EXTENT OF ROAD LIGHTING IMPACT ON HIGHWAY CAPACITY NIMA JAHANDAR

EXTENT OF ROAD LIGHTING IMPACT ON HIGHWAY CAPACITY NIMA JAHANDAR A project report submitted in partial fulfillment of the requirement for the award of the degree of Master of Engineering (Civil Transportation and Highway) Faculty of Civil Engineering Universiti Teknologi Malaysia May 2011

To my beloved mother and father, Fariba and Mojtaba iii

iv ACKNOWLEDGMENT This handbook could not have been written without help of my supervisor Associate Professor Dr. Johnnie Ben-Edigbe, who encouraged and challenged me through my academic program. A special thanks to all the authors mentioned in the references section for materials collected in this handbook that I found in articles or in books. Without you, this handbook would have taken years off my life. Thanks to my friend, classmate and also teacher, Nur Hidayah, for translating some materials to English and also some into Behasa Melayu. Thanks to all my fellow friends and MAP classmates specially Mehrdad, Ali, Ida and Neema for their support. Finally I state million words of thanks to my parents for their kindness and patience and to my sisters, Nassim and Negin, for their support and encouragement in almost all aspects of my life.

v ABSTRACT As roads are very scarce and costly to build, it is needed to use their maximum capacity at a reasonable serviceability. Clearly, to achieve this goal, roadways should be studied in different conditions in order to provide certain facilities. This study examines the impact of road lighting on roadway capacity during night-time under the road lightings and to compare to its original capacity when there is natural day light. Data for this study was collected from a two-lane urban highway 5 near Universiti Teknologi Malaysia in Johor state of Malaysia. A pneumatic loop detector was installed for 3 weeks to record volume and speed of the traffic 24 hour. The data was filtered to avoid adverse weather conditions and congestions. Data related to off-peak uncongested conditions during daylight and lighting were analysed to see the effect of road lighting. Capacity of study route estimated 2665 pc/h/ln during daylight. In addition, during lighting hours, maximum flow is estimated 2364 pc/h/ln which is approximately 11% reduction compare to daylight. Meanwhile free-flow speed and optimum speed computed during study and results show minor changes. Free-flow speed and optimum speed computed 85 km/h and 42 km/h, respectively, for both daylight and lighting hours.

vi ABSTRAK Oleh kerana pembinaan jalan adalah sangat sukar dan mahal, ianya amat memerlukan penggunaan kapasiti yang maksimum pada satu nilai yang munasabah. Bagi mencapai sasaran yang diingini, laluan kenderaan haruslah dikaji mengikut keadaan yang berbeza bagi menyediakan kemudahan tertentu. Kajian ini dijalankan bagi memeriksa kesan pencahayaan jalan terhadap kapasiti laluan jalan ketika waktu malam di bawah pencahayaan lampu dan membandingkannya dengan kapasiti penggunaan ketika waktu siang. Data untuk kajian ini diperolehi daripada satu lebuh raya bandar dua lorong 5 berhampiran Universiti Teknologi Malaysia di negeri Johor. Satu Pengesan gelung pneumatik telah dipasang selama 3 minggu bagi merekodkan jumlah dan kelajuan trafik 24 jam. Data telah disaring untuk mengelak keadaan cuaca yang buruk dan juga kesesakan.data berkaitan dengan kesesakan luar musim ketika waktu siang dan penggunaan lampu dianalisis bagi melihay kesan penggunaan lampu jalan. Keupayaan laluan kajian mengira 2665 pc/h/ln semasa siang. Sebagai tambahan, semasa menerangi jam, aliran maksimum ialah dianggarkan 2364 pc/h/ln yang mana dianggarkan kira-kira 11% pengurangan berbanding dengan waktu siang. Sementara itu kelajuan aliran bebas dan kelajuan optimum mengira semasa kajian dan keputusan menunjukkan perubahan kecil. Kelajuan aliran bebas dan kelajuan optimum yang diukur adalah 85 km/h dan 42 km/h, masing-masing, untuk waktu siang dan malam.

