TRAFFIC IMPACT ASSESSMENT OF NEW COMMERCIAL …eprints.utm.my/id/eprint/33300/1/NazirHuzairyZakiMFKA2013.pdf · Menyilang dan Analisa Regresi untuk mengetahui trafik di masa hadapan

TRAFFIC IMPACT ASSESSMENT OF NEW COMMERCIAL DEVELOPMENT

IN THE NEIGHBOURHOODS OF SKUDAI TOWN

NAZIR HUZAIRY BIN ZAKI

UNIVERSITI TEKNOLOGI MALAYSIA

TRAFFIC IMPACT ASSESSMENT OF NEW COMMERCIAL

DEVELOPMENT IN THE NEIGHBOURHOODS OF SKUDAI TOWN

NAZIR HUZAIRY BIN ZAKI

A project report submitted in partial fulfillment of the

requirements for the award of the degree of

Master of Engineering (Civil-Transportation and Highway)

Faculty of Civil Engineering

Universiti Teknologi Malaysia

JAN 2013

iii

Dedicated to my beloved mama, Hasnah Binti Abdul Rahim

and ayah, Zaki Bin Ahmad Ghazi

iv

ACKNOWLEDGEMENT

First and foremost I would like to thank Allah S.W.T. for His blessing I finally

completed my Master Project without much hassle and I able to it on time.

I would like to express my gratitude and special thanks to my supervisor Dr. Anil

Minhans who for the past two semesters had tremendously helped me to finish my

Master Project. Dr. Anil would not mind giving me new ideas and ways to solve my

problems even though he is busy with his own work and other duties.

Heartiest thanks to Ms. Salida and Ms. Aisyah from MPJBT that had helped me by

giving the data required. A thousand thanks to management personnel from Giant U

Mall, Jusco Taman Universiti and Carrefour Sutera Utama which had gave me the

permissions to use their sites for data collection.

A special thanks also for my friends and family who has supported me all out during

this time. Without their support and encouragement I may not be able to complete

my Master Project on time.

Thanks.

v

ABSTRACT

Urban areas in Malaysia including Johor Bahru are witnessing a rampant commercial

development. The purpose of development can easily be defeated by unanticipated

traffic congestion and other negative impacts. This paper deals with traffic impact

assessment (TIA) of proposed commercial development in the neighbourhoods of

Skudai Town. In traffic impact studies, estimation of mean trip rate is a central

component for TIA and adoption of inaccurate trip rates can result into

underestimation or overestimation of development traffic, both with undesirable

impacts. This paper analyses three regimes of Trip Rate Analysis, Cross-

Classification Analysis and Regression Analysis techniques to determine the future

development traffic for a proposed Tesco hypermarket (TH) within Skudai Town.

Furthermore, the obtained mean trip rates for critically examined for their adoption

and forecasting traffic for base year 2015 and horizon year 2025. The results

indicated significant variances in the estimated entry mean trip rates when compared

with the entry trip rates from Trip Generation Manual (TGM) Malaysia. These

estimated mean trip rates were then tested to measure the performance of critical

intersection in the immediate vicinity of proposed Tesco Hypermarket for the

opening year 2015. Critical Intersection is analysed using SIDRA software to

estimate delay, a criterion for determining the level of service (LOS) provided to

motorists. The traffic projections made for horizon year 2025 were further analysed,

depicting a LOS F with 2716.9s of average delay. Furthermore, traffic improvements

were proposed to mitigate the impact of future development traffic. In this regard, the

study provided a framework for the estimation of trip rates for local Malaysian

conditions and their adoption guidelines. These offer indispensible assistance to TIA

that can assist developers or local authorities in decision making.

