extent of road lighting impact on the quality of...

EXTENT OF ROAD LIGHTING IMPACT ON THE QUALITY OF ROADWAY

SERVICE

AZTRI YULI KURNIA

A project report submitted in partial fulfillment of the

requirements for the award of degree of

Master of Engineering (Civil - Transportation and Highway)

Faculty of Civil Engineering

Universiti Teknologi Malaysia

JANUARY 2012

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To my beloved mommy and daddy

iv

ACKNOWLEDGEMENT

First and foremost, I would like to express my sincere thanks and

appreciation to my project supervisor Assoc. Prof. Dr. Johnnie Ben-Edigbe, who

continuously guided me throughout every step of my study and generously shared his

time and knowledge with me.

My special thanks to lecturers who have given knowlegde and guidance

during my study, staff members of FKA especially Department of Geothechnics and

Transportation for their help and assistance.

Million words of thanks to my parents, sisters, brothers, and my beloved for

their support and encouragement in all my life. Big thanks for MAP classmates and

best friends who showed their concern and support all the way. Unfortunately, it is

not possible to list all of them in this limited space.

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ABSTRACT

The quality of road surface and its facility will relate to performance

evaluation, which relies on measures of performance quality, often stated in quality

of roadway service (QRS). One of the facilities that available in highway outside the

carriageway is road furniture, including road lighting. The availability of road

lighting in highway helps driver at night time driving. Road lighting be expected can

make road can be functioned in night time as well as drive in daytime. This study

will compare QRS of two scenarios – day light condition and road light condition –

in dry weather. QRS can be estimated by comparing 85th

and 15th

percentiles of

cumulative speed distribution. Roadway capacity during daylight is estimated

approximately 2096 pcu/hr/ln, while during road lighting the roadway capacity is

2154 pcu/hr/ln. The 15th

percentile speed during day light is 61 km/hr, decreasing to

59 km/hr during road lighting condition. The 85th

percentile speed during day light

and road lighting are 88 km/hr and 85 km/hr respectively. Statistical test result

shown that the difference of 85th

and 15th

percentile speed during day light and road

lighting condition was statistically not significant. Optimum speed during daylight is

46.17 km/hr, while during road lighting is decrease to 44.42 km/hr. Since speed is a

distributed parameter, a variance within 32.67 km/hr to 59.67 km/hr for the speed

can be neglected and QRS assumed not affected. It shows that QRS under proper

standard lighting system is not affected significantly compare to the daylight

condition.

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ABSTRAK

Kualiti permukaan jalan dan kemudahan yang berkaitan dengan penilaian

prestasi, bergantung kepada prestasi kualiti yang diukur, yang dinyatakan dalam

kualiti perkhidmatan jalan (QRS). Salah satu kemudahan yang disediakan di luar

laluan lebuh raya adalah perabot jalan, termasuk lampu jalan. Penggunaan lampu

jalan di lebuh raya membantu pemandu di waktu malam. Lampu jalan dijangkakan

boleh membuat jalan berfungsi pada waktu malam serta pemanduan di siang hari.

Kajian ini akan membandingkan QRS bagi dua senario – keadaan siang dan keadaan

malam pada cuaca kering. QRS boleh dianggarkan dengan membandingkan 85 dan

15 persentil agihan laju kumulatif. Kapasiti jalan raya pada waktu siang hari

dianggarkan kira-kira 2096 pcu/hr/ln, manakala semasa malam hari kapasiti jalan

2154 pcu/hr/ln. Kelajuan 15 persentil semasa siang hari adalah 61 km/hr,

berkurangan kepada 59 km/hr dalam keadaan malam hari. Kelajuan 85 persentil

semasa siang hari dan malam hari, masing-masing adalah 88 km/hr dan 85 km/hr.