TABLE of CONTENTS ABSTRACT (English) ABSTRAK (Behasa Melayu) TABLE OF CONTENTS LIST OF FIGURES LIST OF TABLES LIST OF APPENDICES LIST OF SYMBOLS AND ABBREVIATIONS v vi vii x xii xiv xv CHAPTER ONE INTRODUCTION 1 1.1. Background of the Study 1 1.2. Problem Statement 2 1.3. Purpose and Objectives of the Study 3 1.4. Significance of the Study 4 1.5. Scope and Limitations of the Study 4 CHAPTER TWO LITERATURE REVIEW 6 2.1. Introduction 6 2.2. Road Classification 7 2.3. Road Lighting 9 2.3.1. Road Lighting Objectives 9

viii 2.3.2. Road Lighting Terminology 11 2.3.2.1. Photometric Terms 11 2.3.2.2. Installation Terms 12 2.3.3. Geometry of Road Lighting 17 2.4. Traffic Flow Theory 17 2.4.1. The Principal Parameters 17 2.4.2. The Fundamental Relationship 20 2.4.3. Macroscopic Stream Models 20 2.4.4. Greenshield s Model Development 23 2.5. Estimation of Roadway Capacity 25 2.5.1. Capacity Estimation Methods 25 2.5.2. Average Speed 27 2.5.3. Headway and Spacing 28 2.5.4. Passenger Car Equivalent 29 2.6. Peak Hour Factor 30 2.7. Linear Regression 31 2.8. Automatic Traffic Count 32 2.9. Stopping Sight Distance 33 CHAPTER THREE METHODOLOGY 35 3.1. Introduction 35 3.2. Data Requirements 36 3.3. Selection of the Location 37 3.4. Data Collection 38 3.4.1. Data Collection Equipments 38 3.4.2. Data Collection Method 40 3.4.3. Data Extraction 41 3.4.4. Data Collection Time 42 3.5. Study Hypotheses 43 3.6. Analysis 43 3.7. Summary 46

ix CHAPTER FOUR RESULTS AND ANALYSIS 47 4.1. Introduction 47 4.2. Roadway Characteristics 48 4.2.1 Roadway Geometry 48 4.2.2. Lighting System Geometry 50 4.2.3 Stopping Sight Distance 54 4.3. Demand Data 57 4.3.1. Traffic Proportions 57 4.3.2. Weather Reports 58 4.3.3. Peak Hour 59 4.3.4. Proposed Periods for Comparison 60 4.3.5. Flow, Speed and Density of Traffic 62 4.4. Data Analysis 69 4.4.1. Density Flow Relationship during Daylight 69 4.4.2. Density Flow Relationship during Lighting 73 4.4.3. Parametric Comparison of Models 76 4.4.4. Headways 80 4.4.5. Roadway Characteristics Dispersion Plots 83 CHAPTER FIVE CONCLUSIONS AND SUGGESTIONS 86 5.1. Findings 86 5.2. Other Findings 87 5.3. Suggestions for Further Works 87 REFERENCES 89 APPENDICES 93

x LIST of FIGURES 1.1 Site Map 5 2.1 Road Lighting System 13 2.2 Road Lighting Arrangement 14 2.3 Lantern Projection Length 16 2.4 Traffic Levels 19 2.5 Greenshiled s Speed Density Model 21 2.6 Greensberg s Speed Density Model 22 2.7 Underwood s Speed Density Model 22 2.8 Density vs. Speed Diagram 23 2.9 Density vs. Flow Diagram 23 2.10 Flow vs. Speed Diagram 23 3.1 Pneumatic Road Tube and Recorder 39 3.2 In-site View 39 3.3 Automatic Traffic Counter in Site 41 3.4 Scatter Plot k-u 44 3.5 Scatter Plot k-q 44 3.6 Maximum Flow 45 3.7 Flow Chart of the Study 46 4.1 Roadway Plan View 48 4.2 Carriageway 48 4.3 Spacing 50 4.4 Illumination Satisfactory Range 51 4.5 Lighting Column Dimensions 53 4.6 Speed Histogram 55 4.7 Posted Speed Limit 56 4.8 Lighting Phases 56