vi

ABSTRAK

Kawasan Bandar di Malaysia termasuk Johor Bahru sedang menyaksikan

pembangunan komersial yang pesat. Matlamat pembangunan boleh dikalahkan

dengan kesesakkan lalu lintas dan impak negatif lain yang tidak dijangka. Kajian ini

membincangkan tentang taksiran impak trafik (TIA) oleh cadangan pembangunan

komersial di dalam kawasan kejiranan Bandar Skudai. Di dalam kajian impak trafik,

pengiraan kadar perjalanan adalah perkara asas untuk TIA dan penggunaan kadar

perjalanan yang tidak tepat boleh menghasilkan kadar yang terlalu tinggi atau rendah

yang mana kedua-duanya mempunyai impak yang tidak diingini. Kajian ini

menganalisa tiga rejim iaitu Analisa Kadar Perjalanan, Analisa Klasifikasi

Menyilang dan Analisa Regresi untuk mengetahui trafik di masa hadapan disebabkan

oleh pembangunan Pasaraya Besar Tesco (TH). Purata kadar perjalanan yang

diperoleh diuji secara kritikal untuk pengunaan dan ramalan trafik untuk tahun dasar

2015 dan tahun ufuk 2025. Hasil kajian menunjukkan terdapat perbezaan ketara di

antara kadar perjalanan masuk yang di kira dengan kadar perjalanan masuk daripada

Manual Generasi Kadar (TGM) Malaysia. Kadar perjalanan yang di kira diuji untuk

mengira prestasi simpang kritikal di dalam kawasan persekitaran cadangan TH untuk

tahun pembukaan 2015. Persimpangan kritikal itu dianalisa mengunakan perisian

SIDRA untuk mengira kelewatan iaitu kriteria untuk mengetahui Tahap Servis

(LOS) untuk pengguna jalanraya. Analisa diteruskan dengan unjuran trafik untuk

tahun ufuk 2025 yang menunjukkan LOS F dengan purata kelewatan 2716.9s.

Tambahan lagi, penambahbaikkan trafik telah dicadangkan untuk mengatasi impak

trafik akibat pembangunan di masa hadapan. Dalam hal ini, kajian ini memberi

rangka kerja dan juga garis panduan pengunaan untuk pengiraan kadar perjalanan

untuk situasi Malaysia. Ini memberi bantuan yang amat penting kepada TIA yang

boleh membantu pemaju dan pihak berkuasa tempatan di dalam membuat keputusan.

