1. Data Collection Technologies for Road Management Brown Bag Lunch Presentation 4 May 2005 Christopher R. Bennett EASTR

2. Introduction

3. Project Objectives  Give an overview of technologies available to collect data on l Pavements l Bridges l Traffic Volume and Weight  Provide information to managers to help l Establish an appropriate data collection program l Procure appropriate equipment

4. Project Details  Funded by TRISP  Group Effort l C.R. Bennett (World Bank) l H. de Solminihac/A. Chamorro (Catholic University Chile) - Pavements l G. Flintsch/C. Chen (Virginia Tech) - Bridges and Traffic l Conducted research and user surveys  Outputs: l Report l www.road-management.info

5. Road Management Data Project Focus

6. Categories of Data  Inventory l Physical elements of system l Do not change markedly over time Typically measured in ‘ one off ’ exercise and updated Typically measured in ‘ one off ’ exercise and updated  Condition l Change over time l Require regular (or irregular) monitoring

7. What to Collect?  Foundational question  Decision often based on Wish list ( “ nice to have ” ) Wish list ( “ nice to have ” ) l Existing or historical data collection processes  Can lead to data collection becoming an end in itself  Excessive or inefficient data collection could compromise project

8. Recommended Approach  Collect only the data you need  Collect data to the lowest level of detail sufficient to make an appropriate decision  Collect data only when they are needed  Use pilot studies to test the appropriateness of the approach

9. Information Quality Levels

10. Survey Frequency  Inventory Data l One off exercise l Updated/verified ~5 years  Pavement Condition Data l Main roads 1-2 years l Minor roads ~2-5 years  Bridge Condition Data l Regular surveys 1-2 years l Intensive surveys ~5 years  Traffic Data l Permanent count stations (24/7/365) l Short-term count stations (~ 1 - 7 days)

11. Location Referencing

12. The Most Important Issue  Unless properly referenced, data will be of limited use  Two elements: l The location l The address used to identify the location  Three components: l Identification of a known point (eg km stone) l Direction (ie increasing/decreasing) l Distance measurement (ie displacement/ offset)

13. One Location - Many Addresses

14. Linear Referencing  Most common  Different methods l Kilometre point (e.g., 9.29) l Kilometre post (e.g., 9.29 with equations) l Reference point (e.g., xx + 0.29) l Reference post (e.g., xx + 0.29)

15. Spatial Referencing  Latitude/Longitude  Usually measured with GPS l Accuracy typically 95% +/- 10 m  Improved through differential correction or post-processing l Survey issues will typically give accuracy +/- 1 m  Recorded in WGS84 datum and so usually needs to be converted to local co-ordinate system

16. Example of Projection Problem

17. GPS Topological Corrections

18. Pavement Data Collection

19. Pavement Data Framework

20. Measurement Equipment Types

21. Multi-function Systems  Measure multiple attributes in a single pass  Most cost effective and reduces location referencing issues  Two groups: l Portable systems: installed in any vehicle l Dedicated systems: custom instrumented vehicle  Portable usually cheaper and more sustainable but sophisticated measurements require dedicated vehicle

22. Location Referencing  Digital DMI (< $1 k)  GPS (< $1 – 10 k)  GPS with Inertial System (< $2 - 15 k)

23. Video Logging

24. Geometry  Combine GPS and precision gyroscopes/ inclinometers (> $50k)  Precise 3-D measurements including cross-fall

25. Roughness  ‘ Bumpiness ’ of road  Usually related to servicability but also reflects structural deterioration  Affects VOC, safety, comfort, speed  Most commonly expressed as IRI  IRI simulates response of ‘ Quarter-car ’ to road profile

26. Types of Equipment

27. Roughness Measurements Class I Class III

28. Variability Between Class I Instruments 2.5 IRI (m/km) 3.5

29. Comparison of Footprints

30. Texture  Measurements focus on microtexture and macrotexture  High speed measurements use lasers  Expressed as the MPD or SMTD

31. Texture Measurements Macrotexture Microtexture

32. Skid Resistance  Primarily function of surface texture  Tire contact with texture creates ‘ grip ’ under wet conditions  Speed has impact l < 70 km/h: microtexture dominates l > 70 km/h: macrotexture important  Measured indirectly by operating wet tire on pavement  Often expressed as IFI

33. Skid Resistance Measurements Dynamic Static

34. Structural Capacity  Destructive techniques l Coring l DCP  Non-destructive techniques l Deflection measurements

35. Deflectometers Trailer FWD Vehicle FWDPortable

36. Benkelman Beam

37. Ground Penetrating Radar

38. Surface Distresses  Performed manually or with automated equipment  Includes: l Cracking l Surface Defects l Deformations  Great variation in measures used between countries

39. Distress Measurements

40. Video Distress Analysis

41. Current Situation – Video Distress  A number of successful commercial systems  Some degree of human intervention required  Systems usually expensive (> $200 k) and require dedicated vehicles with supplemental lighting  Technology ‘ evolving ’

42. Rut Depths  Measured using discrete sensors (ultrasonic/laser) or line  Data analyzed to simulate rut depth under a straight edge  Systematic under- recording with discrete sensors

43. Selecting Equipment  Used multi-criteria analysis based on survey and literature review

44. Cost/Performance Matrix

45. Traffic Data

46. Types of Traffic Equipment  Generally two components l Sensor l Data Logger  Different technologies for different purposes

47. Classifications  Based on number of axles and axle spacings or length  Different countries have different systems  Important to be able to set up for local vehicle fleet

48. Data Produced by Different Sensors

49. Examples of Sensors Inductance Loop Video Detection

50. Manual Counters

51. Vehicle Weighing Equipment Static Plate Capacitance Pad

52. WIM Classifications  Type I – high accuracy data collection systems (typically bending plate scale type WIM);  Type II – lower cost data collection systems (typically piezoelectric scale type WIM);  Type III – systems for use in a sorting application at weigh station entrance ramps (bending plate or deep pit load cell type WIM) at speeds from 15 to 50 mph;  Type IV – low-speed WIM

53. Suitability Rankings