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

Introduction

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

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

Road Management Data Project Focus

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

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

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

Information Quality Levels

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 (~ days)

Location Referencing

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)

One Location - Many Addresses

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 ) l Reference post (e.g., xx )

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

Example of Projection Problem

GPS Topological Corrections

Pavement Data Collection

Pavement Data Framework

Measurement Equipment Types

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

Location Referencing  Digital DMI (< $1 k)  GPS (< $1 – 10 k)  GPS with Inertial System (< $ k)

Video Logging

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

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

Types of Equipment

Roughness Measurements Class I Class III

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

Comparison of Footprints

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

Texture Measurements Macrotexture Microtexture

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

Skid Resistance Measurements Dynamic Static

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

Deflectometers Trailer FWD Vehicle FWDPortable

Benkelman Beam

Ground Penetrating Radar

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

Distress Measurements

Video Distress Analysis

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 ’

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

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

Cost/Performance Matrix

Traffic Data

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

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

Data Produced by Different Sensors

Examples of Sensors Inductance Loop Video Detection

Manual Counters

Vehicle Weighing Equipment Static Plate Capacitance Pad

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

Suitability Rankings