xi 4.9 Traffic Proportions Chart 57 4.10 Noon Peak 59 4.11 p.m. Peak 60 4.12 Vehicle Flow 61 4.13 Vehicle Flow Typical Pattern 61 4.14 Density vs. Flow Diagram 70 4.15 Daylight Residual Plot 71 4.16 Scatter Data during Daylight 72 4.17 Density Flow Full Diagram during Daylight 72 4.18 Density vs. Flow Diagram 74 4.19 Lighting Residual Plot 74 4.20 Scatter Data during Lighting 75 4.21 Density Flow Full Diagram during Lighting 76 4.22 Density Flow Comparison 77 4.23 Negligible Range 78 4.24 Density Flow Diagram Transformation 79 4.25 Free-Flow and Optimum Speeds 80 4.26 Headway Histogram during Daylight 82 4.27 Headway Histogram during Lighting 82 4.28 Density vs. Speed Diagram during Daylight 83 4.29 Density vs. Speed Diagram during Lighting 83 4.30 Density vs. Flow Diagram during Daylight 84 4.31 Density vs. Flow Diagram during Lighting 84 4.32 Flow vs. Speed Diagram during Daylight 85 4.33 Flow vs. Speed Diagram during Lighting 85

xii LIST of TABLES 2.1 Road Hierarchy 9 2.2 Absolute Minimum Setback 15 2.3 Projection Length 16 2.4 Conversion Factors to p.c.u. 29 2.5 ARX Classification Scheme 30 3.1 Vehicle Classification 42 4.1 Sunset Time 52 4.2 Speed Statistics 54 4.3 Minimum Stopping Sight Distance 55 4.4 Study Area Weather Conditions 58 4.5 Selected Dates 62 4.6 May 31, 2010 64 4.7 June 1, 2010 64 4.8 June 2, 2010 64 4.9 June 3, 2010 65 4.10 June 4, 2010 65 4.11 June 7, 2010 65 4.12 June 8, 2010 66 4.13 June 9, 2010 66 4.14 June 10, 2010 66 4.15 June 11, 2010 67 4.16 June 14, 2010 67 4.17 June 15, 2010 67 4.18 June 16, 2010 68 4.19 June 17, 2010 68 4.20 June 18, 2010 68

xiii 4.21 Daylight Density Flow Regression Parameters 69 4.22 Lighting Density Flow Regression Parameters 73 4.23 Extremes Values 77 4.24 Headway Frequency 81

xiv LIST of APPENDICES APPENDIX A 93 SAMPLE CALCULATIONS APPENDIX B 97 VEHICLE COUNT APPENDIX C 102 WEATHER REPORTS APPENDIX D-1 112 VARIABILITY OF COLLECTED DATA DURING DAYLIGHT APPENDIX D-2 115 VARIABILITY OF COLLECTED DATA DURING LIGHTING APPENDIX E STATISTICAL ANALYSIS 119

xv LIST of SYMBOLS and ABBREVIATIONS a Deceleration Rate (m/sec 2 ) 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 G Longitudinal Grade of the Road h Height (m) h Hour H Time Headway (sec) H a HCM HGV H o ITE JKR k k cr k j km lm Alternative Hypothesis Highway Capacity Manual Heavy Goods Vehicle Null Hypothesis Institute of Transportation Engineers Jabatan Kerja Raya Density (veh/km) Critical Density (veh/km) Jam Density (veh/h) Kilometer Lumen

