THE INTEGRATION OF CLOSE RANGE PHOTOGRAMMETRY AND

DATABASE MANAGEMENT FOR TRAFFIC ACCIDENT MAPPING

NURKHALIESA BALQIS BINTI HAMZAH

A thesis submitted in fulfilment of the

requirements for the award of the degree of

Master of Science (Geomatic Engineering)

Faculty of Geoinformation and Real Estate

Universiti Teknologi Malaysia

MARCH 2014

iii

To my dearest husband, Saiful Adilin Ab Aziz

my lovely mama, Jamaliah Desa

my late dad, Hamzah Md. Jidin

my siblings, Faris Syahin,

Muhammad Qayyum and

Nur Batrisyia

iv

ACKNOWLEDGEMENT

First of all, I thank Almighty, my husband, my parents, brothers, sisters,

family in laws and friends for their constant encouragement without which this thesis

would not be possible.

I take this opportunity to express my profound gratitude and deep regards to

my guide Prof. Dr. Halim Setan and Dr. Zulkepli Majid for their exemplary

guidance, monitoring and constant encouragement throughout the course of this

thesis. The blessing, help and guidance given by them time to time shall carry out me

a long way in the journey of life on which I am about to embark.

I also take this opportunity to express a deep sense of gratitude to PLSRG

members, Sahidatul Fariza, Saidatul Shamila, Rizka Akmalia, Suzanna, Nurul

Shahida, Suraya, Faizah, Sabrina, Erna, and Ajibah for the valuable information

provided by them in their respective fields. I am grateful for their cooperation during

the period of my thesis.

i

THE INTEGRATION OF CLOSE RANGE PHOTOGRAMMETRY AND

DATABASE MANAGEMENT FOR TRAFFIC ACCIDENT MAPPING

NURKHALIESA BALQIS BINTI HAMZAH

UNIVERSITI TEKNOLOGI MALAYSIA

v

ABSTRACT

Various approaches in acquiring data of road accident are being implemented

worldwide. For police and forensic in Malaysia, they face challenges in obtaining accurate

measurements because they are still implementing the conventional method which is

impractical to map the road accident scene, consequently explain the lack of a

comprehensive accident recording and analysis system. This research presents the

implementation of close range photogrammetry of accident scene for data collection by

using three types of sensors to study the effectiveness of each sensor which are SONY

DSCHX5V for compact camera, NIKON D300S for Single Lens Reflex (SLR) camera and

MI DVJ350 for video recorder. Each accident simulation conducted at Universiti Teknologi

Malaysia (UTM) was recorded and imported into two different processing softwares which

are Photomodeler and iWitness that is employed together with CrashZone, to perform non-

contact measurement on physical evidences and subsequently generate 3D model of the

crash scene. The outcomes of this research are the measurement of evidences and 3D model

of road accident from three types of sensors. Data is stored, organized and retrieved in

accident data management system by using Microsoft Visual Studio together with SQL

Server Management Studio. The result shows that among these three sensors, NIKON

D300S is the best sensor that fit the requirement of law enforcement in acquiring accident

data because it has achieved the highest accuracy for physical evidences measurement. From

iWitness software the RMS obtained was 0.0344m while Photomodeler was 0.0348m. In

conclusion, this research gives benefits and contribution to the Malaysia’s traffic

management system due to the application of close range photogrammetry (CRP). The final

result can be as evidence in court litigation because in most jurisdictions, accidents involving

fatalities must be surveyed and mapped.

vi

ABSTRAK

Pelbagai pendekatan di dalam pengumpulan data kemalangan jalan raya sedang

diimplimentasikan di seluruh dunia. Bagi pihak polis dan forensik di Malaysia, mereka

menghadapi cabaran dalam mendapatkan pengukuran yang tepat kerana mereka masih

mengimplimentasi kaedah konvensional yang mana tidak praktikal untuk memetakan

kemalangan jalan raya, seterusnya menunjukkan kelemahan sistem merekod dan analisis

yang komprehensif. Kajian ini mempersembahkan pengimplimentasian fotogrametri jarak

dekat terhadap situasi kemalangan untuk pengumpulan data dengan menggunakan tiga jenis

sensor untuk mengkaji keberkesanan setiap sensor iaitu; SONY DSCHX5V mewakili

kamera kompak, NIKON D300S mewakili kamera lensa reflex tunggal dan MI DVJ350

mewakili perakam video. Setiap simulasi kemalangan dijalankan di Universiti Teknologi

Malaysia (UTM) telah direkod dan diimport ke dalam dua perisian pemprosesan berbeza

iaitu Photomodeler dan iWitness yang digunakan bersama dengan CrashZone, untuk

melakukan pengukuran tanpa sentuh terhadap bukti-bukti fizikal dan seterusnya

menghasilkan model 3D suasana kemalangan tersebut. Hasil kajian ini adalah pengukuran

bukti-bukti dan model 3D kemalangan jalan raya daripada tiga jenis sensor. Data telah

disimpan, diselenggara dan dicapai di dalam sistem pengurusan data kemalangan dengan

menggunakan Microsoft Visual Studio bersama dengan SQL Server Management Studio.

