1 data Collection Technologies for road management Version February 2007. Christopher R. Bennett Alondra Chamorro Chen Chen Hernan de Solminihac Gerardo W. Flintsch East Asia Pacific Transport Unit The World Bank Washington, data Collection Technologies for road management The World Bank East Asia Transport Unit 1818 H Street NW. Washington, 20433, Tel: (202) 458-1876. Fax: (202) 522-3573. Email: Website: A publication of the World Bank East-Asia Transport Unit sponsored by the Transport and Rural Infrastructure Services Partnership (TRISP). The TRISP-DFID/World Bank Partnership has been established for learning and sharing knowledge. This report is a product of the staff of the World Bank assisted by independent consultants. The findings, interpretations, and conclusions expressed herein do not necessarily reflect the views of the Board of Executive Directors of the World Bank or the governments they represent.
2 The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of the World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. 2 August 2007 ii data Collection Technologies for road management Acknowledgements This report was sponsored by the Transport and Rural Infrastructure Services Partnership (TRISP). The TRISP-DFID/World Bank Partnership has been established for learning and sharing knowledge. Dr. Christopher R. Bennett of the World Bank managed the project and wrote the section on data issues and assisted with the pavement and traffic sections. Prof. Hernan de Sominihac and Ms. Alondra Chamorro from the Catholic University of Chile were primarily responsible for the pavement section.
3 Prof. Gerardo Flintsch and Mr. Chen Chen from Virginia Tech University were responsible for the bridge and traffic sections. The project web site was designed by Mr. Raoul Pop. The draft specifications for data Collection equipment were prepared by Doug Brown and Simon Deakin with input from Tom Thomson and several reviewers and vendors. The project team would like to express its appreciation to the many vendors and users in different countries who contributed to the project and provided data on equipment and their experiences with data Collection . Quality Assurance Statement Report Name: Prepared by: Bennett, A. Chamorro, C. Chen, data Collection Technologies H. de Solminihac, G. Flintsch for road management Reviewed by: R. Archondo-Callao Project Manager: Approved for issue by: Bennett Bennett February 2007. Revision Schedule Reviewed Approved Rev. No Date Description Prepared by by by Updated text based on reviewer feedback.
4 Includes expanded cost/performance matrixes for a 2 5/1/06 HDS/AC CRB CRB. range of road classes. Equipment evaluation includes suitability for HDM analyses. Included annex on pavement 2 8/5/06 HDS/AC TT CRB. strength measurement Includes discussion on generic 2 1/15/07 CRB/DB/SD TT CRB. specifications 2 2/5/07 Included section on validation CRB DB CRB. 2 7/23/07 Fixed page numbering error CRB - CRB. 2 August 2007 iii data Collection Technologies for road management 2 August 2007 iv data Collection Technologies for road management Contents 1 Introduction .. 1. 2 data Collection Issues .. 3. Introduction .. 3. Deciding What to Collect .. 3. Information Quality Levels (IQL).. 5. Sampling Intervals and Sectioning .. 7. Survey Frequency ..10. 3 Location Referencing .. 12. Introduction ..12. Linear Spatial 4 Pavement Condition and Structure .. 23. Types of Evaluations.
5 23. Pavement Characteristics ..24. Texture ..27. Skid Resistance ..29. Mechanical/Structural Properties ..30. Surface Distresses ..31. data Collection Techniques ..32. Location Referencing ..34. road Geometry ..37. Skid Resistance ..44. Mechanical/Structural Properties ..46. Surface Distresses ..53. Rut Depths ..56. Technology Suitability Ranking and Cost/Performance Suitability Evaluation Forms ..60. Suitability Index Calculation ..63. Suitability Ranking ..65. Cost/Performance Matrix ..67. 5 Bridge data Collection .. 73. Introduction ..73. Bridge Inspection Procedures ..74. Bridge Component Inspection and Available Technologies ..74. Timber Concrete Members ..75. 2 August 2007 v data Collection Technologies for road management Steel and Iron Members ..76. Bridge data Collection Equipment ..76. Bridge Access Technologies ..77. Non-destructive Testing (NDT) Technologies .