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 xv

LIST OF ABREVATIONS xvii

LIST OF APPENDIX xviii

1 INTRODUCTION 1

1.1 Background of Study 1

1.2 Problem Statement 2

1.3 Objectives 5

1.4 Scope of Study and Limitations 5

1.5 Significance of Study 6

2 LITERATURE REVIEW 7

2.1 Introduction 7

2.2 Effects of Improper Trip Rate Estimation 8

2.3 Development of Trip Generation Manual 9

2.4 Type of Land Use 10

viii

2.5 Current Traffic Condition 14

2.5.1 Origin-Destination Survey 14

2.6 Forecasting Travel Demand 15

2.6.1 Sequential Steps of Travel Forecasting 16

2.6.2 Trip Generation 18

2.6.3 Types of Trips 18

2.6.4 Determination of Mean Trip Rates 21

2.7 Traffic Growth Factor 24

2.8 Transport Improvement 24

3 RESEARCH METHODOLOGY 26

3.1 Introduction 26

3.2 Collection of Data 29

3.3 Study Boundary 29

3.4 Current and Proposed Land Use Developments 31

3.5 Type, Location and Characteristics of Proposed New

Commercial Development

36

3.6 Number and Locations of Existing Commercial

Developments with Similar Characteristics

39

3.7 Questionnaire Surveys 41

3.7.1 Customers Survey 41

3.7.2 Shop Owners Survey 43

3.8 Vehicle Counts 43

3.8.1 Vehicles Count at Existing Commercial

Developments

44

3.8.2 Vehicles Count at Critical Intersection near the

Proposed Tesco

46

3.9 Mean Trip Rate Estimation Procedures 48

3.9.1 Trip Rate Analysis Procedures 48

3.9.2 Cross-Classification Analysis Procedures 50

3.9.3 Regression Analysis Procedures 51

3.10 Projected Traffic Volume 52

3.11 Appropriate Road Improvement 54

ix

4 ANALYSIS AND RESULTS 55

4.1 Introduction 55

4.2 Trip Rate Analysis 56

4.2.1 Giant U Mall 56

4.2.2 Jusco Taman Universiti 56

4.2.3 Carrefour Sutera Utama 57

4.2.4 Mean Trip Rate Using Trip Rate Analysis 57

4.3 Cross-Classification Analysis 58

4.3.1 Giant U Mall 58

4.3.2 Jusco Taman Universiti 70

4.3.3 Carrefour Sutera Utama 82

4.3.4 Mean Trip Rate Using Cross-Classification

Analysis

98

4.4 Regression Analysis 99

4.4.1 Mean Trip Rate Using Regression Analysis 105

4.5 Comparison of Entry Mean Trip Rate Using Trip Rate

Analysis, Cross-Classification Analysis, Regression

Analysis and Trip Generation Manual

106

4.6 Traffic Impact Assessment 107

4.6.1 Base Year Traffic Volume at Critical

Intersection

107

4.6.2 Projected Traffic Volume at Opening Year

2015

110

4.6.3 Projected Traffic Volume in Horizon Year

2025

112

4.7 Transport Improvement 114

5 CONCLUSIONS 115

5.1 Conclusions 115

REFERENCES 119

APPENDIX A-C 121

x

LIST OF TABLES

TABLE NO TITLE PAGE

2.1 Effects of improper estimation of trip rates (Minhans, A.

et. al., 2012)