Keputusan menunjukkan di antara ketiga-tiga sensor ini, NIKON D300S adalah sensor

terbaik yang sesuai dengan keperluan pihak penguasa dalam mendapatkan data-data

kemalangan kerana ia telah mencapai ketepatan paling tinggi bagi pengukuran bukti-bukti

fizikal. Dari perisian iWitness, RMS yang diperolehi adalah 0.0344m manakala

Photomodeler adalah 0.0348m. Secara kesimpulannya, kajian ini memberi kelebihan dan

sumbangan kepada sistem pengurusan trafik Malaysia disebabkan aplikasi fotogrametri jarak

dekat (CRP). Keputusan akhir boleh dijadikan sebagai bukti di perbicaraan mahkamah

kerana dalam kebanyakan bidang kuasa, kemalangan yang melibatkan kematian mesti

diukur dan dipetakan.

vii

TABLE OF CONTENTS

CHAPTER TITLE PAGE

DECLARATION ii

DEDICATION iii

ACKNOWLEDGEMENT iv

ABSTRACT v

ABSTRAK vi

TABLE OF CONTENTS vii

LIST OF TABLES x

LIST OF FIGURES xi

LIST OF ABBREVIATIONS xv

LIST OF APPENDICES xvi

1 INTRODUCTION 1

1.1 Background of Study 1

1.2 Problem Statement 3

1.3 Objectives of Study 4

1.4 Scope of Study 5

1.5 Significance of Study 7

1.6 Thesis Chapters Layout 8

2 LITERATURE REVIEW 10

2.1 Information on Traffic Accidents 10

2.2 Methods Used in Traffic Accident Data Collection 13

2.2.1 Conventional Method 14

2.2.2 Close-Range Photogrammetry 16

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2.2.3 Other Methods 21

2.3 Traffic Accident Management System 24

2.4 Critical Needs of Road Accident Database 29

2.5 General Requirement to Develop Road Accident 32

System

2.6 Type of Database Management System (DBMS) 36

2.6.1 Relational DBMS (RDBMS) 37

2.6.2 Hierarchical 38

2.6.3 Object-oriented (O-O) 39

2.7 Chapter Summary 41

3 RESEARCH METHODOLOGY 44

3.1 Flowchart of Research Methodology 44

3.2 Traffic Accident Mapping 46

3.2.1 Data Collection 46

3.2.2 Data Processing 48

3.2.2.1 Image Processing in iWitness and 48

CrashZone

3.2.2.2 Image Processing in Photomodeler 56

3.3 Traffic Accident Data Management System 61

3.3.1 Overall Workflow 62

3.3.2 Database Design 63

3.3.3 Database System Development 67

3.3.4 System Evaluation 68

3.4 Chapter Summary 69

4 RESULT AND ANALYSIS 70

4.1 Introduction 70

4.2 Camera Calibration 70

4.2.1 iWitness Camera Calibration 71

4.2.2 Photomodeler Camera Calibration 72

ix

4.3 Example of Road Accident Simulation 74

4.4 Accuracy of Referencing 76

4.5 Measurement of Physical Evidences 79

4.6 3D Model of Accident Reconstruction 83

4.6.1 3D Model of Accident Reconstruction 84

in iWitness and CrashZone

4.6.2 3D Model of Accident Reconstruction 86

in Photomodeler

4.7 Design and Development of Road Accident 89

Database

4.7.1 Database Query 89

4.7.2 User Interface 90

4.7.2.1 Starting Window 91

4.7.2.2 Complainant Report 91

4.7.2.3 Investigation Result 93

4.7.2.4 Staff Registration 94

4.7.3 Road Accident Report Generator 95

4.8 Chapter Summary 99

5 CONCLUSION AND RECOMMENDATION 104

5.1 Conclusion 104

5.2 Recommendation 106

REFERENCES 108

APPENDICES

Appendix A to W20 122

x

LIST OF TABLES

TABLE NO. TITLE PAGE

1.1 Thesis Chapters Layout 9

2.1 Existing Traffic Accident Mapping and Data Management 41

3.1 Sample of Physical Evidences 53

4.1 Camera Calibration Result in iWitness for Three Cameras 71

4.2 Camera Calibration Result in Photomodeler for Three Cameras 73

4.3 Root Mean Square for iWitness and Photomodeler Project (in Pixel) 78

4.4 Dimensions of Physical Evidences Using Measurement Tape and 81

iWitness Based on 3 Cameras (Simulation 1)