Keputusan ujian statistik menunjukkan bahawa perbezaan kelajuan 85 dan 15

persentil semasa siang hari dan keadaan malam hari adalah tidak signifikan secara

statistik. Kelajuan optimum pada waktu siang hari adalah 46,17 km/hr, manakala

semasa malam hari menurun kepada 44,42 km/hr. Oleh kerana kelajuan adalah

parameter teragih, varians untuk kelajuan dalam lingkungan 32,67 km/hr hingga

59,67 km/hr boleh diabaikan dan QRS dianggap tidak terjejas. Ini menunjukkan

bahawa QRS pada malam hari di bawah sistem lampu piawaian yang betul tidak

terjejas dengan ketara berbanding dengan keadaan siang hari.

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TABLE OF CONTENTS

CHAPTER TITLE PAGE

DECLARATION ii

DEDICATION iii

ACKNOWLEDGEMENTS iv

ABSTRACT v

ABSTRAK vi

TABLE OF CONTENTS vii

LIST OF TABLES xii

LIST OF FIGURES xiv

LIST OF APPENDICES xvi

LIST OF SYMBOLS AND ABBREVIATIONS xvii

1 INTRODUCTION 1

1.1 Introduction 1

1.2 Statement of the Problem 2

1.3 Aim and Objective of the Study 3

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1.4 Scope 3

1.5 Significant of the Study 4

2 LITERATURE REVIEW 5

2.1 Introduction 5

2.2 Road Lighting 5

2.2.1 Objectives of Road Lighting 5

2.2.2 Road Lighting Terminology 6

2.2.2.1 Photometric Terms 6

2.2.2.2 Installation Terms 7

2.3 Traffic Stream Parameter 10

2.3.1 Volume and Rate of Flow 10

2.3.2 Speed 12

2.3.3 Density 14

2.3.4 Relationship of Flow, Speed, and

Density

14

2.4 Greenshield’s Macroscopic Stream Model 15

2.5 Roadway Capacity 17

2.5.1 Passenger Car Equivalent 18

2.6 Level-of-Service 20

2.6.1 Level-of-Service Based on Highway

Capacity Manual

20

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2.6.2 Level-of-Service Based on Malaysian

Standard

21

2.7 Factors Affecting Capacity and Quality of

Roadway Service

22

2.8 The 85th

and 15th

Percentile Speeds 24

2.8.1 Asymptotic Distribution of Sample

Quantiles

25

2.8.2 Asymptotic Distribution of 85th

Sample

Quantile From The Normal Distribution

26

2.9 Linear Regression 27

3 METHODOLOGY 28

3.1 Introduction 28

3.2 Data Requirement 28

3.3 Location Selected 29

3.4 Data Collection 30

3.4.1 Data Collection Equipments 30

3.4.2 Data Collection Method 30

3.4.3 Data Extraction 31

3.4.4 Data Collection Time 32

3.5 Study Hypotheses 33

3.6 Data Analysis 33

3.7 Summary 35

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4 FINDINGS 36

4.1 Introduction 36

4.2 Site Characteristics 36

4.2.1 Site Geometry 36

4.2.2 Road Lighting Geometry 37

4.3 Existing Data 37

4.3.1 Traffic Proportion 37

4.3.2 Peak Hour 38

4.3.2 Period for Comparison 40

4.4 Data Analysis 42

4.4.1 85th

and 15th

Percentile Speeds 42

4.4.2 Flow, Speed, Density of Traffic 45

4.4.3 Flow – Density Relationship During Day

Light

51

4.4.4 Flow – Density Relationship During

Road Lighting

54

4.4.5 Speed – Flow Relationship During Day

Light

57

4.4.6 Speed – Flow Relationship During Road

Lighting

59

4.5 Comparison of Model 61

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5 CONCLUSIONS AND RECOMMENDATIONS 68