8

2.2 Typical trip production table (Garber and Hoel, 2009) 22

2.3 Typical trip attractions table (Garber and Hoel, 2009) 23

3.1 Districts within each zone together with population size 31

3.2 Percentage of each type of land use in Skudai Town as

obtained from MPJBT

33

3.3 General characteristics of the proposed TH, GUM, JTU

and CSU

40

3.4 PCU factors as taken from Malaysian Trip Generation

Manual 2010 by HPU

49

4.1 Trip Rate Analysis results (GUM) 56

4.2 Trip Rate Analysis results (JTU) 56

4.3 Trip Rate Analysis results (CSU) 57

4.4 Weekday AM peak, weekday PM peak, weekend AM

peak and weekend PM peak mean trip rate PCU trips

per hour per 100m2 GFA and standard deviation

58

4.5 Weekday AM peak survey data (GUM) 59

4.6 No. of shops in each GFA category versus no. of

employees

59

4.7 Average number of person trips per shop per hour

versus GFA and number of employees

60

4.8 Percentage of shops in each GFA category 60

xi

4.9 Number of person trips per hour with respect to each

GFA category and number of employees

60

4.10 Weekday PM peak survey data (GUM) 62


employees

62



63




63

4.15 Weekend AM peak survey data (GUM) 65


employees

65



66




66

4.20 Weekend PM peak survey data (GUM) 68


employees

68



69




69

4.25 Weekday AM peak survey data (JTU) 71

4.26 No. of shops in each GFA category versus employees 71



72




72

xii

4.30 Weekday PM peak survey data (JTU) 74


employees

74



75




75

4.35 Weekend AM peak survey data (JTU) 77


employees

77



78




78

4.40 Weekend PM peak survey data (JTU) 80


employees

80



81




81

4.45 Weekday AM peak survey data (CSU) 83


employees

84



84




85

4.50 Weekday PM peak survey data (CSU) 87

xiii


employees

88



88




89

4.55 Weekend AM peak survey data (CSU) 91


employees

92



92




93

4.60 Weekend PM peak survey data (CSU) 95


employees

96



96




97



per hour per 100m2 GFA and standard deviation using

Cross-Classification Analysis

98

4.66 Dependency between GFA and number of employees to

number of trips

99

4.67 Dependency of GFA to number of trips 99

4.68 Dependency of number of employees to number of trips 100

4.69 Mean trip rate from regression Analysis for GUM 102

4.70 Mean trip rate from regression Analysis for JTU 103

xiv

4.71 Mean trip rate from regression Analysis for CSU 105



per hour per 100m2 GFA and standard deviation using

Regression Analysis

106

4.73 Comparison of entry mean trip rate per 100 m2 GFA

using trip analysis, cross-classification analysis,

regression analysis and Trip Generation Manual

107

4.74 Base year intersection performance 110

4.75 Number of trips generated by the proposed TH 111

4.76 Intersection performance at opening year 2015 112

4.77 Projected intersection performance in horizon year 2025

with the proposed TH

113

4.78 Projected intersection performance in horizon year 2025

with the proposed TH and proposed road improvement

114

xv

LIST OF FIGURES

FIGURE NO TITLE PAGE

2.1 Type and intensity of land uses in Skudai Town (source:

MPJBT Johor Map 2010)

12

2.2 Travel forecasting process 17

2.3 Typical home based (HB) trip with respect to trip

production and trip attraction

19

2.4 Typical non-home (NHB) based trip with respect to trip

production and trip attraction

19

2.5 Trips characteristics (Minhans, A., 2008) 20

2.6 Transport improvement methods (Minhans, A., Pillai,

C. M., 2012)

25

3.1 Flowchart for the activity of the study 28

3.2 Study area boundary (not to scale) 30

3.3 Boundary of each zone within Skudai Town 30

3.4 Current and proposed all type of land use in Skudai

Town as obtained from MPJBT

32

3.5 Current and proposed commercial type of land use in

Skudai Town as obtained from MPJBT

34

3.6 Current commercial type of land use in Skudai Town as

obtained from MPJBT

35

3.7 Proposed (2020) commercial type of land use in Skudai

Town as obtained from MPJBT

36

3.8(a) Location of new proposed TH at Taman Sri Pulai

Perdana (not to scale)

38

xvi

3.8(b) Location of new proposed TH at Taman Sri Pulai

Perdana (not to scale)

38

3.9 Location of proposed TH, GUM, JTU and CSU (not to

scale)

40

3.10 Surveyor locations for the manual vehicle counting for

GUM

44


JTU

45


CSU

45

3.13 Location of critical intersection nearby the proposed TH 47

3.14 Geometry layout of the intersection 47

4.1 Weekday AM peak (GUM) 100

4.2 Weekday PM peak (GUM) 101

4.3 Weekend AM peak (GUM) 101

4.4 Weekend PM peak (GUM) 101

4.5 Weekday AM peak (JTU) 102

4.6 Weekday PM peak (JTU) 102

4.7 Weekend AM peak (JTU) 103

4.8 Weekend PM peak (JTU) 103

4.9 Weekday AM peak (CSU) 104

4.10 Weekday PM peak (CSU) 104

4.11 Weekend AM peak (CSU) 104

4.12 Weekend PM peak (CSU) 105

4.13 Base year (2012) weekday AM peak hour traffic volume 108

4.14 Base year (2012) weekday PM peak hour traffic volume 108

4.15 Base year (2012) weekend AM peak hour traffic volume 109

4.16 Base year (2012) weekend PM peak hour traffic volume 109

4.17 Projected traffic volume at opening year 2015 without

the proposed TH in PCU/hr for all traffic movements

111

4.18 Projected traffic volume in horizon year 2025 with the

proposed TH in PCU/hr for all traffic movements

113

xvii

LIST OF ABBREVIATIONS

Symbol Descriptions

LOS Level of Service

TIA Traffic Impact Assessment

GFA Gross Floor Area

HCM Highway Capacity Manual

HPU Highway Planning Unit Malaysia

ITE Institute Transportation Engineers

O-D Origin-Destination

IDR Iskandar Development Region

TAZ Traffic Analysis Zone

HB Home Based

NHB Non-Home Based

TH Tesco Hypermarket

GUM Giant U Mall

JTU Jusco Taman Universiti

CSU Carrefour Sutera Utama

xviii

LIST OF APPENDIX

APPENDIX TITLE PAGE

Appendix A Customers Survey Form 121

Appendix B Shop Owners Survey Form 125

Appendix C Manual Vehicle Count Sheet 126

1

CHAPTER 1

INTRODUCTION

1.1 Background of Study

Policy makers in Malaysia under the current 9th Malaysian Plan intend to

develop Malaysia into a developed nation by the year 2020 based from the National