4.5 Dimensions of Physical Evidences Using Measurement Tape and 82

Photomodeler Based on 3 Cameras (Simulation 1)

4.6 Comparison between This Research and Current Implementation 99

by PDRM and UTM Security Unit

4.7 Comparison between Photomodeler and iWitness Software 101

4.8 Comparison between Three Types of Cameras 102

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LIST OF FIGURES

FIGURE NO. TITLE PAGE

1.1 Research Area 5

1.2 i) Compact Camera, SONY DSC HX5V 6

ii) SLR Camera, NIKON D300S

iii) Video Recorder, MI DVJ350

2.1 Results of Traffic Accidents 11

2.2 Total Road Accidents and Motor Vehicles Involved 2001 to 2010 12

2.3 Types of Manual Measurement 14

2.4 Sketch of a Traffic Accident in POL27 Form 16

2.5 Police Investigators Using Camera to Collect Data 17

2.6 Sketches from James Dean Accident Scene 19

2.7 Crashteam (2008) converted an image that shows skid marks to 20

scale top down view of the scene. The right image was central

to the scene reconstruction and development of an accurate

accident scene for speed calculation and 3D animation.

2.8 Concept of Close Range Photogrammetry 20

2.9 Data Collection using Total Station and Laser Scanning 22

2.10 A reconstructionist and forensic mapping trainer, 23

uses a Sokkia robotic total station to map the scene of

a two-vehicle crash.

xii

2.11 Data visualization on seat belt usage in Vectormap. 25

2.12 Components of Abu Dhabi’s Traffic Information Management 27

2.13 Road Traffic Information Centre 27

2.14 Intelligent Road Accident System (IRAS) 28

2.15 Statistic of Road Deaths per 100000 Populations 30

2.16 Road Safety Strategy 31

2.17 Vehicle and Operator Services Agency (VOSA) Accident Database 33

2.18 PDRM Requirement for Measuring Crash Data 36

2.19 Example of Relational Data Model 38

2.20 Formal Relational Term versus Informal Equivalents Term 38

2.21 Hierarchical Database Model 39

2.22 Object Oriented Database Model 40

3.1 Flowchart of Research Methodology 45

3.2 Process of Data Collection 47

3.3 Process of Data Processing in iWitness and CrashZone 49

3.4 The Arrangement of Colour Coded Target for iWitness Camera 49

3.5 Referencing a Corresponding Feature Point in an Initial Image Pair 50

3.6 Process of Editing 52

3.7 Placing a Car Symbol from Symbol Manager Toolbox onto the 55

Drawing Window

3.8 Marking Process in Photomodeler 58

3.9 Setting Up Project Unit and Scale 58

3.10 Wireframe of Digitized Points and Lines 60

3.11 Path Surfaces is Applied into the Project 60

3.12 Fast Textures is Applied into the Project 60

3.13 Quality Textures is Applied into the Project 61

3.14 Overall Workflow for Road Accident Data Management 63

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3.15 (a): ER Diagram (Conceptual Model) 64

(b): ER Diagram (Logical Model) 65

(c): ER Diagram (Physical Model) 66

4.1 Camera Calibration Result (iWitness) 71

4.2 Camera Calibration Result (Photomodeler) 73

4.3 Location of a Simulation of Road Accident 75

4.4 A Scene of Road Accident 76

4.5 3D Point Table for iWitness 77

4.6 3D Point Table for Photomodeler 78

4.7 Sample of Measuring a Feature of Interest in iWitness 80

4.8 Sample of Measuring a Feature of Interest in Photomodeler 80

4.9 2D Diagram of Accident Scene 84

4.10 (a) Images from Camera 85

(b) 3D Reconstructed Model 85

4.11 Wireframe of Digitized Points 87

4.12 Model has been Added Surfaces 87

4.13 Model in Fast Textures 87

4.14 Model in Quality Textures 88

4.15 Model in Quality Textures without Points and Lines 88

4.16 User Form to Make Query 90

4.17 Starting Window 91

4.18 Complainant Form 92

4.19 Investigation Result of an Accident Case 93

4.20 Details of Staff Registration 94

4.21: Total Three Data in Database 95

4.22: Search by Specific Accident Report Number 96

4.23: Search by Specific Accident Location 96

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4.24: Search by All for Complainant Information Report 97