6 79. Digital Application in Developing Countries ..85. 6 Traffic data Collection .. 87. Introduction ..87. Vehicle Classifications ..90. Traffic Sensor Types ..91. Intrusive Sensors ..92. Non-Intrusive Sensors ..97. Traffic Counting and Vehicle Classification Technologies .. 101. Truck Weighing Technology .. 102. Static Scales .. 105. Weight-in-Motion .. 105. Selecting the Traffic Monitoring 108. Application in Developing Countries .. 109. 7 PROCURING EQUIPMENT .. 115. Introduction .. 115. 115. Generic Specifications for data 117. 8 Conclusions .. 120. Implications for Developing Countries .. 120. Location Referencing .. 121. Pavement data Collection .. 121. Bridge data 123. Traffic data Collection .. 123. 9 References .. 125. ANNEX A: Pavement data Collection Equipment Details .. 130. ANNEX B: Suitability Index Rankings - Equipment .. 139. ANNEX C: Suitability Index Rankings - Roads.
7 154. ANNEX D: Assessing Pavement Structural 158. 2 August 2007 vi data Collection Technologies for road management 1 Introduction When considering the road infrastructure and its associated data , there are different types of data used for road management . Table shows one data grouping from Paterson and Scullion (1990). This report focuses on the first four elements, which have two types of data : Inventory; and Condition. Table : road management data Element Aspects road Inventory Network/Location Geometry Furniture/Appurtenances Environs Pavement Pavement Structure Pavement Condition Structures Structures Inventory Bridge Condition Traffic Volume Loadings Accidents Finance Unit Costs Budget Revenue Activity Projects Interventions Commitments Resources Institutional Materials Equipment Source: Paterson and Scullion (1990). Inventory data describe the physical elements of the road system.
8 These do not change markedly over time. Condition data describe the condition of elements that can be expected to change over time. There are a wide range of Technologies available to the road manager for measuring attributes of the road network. The challenge is to select the appropriate equipment, given local conditions and the way in which the data are expected to be used. The purpose of this report is to give an overview of the currently available Technologies and to provide information that could assist managers in establishing an appropriate data Collection program and procuring the appropriate equipment to collect the data . The project includes a literature review and comprehensive survey of vendors and users, both of which were conducted in 2005. It is recognized that with 2 August 2007 1. data Collection Technologies for road management the rapid developments in road data Collection , some information provided in this project report may become outdated.
9 To address this, we have developed a project web site: This site enables vendors and others involved in road management to upload the latest information on equipment and general data Collection issues. It is envisaged that this report will be reissued and refined on a bi-annual basis. The report starts with a discussion of data Collection requirements. This is then followed by separate discussions on pavements, bridges, and traffic data . The final chapter contains our recommendations for data Collection . 2 August 2007 2. data Collection Technologies for road management 2 data Collection Issues Introduction data Collection is expensive. Each data item collected requires time, effort, and money to collect, store, retrieve, and use. The first rule of data Collection is that data should never be collected because "it would be nice to have the data ," or because "it might be useful someday.
10 ". This section addresses a number of issues that road managers face when determining exactly what their data requirements are and how to select the appropriate data Collection Technologies to meet those requirements. Deciding What to Collect Regarding road management data , the first question usually asked is, "What data should we collect?" Many agencies start by asking an internal team to compile a " data wish list." Other agencies first take inventory of their currently available data and try to implement road management systems using that data . Both approaches should be avoided. The real questions that should be asked are: What decisions do we need to make to manage the network? What data are needed to support these decisions? Can we afford to collect these data initially? Can we afford to keep the data current over a long time period? Several agencies have become so mired in data Collection that data Collection appears to be an end in itself.