Transformation Program (NTP). This is revealed in rampant urban development in

many states of Malaysia especially southern state of Johor. Given the location value

of Skudai Town due to its close proximity to Singapore, the development is even

large both in scale and intensity. Skudai Town also contain an international

university, Universiti Teknologi Malaysia which imparts education to over 20,000

students and employs more than 4,000 academic and technical staff. In this regard,

Skudai Town may well be regarded as university town.

But, without a proper understanding of development impacts on the road

network, the intent of the developments which are to bring economic and social

purposes could be easily defeated by unanticipated traffic congestion and other

negative impacts. It is well known that new development will generate new traffic

volume on the existing road network and if the existing road network are unable to

cater for the new amount of traffic volume, traffic congestion will occur which will

2

lead to poor economic return due to delay in travel time, air pollution and high fuel

consumption during congestion and even accidents.

New development can also decrease the accessibility and mobility of

travelers if not planned properly. In other words, the extra traffic generated from the

new development will have an adverse impact on the Level of Service (LOS) of the

road network. Therefore, it is essential to conduct a traffic impact assessment (TIA)

during planning stage of the new development to determine the amount of traffic that

will be generated from the new development and to determine if the existing road

network is capable to sustain the combination of old and new development traffic. If

the existing road network is unable to accommodate the new traffic, ways of

mitigation can be planned based on the results obtained from TIA such as modifying

the road geometrics, adding of an additional lane, providing roundabout or

configuring traffic signal among others that seems appropriate.

Skudai Town is rapidly growing with many new mixed land use development

such as new malls, shop houses, residential areas, factories and many more. Only few

years ago that Skudai Town was under developed with only few residents and

commercial areas on top of already established Universiti Teknologi Malaysia

(UTM). Due to the rapid growth, TIA study for Skudai Town is necessary to be

conducted for estimating the appropriateness of the application of Malaysian trip

rates.

1.2 Problem Statement

TIA is very important during the planning stage of any new development to

avoid congestion and other negative impacts that may arise. The problem in this

country is that the standard and procedures in producing and evaluating of TIA report

3

still has not been standardized or well developed (Wee Ka Siong, 2001). This will

raised concern on validity of the estimation of traffic volume projection.

Because there are no proper standards to follow, traffic engineers or traffic

planners usually refer to guidelines of TIA and use trip generation rates from

previously established manuals such as Trip Generation Manual from Highway

Planning Unit (HPU) in Malaysia or by Institute Transportation Engineers (ITE) in

the United States. Experiences from past projects in determining trip rates are also

used as analogy for estimating trip rates for upcoming projects.

Even though the trip rates stated in the HPU trip manual was based from

study done all across Malaysia, but it was still at early stages with limited number of

survey sites especially for less common types of land uses. On the other hand, the

problem with the ITE manual is that it does not reflect well on the true conditions of

typical Malaysian lifestyle and travel pattern as ITE was published based on various

studies within the United States which are different to typical Malaysian way of life,

climate, socio-economic considerations and so forth which makes the travel pattern

different between these two countries.

Both manuals provide trip rate that are insensitive to population density,

travel patterns, economic growth, accessibility etc. For example, the number of

vehicle trips going into a shopping mall for a car dependent city will considerably

higher than a city that depends on public transport even for the same shopping mall

type and area. In other words, the number of trip generated by a certain type of land

use depends on local conditions of the area. Thus, trip rates calculating procedures

can be prone to biases or errors which can result in overestimation or

underestimation of mean trip rates. These inherent flaws in the trip estimates

provided the need of this study.

