine an amount ofarrivals for a certain time interval, which takes into
account the departure demand. Furthermore the pretactical operation procedure optimization can be input
for the DMAN. The exact evaluation of the tacticaltarget times remains in the responsibility as AMAN and
DMAN, respectively.

6. CONCLUSION
All in all, CLOU is an airport-centered flow
management system, which can detect capacity
bottlenecks at hub airports in a timely fashion, allowing
to take corrective action much earlier than at present.
This means that not only the airport that uses CLOU
profits from the system, the situation in the surrounding
airspace is relieved as well.

7.4 Operation direction change
CLOU focus can be up to six hours. In this time
operation direction changes are possible. Currently
FMAN optimizes traffic only by using the current
operation direction for the whole focus. In the case of achange during the current CLOU focus FMAN shall
optimize including this operation direction change.

The CLOU interface informs the controller about the
future air traffic situation and about a possible solution
for the runway- use strategy. Based on this information,
Tower and Approach could agree on further procedures.
Field tests offer the possibility to get a first validation
by air traffic controllers during operations. Furthermore,
air traffic controllers are able to voice constructive
criticism and make further suggestions concerning thefunctions of CLOU.

The problem can be described as follows (as shown in
Fig. 5):

7. OUTLOOKOn the basis of the runway-related demand and capacity
forecasts, further applications of CLOU will be
developed both within the framework of the German
Aeronautical Research Program and the SESAR
initiative. These include: use by another stakeholders,
coupling of AMAN/DMAN, and dynamic operation
direction change.
7.1 Modulation of complex runway layouts
Due to the upcoming runway layout at Frankfurt Airport
CLOU needs to be adapt to the new infrastructure andtopology. Thereof, new complex interdependencies•

Between tS and tE two operation directions
OD_A and OD_B are predicted.

•

Between tC,S and tC,E the operation directionchange is necessary.

•

The best time tC,O to change operation direction
relating to inducing delay is unknown.

Fig. 5: Description of an operation direction change

5339

E.Rehwald, P. Hecker, S. Marx, K. Nachtigall, K. Schwenteck[2] Eurocontrol Statfor, “Medium-Term Forecast –Flight Movements 2008-2014”, Vol. 1, February
2008[3] Eurocontrol Statfor, “Eurocontrol Trends in Air

Traffic, A Matter of Time: Air Traffic Delay inEurope”, Vol. 2, September 2007

Fig. 6: FMAN optimization depending on the operation direction[4] Kaufhold, R., “TE im Fokus”, edition 1/2008, “Ab-schluss des Vorhabens Kooperatives Air Traffic
Management“, 2008, p.16-18

For example at the Frankfurt Airport the selection ofoperation direction depends mainly on the tailwind
component at the parallel runway system. According toairport specific regulations operation direction 25 isusable until a five knots tailwind component, then it
must be changed to operation direction 07 (as shown in
Fig. 6).

[5] Rehwald, E., Hecker, P., Kaufhold, R.,“Operational Evaluation of an Airport Centered
Flow Management”, 4th International Conference
on Research in Air Transportation, Budapest, 2010

The idea to optimize the best time of operation directionchange tC,O is a combination with the operation
procedure optimization.

9. COPYRIGHTThe authors confirm that they, and/or their company or
institution, hold copyright of all original material
included in their paper. They also confirm they haveobtained permission, from the copyright holder of any
third party material included in their paper, to publish it
as part of their paper. The authors grant full permission
for the publication and distribution of their paper as partof the EIWAC2010 proceedings or as individual
offprints from the proceedings.

8. REFERENCES[1] DFS Deutsche Flugsicherung GmbH , “AirTransport in Germany – mobility Report 2007”,“Luftverkehr in Deutschland – Mobilitätsbericht
2007”, 2008

6340