4.25: Search by All for Vehicle Information Report 98

xv

LIST OF ABBREVIATIONS

CAD - Computer Aided Design

CRP - Close Range Photogrammetry

DXF - Drawing Exchange Format

RMP - Royal Malaysia Police

RMS - Root Mean Square

SLR - Single Lens Reflex

TLS - Terrestrial Laser Scanning

2D - 2 Dimension

3D - 3 Dimension

DBMS Database Management System

xvi

LIST OF APPENDICES

APPENDICES TITLE PAGE

A Image of Camera Calibration in iWitness for SONY DSCHX5V 122

B Image of Camera Calibration in iWitness for NIKON D300S 123

C Image of Camera Calibration in iWitness for MI DVJ350 124

D AutoCal Button to Run Camera Calibration Automatically 125

E Process of Assigning a Scale 125

F XYZ Coordinate Axes in iWitness 126

G Button to View Crash Area in 3D Model 126

H Camera Calibration in Photomodeler 127

I Image activated as the Source in Referencing Mode 127

J Icon of Camera Indicating Position of the Camera Has Been 128

Oriented

K Positions of Camera 128

L Setting Up for Rotation Axes in Photomodeler Project 129

M Measurement of Point of Interest 129

N URA: Interview Session with PDRM-Inspector Haidir 130

O URA: Interview Session with UTM Security Unit-Mr. Norazam 133

P URA: Interview Session with MIROS-Mr. Hizal Hanis 135

Q Road Accident Sketch-by Computer 138

R Road Accident Sketch-by Hand 139

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S Road Accident Report by PDRM 140

T Road Accident Report in hardcopy form by UTM Security Unit 141

U Road Accident Report in HRFin by UTM Security Unit (1) 142

V Road Accident Report in HRFin by UTM Security Unit (2) 143

W1 Difference Value of Camera Parameters in iWitness 144

W2 Images for Processing (Simulation 1) 145

W3 Images for Processing (Simulation 2) 146

W4 Images for Processing (Simulation 3) 147

W5 Images for Processing (Simulation 4) 148

W6 Images for Processing (Simulation 5) 149

W7 Dimensions of Physical Evidences Using Measurement Tape and 150

iWitness Based on 3 Cameras (Simulation 2)

W8 Dimensions of Physical Evidences Using Measurement Tape and 151

Photomodeler Based on 3 Cameras (Simulation 2)

W9 Dimensions of Physical Evidences Using Measurement Tape and 152

iWitness Based on 3 Cameras (Simulation 3)

W10 Dimensions of Physical Evidences Using Measurement Tape and 153

Photomodeler Based on 3 Cameras (Simulation 3)

W11 Dimensions of Physical Evidences Using Measurement Tape and 154

iWitness Based on 3 Cameras (Simulation 4)

W12 Dimensions of Physical Evidences Using Measurement Tape and 155

Photomodeler Based on 3 Cameras (Simulation 4)

W13 Dimensions of Physical Evidences Using Measurement Tape and 156

iWitness Based on 3 Cameras (Simulation 5)

W14 Dimensions of Physical Evidences Using Measurement Tape and 157

Photomodeler Based on 3 Cameras (Simulation 5)

xviii

W15 3D Constructed Model of Accident Scene for Simulation 2 158

(iWitness)

W16 3D Constructed Model of Accident Scene for Simulation 3 159

(iWitness)

W17 3D Constructed Model of Accident Scene for Simulation 4 160

(iWitness)

W18 3D Constructed Model of Accident Scene for Simulation 5 161

(iWitness)

W19 3D Constructed Model of Accident Scene for Simulation 2 162

(Photomodeler)

W20 3D Constructed Model of Accident Scene for Simulation 4 163

(Photomodeler)

1

CHAPTER 1

INTRODUCTION

1.1 Background of Study

As time goes by, traffic accident has been a concern of the world community

since the number of accidents occurs has increased drastically. According to Sahar

and Jehan (2010), this phenomenon is increasingly being recognized as a growing

public issue. There are many factors that cause road collision including the behaviour

of driver, weather conditions, environment of the street, conditions of vehicles and so

forth. Malaysia as a developing country is experiencing growing numbers of vehicles

every year which is also contributing to the numbers of accidents (Road Safety

Department Malaysia, 2010).

