ABSTRACT
Safety of aircraft is a major concern throughout the world. Aircraft accident is
caused as a result of mechanical/electrical failure, human error which may be as a result of
poor communication between the pilot and air traffic controller or as a result of
shortcoming of navigational aids equipment and/or error in radio communication. The air
traffic control system is a vast network of people and necessary navigational equipment that
ensures the safe operation of commercial and private aircraft throughout the world.
Successful taking off, cruising and landing of an aircraft depend on a good and reliable
flight data (Strip) which is used by Air Traffic Controller. Flight data is responsible for
separation of aircraft, prevention of collisions between aircrafts on the manoeuvring area
and maintenance of an orderly flow of air traffic. Every year, many Controllers lost their
life because of stress from the use of the existing tedious manual stripping.
Now that the air traffic control system in Aviation industry is moving towards total
radar coverage, whereby the modern aircrafts are having their own IP addresses, instrument
landing system and the control towers are networked together. With the numerous aircraft
accidents, there is a need for Internet based flight data to enhancing the performance of air
traffic controller and reduce the rate of aircraft accident. Therefore, in this research project,
a fuzzy logic model for air traffic control system is presented that is able to improve safety
of aircraft.
The model is developed and implemented using a web based application, apache as a web
server with PHP scripting language and MySQL, a relational database.
TABLE OF CONTENTS
Declaration…. …………………………………………………………………….iii
Certification…..……………………………………………………………………iv
Acknowledgement…. ……………………………………………………………..v
Table of Content…………………………………………………………………..vi
Abstract……..……………………………………………………………………..xi
CHAPTER ONE : INTRODUCTION …………..…………………………………1
1.1 Background of the study….………………………………………………..1
1.2 Research motivation……………………….……………………………….2
1.3 Research Objectives……………………….……………………………….4
1.4 Methodology……………………………….………………………………4
1.5 Contribution to Knowledge……. …………….……………………………4
1.6 Organisation of the rest of thesis….………….……………………………..4
CHAPTER TWO : LITERATURE REVIEW …………………………………… 6
2.1 Introduction…………………………………………………………………6
2.2 Rules Guiding Aircraft in Flight and on Ground…………………………24
2.3 Separation Standards and Collision Avoidance…………………………..26
2.3.1 Types of Separation………………………..……………………..26
2.4 Flight Action……………………………………………………………… 26
2.4.1 Surface Movement of Aircraft…………………………………….28
2.5 Fuzzy Logic………………………………………….……………………31
CHAPTER THREE : SYSTEM ANALYSIS AND DESIGN……..……………. 45
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Aerodrome and Approach/Radar Control Modelling ……………………………45
3.1 Area Control Model………………………………………………………56
3.2 System Design……………………………………….……………………57
3.3 System Requirement……………………………………………………… 59
3.4 Design Considerations…………………………………………………… 59
3.5 Login Page……………………………………………………………….. 60
3.6 Aerodrome and Approach Control…………………………………….….61
3.7 Area Control……………………………………………………………….65
CHAPTER FOUR : SYSTEM IMPLEMENTATION, RESULT AND
DISCUSSION ……………………………………………………………………..67
4.1 Login page.………………………………………………………………..67
4.2 Aerodrome and Approach/Radar Control…….………………………….. 68
4.3 Area Control………………………………….………………………… 71
CHAPTER FIVE : CONCLUSION AND RECOMMENDATION……. ……….73
5.1 Conclusion………….………………………………………………………73
5.2 Recommendation..…………………………………………….…………..73
5.3 Limitation of the Study ………………………………………………….. 74
5.4 Future Research Work…………………………………………………….74
REFERENCES…………………………………………………………………… 75
APPENDIX A…………………………………………………………………….79
APPENDIX B……………………………………………………………………. 81
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CHAPTER ONE
INTRODUCTION
1.1 Background of the study
Aviation domain became one of the world’s most powerful “team” with millions
and millions of dependents and aircraft shortly after the Wright brothers in 1903 made their
brief successful flight. Everyone thought that the sky was so vast there was little or no risk
for one aircraft to collide with another. However, this belief was short-lived seven years
after the Wright’s experiment, many countries realized the necessity to regulate the aviation
domain by introducing some navigation rules and some ground facilities to guide pilots
from their departure to their destination location in a safe and efficient way. This necessity
became more urgent after four mid-air collisions in 1910 and six in 1912 (National Air
Traffic Service, 2005). As a consequence of all these events and the increasing use of the
shared airspace, the International Commission for Air Navigation (ICAN) was created in
Paris in 1919. Among the main purposes of ICAN were the establishment of uniform rules
and standards for aircraft registration and identification, personnel licensing, maps and
charts, and most importantly, for the Air Traffic Control domain, establishing rules and
giving solutions for air and flying procedures.
Air traffic system world wide has experienced significant growth during the past
twenty years. This growth has resulted in substantial increases in accident and delays at
nearly every major airport. However, environmental and geographic constraints limit the
opportunities to increase system capacity to embark on building new airports or adding new
runways at existing airports. Therefore, the Nigerian Airspace Management Agency
(NAMA) and Federal Airport Authority of Nigeria (FAAN) are currently working on
introduction of Total Radar Coverage, whereby the modern aircrafts, instrument landing
system and the control tower are networked together. Successful taking off, cruising and
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landing of an aircraft depend on a good and reliable flight data (Strip) which is being used
by Air Traffic Controller (ATC). Strip is used for separation of aircraft, prevention of
collisions between aircrafts and maintenance of an orderly flow of air traffic. Many
Controllers died while in action as a result of stress from the use of existing manual strip
for controlling air traffic, now with the availability of internet, there is a need for Internet
based flight data to enhance the performance of air traffic controller and reducing the rate
of aircraft accident.