xvi LOS lx m mi M.S. n ODOT PCE p.c.u. PHF PI q q i q m R 2 SE SSD SS error SS reg SS total t i t p-r TRL, TRRL u u u f u o u S u T UTM V d veh x Level Of Service Lux Meter Mile Malaysian Standards Number of Observed Vehicles Ohio Department of Transportation Passenger Car Equivalent Passenger Car Unit Peak-Hour Factor Prediction Interval Flow (veh/h) Flow Related to Survey i (veh/h) Maximum Flow (veh/h) R-Squared Standard Error Stopping Sight Distance (m) Error Sum of Squares Regression Sum of Squares Total Sum of Squares Time for Vehicle i to Traverse d (h) Perception Reaction Time (sec) Transport and Road Research Laboratory Speed (km/h) Mean Speed (km/h) Free-Flow Speed (km/h) Optimum Speed (km/h) Space Mean Speed (km/h) Time Mean Speed (km/h) Universiti Teknologi Malaysia Design Speed (km/h) Vehicle Length of Road (km)

CHAPTER ONE INTRODUCTION 1.1. Background of the Study One of the most essential issues for a safe and efficient traffic flow on highways is the ability to see for the drivers. However, in many cases, during night-time driving, human eyes limitations prevent vehicle headlights alone from completely satisfying visual requirements. Therefore, help of fixed roadway lighting appears to be useful to supplement vehicle headlights. Fixed roadway lightings extend the visibility range both longitudinally and laterally, thus it helps the driver by providing earlier warning of hazards on or near the roadway [King, L., 1994], moreover, 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 the traffic engineer's viewpoint, the primary objective of road lighting is to improve the safety of roads at night by providing good visibility conditions for all road users. A second reason for installing road lighting is to promote better traffic flow at night, by providing improved delineation of road geometrics, safer overtaking opportunities, and easier observance of traffic management measures.

2 Quality and condition of traffic flow have a strong influence on capacity of the roadway. In Highway Capacity Manual (HCM), highway capacity is defined as the maximum sustained 15 minutes flow rate, expressed in passenger cars per hour per lane, that can be accommodated by a uniform freeway segment under prevailing traffic and roadway conditions in one direction of flow". Observed 15-min flow rate, which is used to estimate highway capacity, may be vary depending on the traffic condition and roadway condition. The factors that affect highway capacity are road condition, traffic flow condition, traffic control condition and automobile technology. One of the most significant factors of road condition is the visibility for the road users. Road lighting plays in lieu of natural day light during night-time to increase visibility to desired level. In addition, not always lighting helps, sometimes a bad design may be worst than no lighting at all [Mace and Porter, 2004]. Some authors have shown that risk compensation in lighted roads may lead to an increase in speed and a decrease of diffuse attention [Wilde, 1984], which may reduce road safety. 1.2. Problem Statement As roads are very scarce and costly to build, it is needed to use their capacity at the highest level. Clearly, to achieve this goal, roadways level of service in different conditions should be examined and certain facilities for road users should be provided. One of the issues to be studied is the extent of road lighting impact on drivers behavior thus roadway capacity. Some studies found no change in average speed when road lighting was introduced, while other showed the contrary [Anais M. et al., 2010].

3 There are too many researches that have been done regarding the effect of road lighting on road safety, rare studies aim for effects of road lighting on capacity. Roadway capacity should be considered while operating under the light of lighting facilities during night-time to compare to its original capacity when there is natural day light. A slight difference in capacity is expected otherwise the roadway s lighting system and pattern should be revised to obtain the desired visibility and thus reduction in capacity loss of the roadway. In a low traffic volume situation, driver s selections of speed is usually influenced by such factors as the road geometry, lighting and weather condition [Othman C.P., 2004], therefore, in a straight segment of road, lighting plays the most significant part in driver s behavior and their desirable speed. On the other hand, road lighting has minor effect to the flow and roadway capacity under the congestion condition. One reason is, in congestion condition, as the space headway decreased so does the speed of vehicles for drivers to retrieve safe time headway. In this situation drivers have enough time to decide what to do when they are seeing an obstacle or changing the lane, having same visibility they have in high speed, when they might been surprised and not have enough time to maneuver smoothly and shock the entire traffic flow. 1.3. Purpose and Objectives of the Study The aim of this study is to determine the extent of road lighting impact on roadway capacity. To achieve this aim the study was carried out upon following objectives:

4 To estimate flow and speed, hence compute density. To use flow and density relationship to determine capacity under day light and dry weather conditions. To use flow and density relationship to determine capacity under road lighting and dry weather conditions. To compare estimated capacities for the two scenarios and draw conclusions. 1.4. Significance of the Study The results of this study will provide models of traffic pattern during daylight and lighting hours. Such models would be useful to verify whether road lighting has impact on the traffic characteristics and as a result the roadway capacity. Consideration of results of this study would help to improve assessments for local roads hence, more accurate and efficient planning and management of resources. 1.5. Scope and Limitations of the Study In order to clarify the extent of road lighting impact on highway capacity, this study will be conducted to compare the capacity of diamond 5 highway namely Lebuhraya Skudai-Pontian under condition of existence of natural day light and lighting during night-time. The study will provide the traffic data including volume and speed of vehicles passing the road during 3 weeks, continuously.

5 Meanwhile, this study appears to suffer from a number of issues, such as changes in the driver populations between night and day, changes in trip motivations, in driver behaviors, etc. For instance, that people driving during darkness and daylight hours are not the same [Assum et al., 1999]. Thus, it is difficult to compare and generalize the findings, and to compensate for the methodological biases [Elvik, 2002]. On the other hand, collected data should present the base condition at which the standard capacity possibly could be estimated. Therefore, both congestion peak hours, bottleneck, vehicle breakdowns, emerging ramps and intersections and adverse weather conditions should be avoided during data collecting phase since previous research shows that adverse weather condition has the same effect on traffic flow as congestion [Alhassan and B. Edigbe, 2011]. The segment of the highway where the study will be carried out is situated to the south of Universiti Teknologi Malaysia. This portion of the road is 1.7 kilometer long and to avoid unwanted issues which discussed before is almost straight with no sharp bend. Study route starts from the grade separated interchange of Jalan Universiti and Skudai-Pontian highway and ends in Jalan Pontian Lama exit ramp. The site of the study is shown in figure (1.1). FIGURE 1.1 Site Map

REFERENCES [1] A. Essam Radwin and Sylvester A. F. Kalevela, Investigation of the Effect of Change in Vehicular Characteristics on Highway Capacity and Level of Service, Transportation Research Record 1005, Transportation Research Board, 1988. [2] Aleksanteri Ekrias, Marjukka Eloholma, Liisa Halonen, Xian-Jie Song, Xin Zhang, Yan Wen, Road lighting and headlights: Luminance measurements and automobile lighting simulations, Journal of Building and Environment (43), 2008. [3] Anais Mayeur, Roland Bremond, J.M. Christian Bastien, Effects of the viewing context on target detection. Implications for road lighting design, Journal of Applied Ergonomics (41), 2010. [4] Anthony Ingle, Development of Passenger Car Equivalents for Basic Freeway Segments, Master s Thesis, Virginia Polytechnic Institute and State University, 2004. [5] Assum, T., Bjornskau, T., Fosser, S., Sagberg, F., Risk compensation - the case of road lighting, Journal of Accident Analysis & Prevention (31), 1999. [6] Box, P.C., Relationship between illumination and freeway accidents. Journal of Illuminating Engineering (5), 1971. [7] Cawangan Elektrik JKR, Specification for Road Lighting Installation, Jabatan Kerja Raya Malaysia, 1999.