5.1 Conclusions 68

5.2 Recommendations 69

REFERENCES 70

APPENDICES 72 - 80

xii

LIST OF TABLES

TABLE NO. TITLE PAGE

2.1 Absolute Minimum Setback 8

2.2 Projection Length 9

2.3 Conversion Factors to p.c.u 19

2.4 ARX Classification Scheme 19

2.5 Definition of level of service (LOS) for highways 21

3.1 Vehicle Classification 32

4.1 Selected Dates for Analysis 42

4.2 Speed Statistics for Day Light Condition 43

4.3 Speed Statistics for Road Light Condition 43

4.4 Speed Statistics 45

4.5 Speed – Flow – Density Data on May 31, 2010 46

4.6 Speed – Flow – Density Data on June 1, 2010 46





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4.20 Result of Statistical Test on 85th

Percentiles Speed 61

4.21 Result of Statistical Test on 15th

Percentiles Speed 62

4.22 Day Light VS Road Lighting 62

4.23 Result of Statistical Test Day Light VS Road Lighting 67

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LIST OF FIGURES

FIGURE NO. TITLE PAGE

1.1 Site Map 4

2.1 Lantern Projection Length 9

2.2 Greenshield’s Speed – Density Model 15

2.3 Speed vs. Density Diagram 16

2.4 Flow vs. Density Diagram 16

2.5 Speed vs. Flow Diagram 17

3.1 Automatic Traffic Count (ATC) 30

3.2 ATC in Study Site 31

3.3 Flow – Density Relationship 34

3.4 Flow Chart of the Study 35

4.1 Traffic Proportion 38

4.2 AM Peak Hour 39

4.3 PM Peak Hour 40

4.4 Vehicle Flow 41

4.5 Vehicle Flow Typical Pattern 41

4.6 Comparative of Cumulative Speed Distribution Curve 44

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4.7 Regression Parameter of Flow – Density During Day Light 51

4.8 Flow – Density Diagram Day Light Condition 52

4.9 Flow – Density Scatter Diagram During Day Light

Condition

53

4.10 Flow – Density Relationship During Day Light Condition 53

4.11 Regression Parameter of Flow – Density During Road

Lighting

54

4.12 Flow – Density Diagram Road Lighting Condition 55

4.13 Flow – Density Scatter Diagram During Road Lighting

Condition

56

4.14 Flow – Density Relationship During Road Lighting

Condition

56

4.15 Speed – Density Relationship Under Day Light Condition 58

4.16 Speed – Flow Relationship During Day Light 59

4.17 Speed – Density Relationship Under Road Lighting

Condition

60

4.18 Speed – Flow Relationship During Road Lighting 61

4.19 Flow – Density Comparison 63

4.20 Transformation Diagram of Flow – Density 64

4.21 Speed – Flow Comparison 65

4.22 Acceptable Speed Range 66

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LIST OF APPENDICES

APPENDIX TITLE PAGE

A ATC Data 72

B Vehicle Count 77

C Statistical Analysis 80

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LIST OF SYMBOLS AND ABBREVIATIONS

a Deceleration rate

AASHTO American Association State Highway Transportation Officials

ADT Average Daily Traffic (veh)

ATC Automatic Traffic Count

B.S British Standards

cd Candela

CI Confidence Interval

d Distance travelled (km)

FFS Free-Flow Speed (km/h)

ft Foot

h hour

H1 Alternative hypothesis

HCM Highway Capacity Manual

HGV Heavy Goods Vehicle

Ho Null hypothesis

JKR Jabatan Kerja Raya

k Density (veh/km)

kc Critical density (veh/km)

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kj Jam density (veh/km)

km Kilometer

lm Lumen

LOS Level of Service

lx Lux

m Meter

mi Mile

M.S Malaysian Standards

n Number of observed vehicles

PCE Passenger Car Equivalent

p.c.u Passenger Car Unit

PHF Peak-Hour Factor

PI Prediction Interval

q Flow (veh/h)

qm Maximum flow (veh/h)

SE Standard Error

ti Time for vehicle i to traverse d (h)

tp-r Perception-Reaction Time (sec)

TRRL Transport and Road Research Laboratory

u Speed (km/h)

uf Free-flow speed (km/h)

uo Optimum speed (km/h)

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Space mean speed (km/h)

Time mean speed (km/h)

UTM Universiti Teknologi Malaysia

Vd Design speed (km/h)

veh Vehicle

x Length of road (km)

CHAPTER 1

INTRODUCTION

1.1 Introduction

Highway is the important aspect in life because it supports people movement

to do their daily activity. It is also the important aspect in economic growth in a

country. Economic growth can be directly related to the highways such as

transportation of goods from factory to be distributed, people activity to go to work,

or even family trip to recreational place.