1.2 Research Motivation
In the past, there have been controversies over the cause of many aircraft accidents,
in some cases it is difficult to retrieve Black Box that contained the last conversation
between the controller and the pilot or even when retrieved, the information might have
been tampered with. For instance the controversy surrounding the cause of Boeing 737
ADC Airlines accident on October 29 , 2006 at Tunga Madaki Village near Abuja where
ninety six (96) people died including the 19th Sultan of Sokoto Alhaji Ibrahim
Muhammad Maccido, Senator Yari Gandi and Senator Maccido could not be ascertained.
The accident occurred just after taken off en route Sokoto, the Controller on duty claimed
that he informed the pilot about the bad weather condition, but the pilot insisted that he
would go. Successful take off, cruising and landing of aircraft depend on a good and
reliable Air Traffic Controller’s Fuzzy Logic model. This is being used to separate aircrafts,
prevent collisions between aircrafts and maintain an orderly flow of air traffic. However,
flight progress strip is used for Aerodrome, Approach, Radar and Area Control.
Information obtained from flight plan supplied by pilot is used by Air traffic controller to
fill strip which presently, is being manually prepared. A strip is manually cut, ruled and
filled. Strip represents an aircraft which indicates departure, arrival or en-route. Time in
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aviation industries is very crucial, in a busy aerodrome, it is possible that ten or more
aircrafts on hold may be requesting for clearance to land while five or more may be
requesting for clearance to take off and at the same time one or two en route may be
requesting for clearance to over-fly the airway, it is the responsibility of the controller on
duty to provide separation between aircrafts by taking appropriate prompt decision to avoid
collision, in such a traffic, controller may find it difficult to coordinate the traffic. Failure to
take immediate and appropriate decision may jeopardize the life of passengers on board.
Many Controllers lost their life as a result of the use of existing tedious manual Flight
Progress Strip.
Existing manual system has so many limitations, these include:
(i) manual systems lead to tedious manual works. (ii) a strip represents an aircraft,
manually searching for strip of a particular aircraft among numerous ones in the present
system is difficult and this can cause delay and consequently can lead to accident (iii) a lot
of time is consumed in entering data which is dangerous because time is crucial in aviation.
(iv) the volume of strip increases daily so it becomes difficult to manage and generating
report is very difficult in the present system.
As a result of these, there is a need to automate Flight Progress Strip in order to
ease data entry and retrieval for a particular aircraft departing or arriving. In case of aircraft
accident where black box could not be retrieved or some people concerned want to tamper
with the information obtained from the box, automatic flight data processor will be readily
available to supply useful information.
Therefore, in this thesis, a fuzzy logic model for air traffic control system is
developed that will enhance the performance of air traffic controller and reduce the rate of
aircraft accident.
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1.3 Research Objectives
The objective of this research is to develop a model to automate Air Traffic
activities and hence :
(i) expedite and maintain an orderly flow of air traffic.
(ii) prevent collision between aircrafts.
(iii) serve as a legal tender in case of air mishap.
1.4 Methodology
This research applies fuzzy expert systems to control the activities of an air traffic
controller. A web programming and database design techniques were used.
Review of related literatures were carried out. Manual methods of flight data processing
were examined.
Fuzzy expert systems bring an expert’s skill to solving a particular problem, the systems
allow parallel operations, and as a result, controllers can take many decisions at the same
time. A dynamic relational database keeps track of air traffic operations. A model was
developed and implemented using a web based application.
1.5 Contribution to Knowledge
In this research work, fuzzy expert systems is used as a tool to model flight data for
air traffic control because of its capability in bringing an expert’s skill to solve the problem
involved in the process. This allows parallel operations by the controller. Flight data that
were done manually before is now being automated to expedite an orderly flow of air
traffic. This prevents collision and reduce the consumption of fuel by aircraft and
consequently improve safety and reduce the stress of controller.
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1.6 Organization of the rest of thesis
The rest of the thesis is organised as follows: Chapter Two focuses on the review of related
literature such as the use of a flight progress strips in Aerodrome, Functions of Air traffic
controller, Navigational Aids Equipments for Instrument Flight Rules, Rules Guiding
aircraft in Flight and on Ground, Separation Standards and Collision Avoidance, Flight
Action, Avoidance of Collisions, Fuzzy expert systems, ATC simulators such as Tower
Research Simulator (TRS), and Total Airspace and Airport Modeler (TAAM) and existing
software such as Tactical Separation Assisted Flight Environment (TSAFE) invented by
Heinz Erzberger Chief Scientist for air traffic control at National Aeronautics and Space
Administration (NASA) Ames Research Center, CARATS (Configurable Airspace
Research and Analysis Tool Sharp) en route air traffic management research software by
Menon and his colleagues together with Center – Tracon Automated System (CTAS)
designed and implemented at NASA Ames Research Center. Chapter Three presents a
Model and System Design for Fuzzy Logic model for Aircraft Control System. Also
presented are System Requirement, System design and development, in which requirement
specification and design consideration, development, code design, system requirement and
testing are specified. Chapter Four discusses results obtained from the model. Finally
Chapter Five is Conclusion and Recommendation.
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