Various methods have been introduced to collect the measurement of road

accident data ranged from conventional method to the sophisticated technology. The

data collection techniques includes by using a tape measure, close range

photogrammetry (CRP), laser scanner, and etc (Randles et al, 2010). Based on Haidir

(2012), Malaysian police still make use of tape measure to obtain accident data

measurement. Another method that can be implemented for this initiative is by using

digital cameras.

2

These sensors comprises of cameras that can be utilized for capturing images

and videos. Recorded images are the source of accident data collection to do

measurement on evidences, reconstruct and map the crash scene afterwards. Crash

data can be obtained by using close range photogrammetry (CRP) method. Coyle

(2008) stated that CRP can be implemented in motor vehicle accident reconstruction

while Richard and Stephen (2000) declared that videogrammetry can be used by

forensic engineers to assist them in the same field.

There are numerous effects of a road accident to the individual involved, their

family, and towards the country (Qirjako et al., 2008). Hence, many efforts have

been made by different organizations in improving safety each year. The utilization

of computers makes this effort more comprehensive and productive. One of the

approaches is by using Geographic Information System (GIS) technology which has

been a vital tool for visualization of accident data and analysis of hotspots on the

road. Mino and Asada (2003) explained that they have demonstrated the spatial

information technology such as GIS which can assist their case study.

The key of this study is to investigate five simulation cases of traffic

accidents by using 3 types of camera which are SONY DSCHX5V for compact

camera, NIKON D300S for Single Lens Reflex (SLR) camera and MI DVJ350 for

video recorder. The accident scene is recorded and imported into two different

processing softwares which are iWitness that is employed with CrashZone and

Photomodeler to perform non-contact measurement on physical evidences. The

generation of 3D model of crash scene is made afterwards. The outcomes from these

three types of sensors are the measurement of evidences and 3D model of road

accident that are analyzed in data analysis section.

Accident data that has been processed are the input for the database to be

further analysed. These data are served as visualization purpose in the traffic accident

database system. The data management system is developed using Visual Studio to

3

determine accident location, to identify the details of particular accidents and also to

determine how accident countermeasures can be implemented.

1.2 Problem Statement

One of the major concerns for police investigators and forensic scientists in

Malaysia is the challenges in documenting traffic accident scenes to obtain accurate

measurements. The approach for collecting the measurement of evidences is

conventional method which is using a tape measure (Yew, 2009). It is almost

impractical to map the scene due to many issues such as traffic jam, the environment

of the road, unstable flooring, and line of sight issues consequently this is often

inaccurate for 3D data.

In spite of this matter, other techniques that can be implemented for most

cases are close range photogrammetry. Currently, law enforcement in Malaysia

depends on images captured on site of the accident scene which is only for

visualization purpose (Haidir, 2012). The utilization of camera for them is just for

pointed out the evidence which is difficult when it comes to retrieve the data.

Nowadays, different types of camera are available in the market with

different technology and specification. Thus, the need to find the suitability of

camera must be discovered to be the best sensor that can fit the requirement of law

enforcement in acquiring accident data. This camera is expected to give the best

image resolution and achieve the highest accuracy for physical evidence

measurement.

4

The representation of different type of cameras; SONY DSCHX5V for

compact camera, NIKON D300S for SLR camera and MI DVJ350 for video

recorder, producing a variety of data accuracies in terms of image processing. Hence,

analysis is done to evaluate the effectiveness of using three types of camera based on

different data accuracy.

In the aspect of data processing, the usage of two different softwares which

are iWitness and PhotoModeler yield different quality of evidences measurement and

the reconstruction of accident scene. To check the reliability of accident simulation,

5 different cases were carried out by using the same three types of camera together

with the two kinds of CRP data processing softwares. In brief, various types of

camera and processing softwares are used in this research to produce different type

of data. The result is different according to accident cases, sensor’s accuracy,

measurement of evidences, and crash scene mapping.

In addition, accident recording and analysis system must be developed to

support crash data that are obtained by using proposed sensors. Therefore, an

appropriate database is necessary to help the police investigators and forensic

scientists to assist and manage the road collision data.

1.3 Objectives of Study

The objectives are specified as follows:

i) To reconstruct 3D model of simulation of five accident scenes by

using PhotoModeler and iWitness software according to different

types of camera.

ii) To develop traffic accident database system.