4

Another source was to calculate the trip rates by the developer themselves but

the trip rates can also prone to biases or error which means the developer usually

manipulated the procedures to estimates minimum trip rates to show that the

proposed new development will not have major impacts on the current traffic volume

just to obtain a planning certificate easily or the developer lacks sound knowledge of

how to estimates the trip rates with limited errors.

When there is underestimation of trip rates, the outcome of TIA is rather

minimal which shows that the new development will not generate much traffic in the

future. That means the road network within the area will be design base on small

traffic volume which may not be enough or adequate in the future. This can lead to

serious congestion when the road is operating at capacity. This is also beneficial to

the developer due to the low cost for the development because underestimation of

trip rates requires less number of complex road networks.

By using unsuitable procedures to estimate the trip rates can also lead to

overestimation. An overestimation of trip rates shows that the new development will

create high traffic volume in the future. This means that the road network will be

designed based on high traffic volume which will be higher in terms of investment

cost and also the operating cost to construct the road network. There will also be

using lot of land spaces. This can lead to the road network be underutilized and a

wastage of spaces of land and money just to built unessential roads.

Hence, local TIA studies in Skudai Town were conducted to understand

traffic conditions that may emerge in the future and accuracy of mean trip rates.

Furthermore, the percentage of commercial developments in Skudai Town is rapidly

increasing for the past 5 years which has resulted in the rapid growth of traffic

volume annually compare to years before that which means any trip rates study done

here in the past 10 or more years may not be valid now. Therefore, this study can

provide valuable information pertaining traffic issues in Skudai Town and identical

urban areas.

5

1.3 Objectives

In order to achieve the aim of the study, the main objectives had been

identified as:

i. To estimate the mean trip rates per 100m2 of gross floor area (GFA) under

commercial land use;

ii. To test and validate the adoption of mean trip rates per 100m2

while

comparing three test regimes; Trip Rate Analysis, Cross Classification

Analysis And Regression Analysis techniques;

iii. To quantify the impacts of additional development traffic from the proposed

commercial area for the horizon year 2025 on the neighboring road network;

iv. To propose appropriate transport improvement measure for the existing road

network within Skudai.

1.4 Scope of Study and Limitations

In order to achieve the objectives, the scope of study was confined only to

commercial areas in the neighborhoods of Skudai Town. It involved collection of

information on land uses, current and proposed commercial area establishment

characteristics, traffic growth factor and current traffic volume in Skudai Town. This

study used three test methods to determined the mean trip rate for a proposed

commercial area namely Trip Rate Analysis, Cross-classification Analysis and

Regression Analysis where only the entry volumes were counted due to limitations

of time, man power and resources to count both the entry and exit traffic volume as

the exit traffic volume was assume to be the same as entry traffic volume.

6

Another limitation, that type, scale and intensity of commercial activities in

the preselected commercial markets for analysis are considered to be identical in

nature. These commercial areas are presumed to generate trip rates which are deemed

comparable. The projected traffic volumes at a critical intersection near the proposed

commercial establishment were analyzed using SIDRA software to determine the

performance of the intersection.

1.5 Significance of Study

As what already been mentioned, this study focused on TIA due to a new

commercial area development in rapidly developing Skudai Town. This study which

was based from existing commercial developments in the study area will give an

expectation on how much trips will be generated by a new propose commercial

developments in the area.

The trip rates estimation in this study will not be biased to any party, be it a

developer or municipal authorities and will be adequate enough that it will not be too

low nor too high that can lead to the new road network at capacity which can cause

congestion or underuse which is a waste in term of cost and land spaces within the

new development. The results could be used for future TIA studies from similar

development of commercial areas in Skudai Town.

Also, this study signifies the appropriateness of the application of universal

Malaysian trip rates and its impacts.