Road lighting is an important infrastructure facility. Initially, lighting was to

enable pedestrians to move about in cities at night without being attacked. Currently

road lighting installed because of its ability to reduce night time accident and driver

comfort (Holmes; 1997). Moreover, road lighting has function to illuminate

adequately the road surface and objects on the road and its surrounding areas to be

visible enough to ensure that the driving task is performed successfully (Aleksanteri

E. et al., 2008). From engineer’s point of view, primary object of road lighting is to

improve the safety of roads at night by providing good visibility conditions for all

road users.

A good highway makes it possible for user to ride safely and comfortably at

the design speed. The quality of road surface and its facility will relates to

performance evaluation, which traffic engineers can rate operating characteristics of

individual section of roadway and facilities as a whole in relative terms. Evaluation

relies on measures performance quality, often stated in level of service. The Highway

2

Capacity Manual (HCM) defines highway level of service as a qualitative measure

describing operational conditions within a traffic steam, as perceived by motorist

(Transportation Research Board; 2000). Level of service (LOS) divide into six levels,

which range from A to F, separated by different value of measurement which is

traffic density, volume-to-capacity (v/c) ratio, and average speed. However, the level

of which these level of service are according to motorists’ perception in USA. In

Malaysia, quality of service can be measured from speed – volume relationship. In

essence, by comparing 85th

and 15th

percentiles of cumulative speed distribution of

roadway under day light and road lighting condition, the quality of roadway service

can be estimated.

Greenshield (1934) method can be used to determine the optimum speed and

free-flow speed as the parameter to describe quality of roadway service. Traffic

condition and roadway condition have a strong influence on vehicles’ speed. One of

the most significant factors of road condition is visibility for the road user. Road light

has important part in night time to provide visibility.

1.2 Statement of the Problem

Activity of the people is not restricted only in daytime, but people still doing

their activity in night time. Night time driving can be a particularly problem. The US

Department of Transportation (USDOT) and The National Highway Transportation

Safety Administration (NHTSA) both report show that 27% of total crashes occur

under dark condition, 45% of fatalities occur under dark condition (NTHSA; 2003).

Those problems occur relates to good visibility for road user which can influence

driver’s behaviour. Previous study found no change in average speed when road

lighting was introduced, while other show contrary (Anais M. et al., 2010).

Most of previous study of road lighting usually related to traffic safety and

accident prevention. Only limited study has been made to investigate effect of road

lighting to the quality of roadway service (QRS). QRS should be considered under

3

road lighting condition to compare with the control QRS when it is under daylight

condition.

In a low traffic volume situation, driver’s selection of speed usually

influenced by factor such as the road geometry, lighting and weather condition,

(Othman C.P., 2004). The availability of road lighting in highway helps driver at

night time driving. Although vehicles have their own headlight, but road lighting still

needed. Road lighting provides visibility, helps driver to get enough visual

information throughout driving. Road lighting be expected can make road can be

functioned in night time as well as drive in daytime. Because of that, study will

mitigate the impact of road lighting on the QRS.

1.3 Aim and Objective of the Study

The aim of the study is to determine the extent of road lighting impact on the

quality of roadway service.

The objectives of this study are:

a) To determine the 85th

and 15th

percentile speed distribution for roadway with

and without road lighting.

b) To compare the outcomes from the two scenarios.

c) To determine speed / flow plot points from estimated flow / density functions.

d) To compare the outcomes from speed / flow graphs from the two scenarios.