5

1.4 Scope of Study

Four scopes of research are listed as below:

i) Area of study is conducted in Universiti Teknologi Malaysia (UTM)

as shown in Figure 1.1. It is located at Johor Bahru, the southern city

in Iskandar Malaysia with 1177 hectares of land. The simulations of

road accidents are located at 5 different places (yellow pinpoint)

which are identified as ‘hotspots’ in UTM area.

Figure 1.1: Research Area

Scale 1:25000

ii) 5 data of road accidents is obtained from 5 accident simulations. Crash

scenes are captured by using 3 types of sensors which are SONY

DSCHX5V (10.2 Megapixels), NIKON D300S (12 Megapixels) and

MI DVJ350 (20.1 Megapixels) as illustrated in Figure 1.2. SONY

DSCHX5V is used to capture images of road accidents to represent

compact camera. NIKON D300S is characterized as SLR camera also

N

6

is utilized to take picture of accident scene. As for video recorder, MI

DVJ350 is employed to capture video of road accident simulation.

These cameras are calibrated before collecting the data. Several cars

are used along with other tools such as scale bar, broken glasses as for

the impact of accident, 6 traffic cones to control the crash area, and

black aerosol spray for creating the scratch tyre. Several images are

taken in different angles to cover the whole area of the crash scene.

i) ii)

iii)

Figure 1.2: i) Compact Camera, SONY DSC HX5V (10.4 x 5.8 x 2.8cm) ii) SLR

Camera, NIKON D300S (14.7 x 11.4 x 7.4cm) iii) Video Recorder, MI DVJ350

(6.7 x 6.9 x 12.9cm)

7

iii) The data are processed by using 2 softwares:

a) iWitness and CrashZone: iWitness is used to process the data

in terms of measurement. In addition, iWitness also used to

perform the camera calibration. CrashZone support iWitness in

order to display the 3D view of the collision scene.

b) Photomodeler: A photogrammetric-based processing software

that measures and model real world objects and scenes through

the use of images. This software brings the powerful

capabilities of photogrammetry in a simple, user friendly

Windows environment (Eos, 2010).

iv) The database of road accident data is stored in SQL Server

Management Studio while the system is developed in Microsoft

Visual Studio 2010.

1.5 Significance of Study

Various actions and treatments have been taken to reduce the rate of traffic

accident in the whole world. According to U.S Department of Interior (2003), “an

accident investigation is the methodical collection of evidence (facts), and the

analysis and interpretation of the evidence. The fundamental purpose is to identify

the cause, why the accident happened, and to recommend corrective actions to

prevent or minimize the chance of a reoccurrence.” Thus, accident data is significant

for government and road agencies as it is served as evidence in jurisdictions and as

countermeasure for road safety.

CRP is an alternative way to conventional method to obtain measurement of

traffic accident data. This technique is more practical to be implemented because of

8

the reducing on scene time, which leads to shorter periods of traffic disruption.

Furthermore, the procedure is easy to adopt for assisting police officers in managing

the road accident case.

This research is expected to give benefits and contribution to the Malaysia’s

traffic management system due to the application of CRP. The final result can be as

evidence in court litigation because in most jurisdictions, accidents involving

fatalities must be surveyed and mapped. In brief, this research contributes to current

practice of data collection with reducing the time and provides higher accuracy of

positional crash data.

Variety of study and advice as well as mass media reports regarding the cause

of the accident give useful messages to other road users. Despite, this tragedy on the

roads continues to be a burden to the society. Thus, this study is essential for traffic

accident management by utilization of database system. Since the rate of road deaths

increases, a database system is extremely significant tool for traffic safety.

This tool has been employed more commonly by many traffic agencies for

accident analysis due to the variety of function such as storing, sharing and managing

a great quantity of data. Thus the need to attempt to avoid road accidents by

whatever means that are effective will become increasingly important.

1.6 Thesis Chapters Layout

This thesis consists of five chapters, Table 1.1 described the summary of

each chapter.

9

Table 1.1: Thesis Chapters Layout

Chapters Summary

1

2

3

4

5

Describe the introduction of the research background, problem

statement, objective of study, scope of study, significance of study

and chapters layout.

Describes the methods used in traffic accident data collection.

Also describes related works on road accident database that has

been established worldwide.

Describes the method implemented in the data collection of traffic

accident and the development of traffic accident database.

Describes the results and analysis.

Describes the conclusion and recommendation for further

research.

108

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