119

REFERENCES

Allen, D. L., Barret, M. L., Graves, R. C., Pigman, J. G., Abu-Lebdeh, G., Aultman-

Hall, L., and Bowling, S. T. (2011). Analysis of Traffic Growth Rates.

Kentucky Transportation Center. Lexington, Kentucky.

Chatterjee, A. and Venigalla, M. M. (1996). Travel Demand Forecasting for Urban

Transportation Planning. Compendium of technical papers: Institute of

Transportation Engineers, 37, 217-281. Institute Transport Engineers.

Garber, N. J. and Hoel, L. A. (2009). Traffic and Highway Engineering. (4th

ed.).

Cengage Learning: Canada.

Highway Planning Unit (2010). Trip Generation Manual 2010. (1st ed.). Malaysia:

Highway Planning Unit.

Institute of Transportation Engineers (1991). Trip Generation. (5th

ed.). Washington

D.C.: Institute of Transportation Engineers.

Lay, M. G. (2009). Handbook of Road Technology. (4th

ed.). New York: Spoon

Press.

Majlis Perbandaran Johor Baru Tengah (2010). Local District Plan Johor Bahru

2020. Malaysia: Majlis Perbandaran Johor Baru Tengah.

Mc all , M G “The four step model ” Handbook of Transport Modelling,

1st Ed., D. A. Hensher and K. J. Button, eds., Elsevier Science, Kidlington,

Oxford, U.K.

Minhans, A. (2008). Traffic Management Strategies in Cases of Disasters. Published

Doctoral Dissertation, Institute for Traffic and Transport, Darmstadt

University of Technology, TUD, Darmstadt, Germany.

Minhans, A. et. al. (2012). Methodologies for Estimation of Traffic Impacts from

Proposed Commercial Developments – A Case Study of Skudai Town, Johor,

Malaysia. Conference Proceedings UTM-IBIMA International Real Estate

Conference 2012. Kuala Lumpur, Malaysia.

Minhans, A., Pillai, C. M. (2012). Multi-Criteria Analysis for Effectiveness and

Difficulties of Traffic Management in Disasters. APSEC-ICCER, Conference

Proceedings, Surabaya, Indonesia.

Papacostas, C. S. and Prevedouros, P. D. (2008). Transportation Engineering and

Planning. (3rd

ed.). New Delhi: Prentice Hall.

120

Rhee, J. (2003). Improvement of Trip Generation Forecast with Category Analysis in

Seoul Metropolitan Area. Proceedings of the Eastern Asia Society for

Transport Studies. Vol.4.

Siong, W. K. (2001). Development of Traffic Impact Assessment (TIA) Criteria in

Malaysia: Johor State as the Basic Model. Doctor Philosophy, Universiti

Teknologi Malaysia, Skudai.

Sosslau, A. B., Hassam, A. B., Carter, M. M. and Wickstrom, G. V. (1978).

NCHRRPe port 187: Quick-Response Urban Travel Estimation, Techniques

and Transferable Parameters. TRB. National Research Council, Washington.

Stopher, P. R. and Meyburg, A. H. (1975). Urban Transportation Modelling and

Planning. (1st ed.). Lexington, Massachussets: Lexington Books, D.C Heath

& Company.

Tesco PLC (2012). Tesco PLC Annual Review and Summary Financial Statement

2012. Tesco PLC: United Kingdom.

Uddin, M. M., Hasan, M. R., Ahmed, I., Das, P., Uddin, M. A. and Hasan, T. (2012).

A Comprehensive Study on Trip Attraction Rates of Shopping Centers in

Dhanmondi Area. International Journal of Civil & Environmental

Engineering. Vol 12.

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TRAFFIC IMPACT ASSESSMENT OF NEW COMMERCIAL …eprints.utm.my/id/eprint/33300/1/NazirHuzairyZakiMFKA2013.pdf · Menyilang dan Analisa Regresi untuk mengetahui trafik di masa hadapan