90 [8] Coleman A. O'Flaherty, Transport Planning and Traffic Engineering, 4 th ed. Butterworth-Heinemann 1996. [9] Electrotechnical Industry Standards Committee, Malaysian Standard-825: Code of Practice for Design of Road Lighting, Part1 Lighting of Roads and Public Amenity Areas, Department of Standards Malaysia, 2007. [10] Elvik, R., 2002. The importance of confounding in observational before-andafter studies of road safety measures. Journal of Accident Analysis & Prevention (34), 2002. [11] H. Douglas Robertson, Joseph Hummer and Donna Nelson, Manual of Transportation Engineering Studies. 3 rd ed. Institue of Transportation Engineers, 2001. [12] Hashim Mohammed Alhassan, Johnnie Ben-Edigbe, Effect of Rainfall Intensity Variability on Highway Capacity Loss, European Journal of Scientific Research (49), 2011. [13] Indian Institutes of Technology, Traffic Stream Models, NPTEL, 2007. [14] Kiewit Center for Infrastructure and Transportation, Stopping Sight Distance and Decision Sight Distance, Oregon Department of Transportation (ODOT), 2004. [15] King, L Ellis, Human Factors in Traffic Safety Roadway Lighting, 2 nd Ed. Institute of Transportation Engineers, 1994. [16] M. Calori, A. Di Donato, D. Pavanello and A. Pirrotta, Traffic Flow Equations, Politecnico di Milano, Dipartimento di Ingegneria Aerospaziale, 2010.

91 [17] Mace, D.J., and Porter, R.J., 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. [18] Microcom (MetroCount), Classification Schemes, Microcom Pty Ltd, 2009. [19] Minnesota Department of Transportation, Roadway Lighting Design Manual, DoT, 2006. [20] National Research Council, Special Report 209: Highway Capacity Manual, 3 rd ed. Transportation Research Board, Washington, D.C., 1998. [21] Nicholas J. Garber, Lester A. Hoel, Traffic and Highway Engineering. 3 rd ed. CL-Engineering 2001. [22] Nordiana Binti Mashros, Platoon Depression Downstream of Traffic Signal, Master s Thesis, Universiti Teknologi Malaysia, 2007. [23] Othman Che Puan, Che Ros Ismail, Driver s Car Following Headway on Single Carriageway Roads, Universiti Teknologi Malaysia, 2004. [24] Per Ole Wanvik, Effects of road lighting: An analysis based on Dutch accident statistics 1987 2006, Journal of Accident Analysis and Prevention (41), 2009. [25] Richard Chow, Joe Mah and Robert Duckworth, Highway Lighting Giude, Minister of Transportation, Alberta, 2003. [26] Rodrigue, J, C. Comtois and B. Slack, The Geography of Transport Systems, 2 nd ed. New York, Routledge, 2009. [27] Technical Committee CPL/34, British Standard EN 13201-1: Road Lighting - Selection of Lighting Classes, BSi, 2004.

92 [28] Technical Committee CPL/34, British Standard EN 13201-2: Road Lighting - Performance Requirements, BSi, 2003. [29] Technical Committee CPL/34/8, British Standard EN 13201-3: Road Lighting - Calculation of Performance, BSi, 2003. [30] Technical Committee CPL/34/8, British Standard EN 13201-4: Road Lighting - Methods of Measuring Lighting Performance, BSi, 2003. [31] Technical Committee LGL/23, British Standard EN 5489-1: Road Lighting - Guide to the General Principles, BSi, 1998. [32] Technical Committee RDB/28, British Standard EN 5649-2: Specification for Lighting columns - Dimensions and Tolerances, BSi, 1978. [33] Wilde, G.J.S., Target Risk. Dealing with the Danger of Death, Disease and Damage in Everyday Decisions, PDE Publications, Toronto, 1984. [34] Zunhwan, H. Jumsan, K. and Sungmo, R., Development of a New Highway Capacity Estimation Method, Proceedings of the Eastern Asia Society for Transportation Studies, Vol. 5, pp. 984-995, 2005.