1.4 Scope

Scope of the study will be focused to determine QRS of the section of

Skudai-Pontian Highway. QRS of highway section will be in two different

conditions, day light during day time and road lighting during night time, to know

4

the impact of road lighting. The study will provide traffic data including volume and

speed for that section of highway during 3 weeks continuously. Roadway type and

geometry, and other important information in study location shall be collected.

Section of highway for this study is started from interchange of Jalan

University and Skudai-Pontian highway and ended in Jalan Pontian Lama exit ramp.

This segment of road is 1.7 km length with no sharp curve.

Figure 1.1: Site Map

Site location should be based on criteria so that the data is not affected by other

factor. The criteria for site for this study are:

roadway should be in level terrain, not hilly terrain

roadway should not influenced by attractions and intersection

1.5 Significant of the Study

Result of this study will provide models of traffic pattern during daylight and

road lighting condition. Models will be use to verify whether road lighting has

impact on QRS, provided the road lighting are operated based on design standard and

road surface is free from surface defect.

REFERENCES

Ahmed F. Al-Khaisy et al. Effect of Darkness on the Capacity of Long Term

FreewayReconstruction Zones. Department of Civil Engineering McMaster

University, Ontario, Canada.

Aleksanteri Ekrias, Marjukka ELoholma, Liisa Halonen, Xian-Jie Song, Xin Zhang,

Yan Wen, Road Lighting and Headlights: Luminance Measurements and

Automobile Lighting Simulation, Journal of Building and Environment (43).

2008.

Anais Mayeur, Roland Bremond, J.M. Christian Bastien. Effect of the Viewing

Context on Target Detection. Implications for Road Lighting Design, Journal

of Applied Ergonomics (41). 2010.

Carlos Sun, Yi Hou, Praveen Edara. A Statical Test for 85th

and 15th

Percentile

Speeds Using the Asymptotic Distribution of Sample Quantiles. University of

Missouri – Columbia. 2011.

Hildebrand, E.D., et al. Speed Management Strategies for Rural Temporary Work

Zones. In Proceedings of Canadian Multidisciplinary Road Safety Conference

XIII, Banff, Alberta. June 8-11, 2003.

Institute of Transportation Engineers. Traffic Engineering Handbook 3rd

Edition.

Prentice-Hall, Pearson Education, NJ. 2004.

Jabatan Kerjaraya Malaysia. A Guide on Geometric Design of Roads. ArahanTeknik

(Jalan) 8/86.

71

Jiang Yongqin et al. Traffic Safety and Road Lighting Evenness Influence. Harbin

University of Science and Technology, Harbin. 2007.

Khisty, C. Jotin, B. Kent Lall. Transportation Engineering – An Introduction 2nd

Edition, Prentice-Hall. Pearson Education. NJ. 1998.

Mace, D.J., and Porter, R.L. Fixed Roadway Lighting: The Effect of Lighting

Geometry and Photometry on Target Visibility and Driver Comfort. Presented

at the 83rd

Transportation Research Board Annual Meeting, 2004.

Mattox, J.H. et al. Development and Evaluation of Speed-Activated Sign to Reduce

Speeds in Work Zones. In Transportation Research Record: Journal of the

Transportation Research Board, No. 2015, Transportation Research Board of

the National Academies, Washington, D.C., 2007.

Nicholas J. Garber, Lester A. Hoel. Traffic and Highway Engineering 3rd

Edition.

CL-Engineering 2001.

Othman Che Puan, Che Ros Ismail. Driver’s Car Following Headway on Single

Carriageway Roads. Universiti Teknologi Malaysia. 2004.

R. W. Holmes. The Purpose of Road Lighting. CIE Division 4, Department of

Transport, NASA Astophysics Data System.1997.

Transportation Research Board. Highway Capacity Manual. National Research

Council. Washington, D.C. 2000.

Technical Committee LGL/23, British Standard EN 5489-1 :Road Light Guide to the

General Principles,Bsi. 1998

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