Cost-Effective Collection of a Network-Level Asset Inventory. Michael Nieminen, Roadware



Similar documents
Integrating GIS-Based Videolog and Asset Data With Commonly Used Systems Provides Major Benefits With Minimal Effort

GIS DATA CAPTURE APPLICATIONS MANDLI COMMUNICATIONS

USING MOBILE LIDAR TO SURVEY A RAILWAY LINE FOR ASSET INVENTORY INTRODUCTION

IP-S2 HD. High Definition 3D Mobile Mapping System

Monitoring Highway Assets with Remote Technology

automatic road sign detection from survey video

IP-S2 Compact+ 3D Mobile Mapping System

IP-S3 HD1. Compact, High-Density 3D Mobile Mapping System

APPLANIX POSITION AND ORIENTATION SYSTEMS FOR LAND VEHICLES (POS LV)

Types of Data. Features. Getting Started. Integrated Roadway Asset Management System

MobileMapper 6 White Paper

TOPOGRAPHICAL SURVEY REPORT - PART OF L.R No. 7413/11 Done on February 2015 at International Union for Conservation of Nature (IUCN) Eastern African

Apogee Series. > > Motion Compensation and Data Georeferencing. > > Smooth Workflow. Mobile Mapping. > > Precise Trajectory and Direct Georeferencing

Automated Mobile Mapping for Asset Managers

Using Cloud-Computing to Promote Asset Management Best Practices A Ministry of Transportation Ontario Case Study

How To Fuse A Point Cloud With A Laser And Image Data From A Pointcloud

NJDEP GPS Data Collection Standards For GIS Data Development

Guide to the Texas A&M Transportation Institute Mobile Retroreflectometer Certification Program

Intergraph Roadway Information Management Solution. Title Title. Title Title. A White Paper

The Applanix SmartBase TM Software for Improved Robustness, Accuracy, and Productivity of Mobile Mapping and Positioning

Create and share a map with GIScloud.com

sonobot autonomous hydrographic survey vehicle product information guide

Field Techniques Manual: GIS, GPS and Remote Sensing

Global Positioning System (GPS) Automated Vehicle Location (AVL) Geographic Information System (GIS) and Routing/Scheduling System

Legislative Council Panel on Information Technology and Broadcasting. Information Note on the Development of Global Positioning System in Hong Kong


Mobile 360 Degree Imagery: Cost Effective Rail Network Asset Management October 22nd, Eric McCuaig, Trimble Navigation

CITY COUNCIL AGENDA ITEM CITY OF SHORELINE, WASHINGTON

Enabling RTK-like positioning offshore using the global VERIPOS GNSS network. Pieter Toor GNSS Technology Manager

ADA POST INSPECTION CHECKLIST. Job No. Route County Location

SURVEYING WITH GPS. GPS has become a standard surveying technique in most surveying practices

Positioning Aware Solutions for Smart Grid. Enterprise Geospatial & Business Development Manager- GIS DC (Trimble, MEIA Region)

Tracking Vehicles with GPS:

An Innovative Concept to Manage GPS Reference Stations Network and RTK Data Distribution Globally

In 2005, the City of Pasadena, CA, USA, with the support of consultants,

Project Overview Mapping Technology Assessment for Connected Vehicle Highway Network Applications

Installing Tri-Global Software

Global Positioning Monitoring System for Electric Vehicle Fleets (GPMS)

Provide network RTK Services in a few simple steps

Experience Sharing of GPS Trial in Singapore

GPS/INS Integration with the imar-fsas IMU

RF Coverage Validation and Prediction with GPS Technology

Land Mobile Mapping & Survey

Pavement Asset Management Guidance Section 3: Inventory and Data Management

Extending Enterprise GIS Into The Field with Mobile GIS Technology

INDIANA DEPARTMENT OF TRANSPORTATION OFFICE OF MATERIALS MANAGEMENT. MEASUREMENT OF RETRO-REFLECTIVE PAVEMENT MARKING MATERIALS ITM No.

Traffic Sign Management: Data Integration and Analysis Methods for Mobile LiDAR and Digital Photolog Big Data

Road Asset Management

Vehicle and Object Tracking Based on GPS and GSM

Managing Linear Assets with Ventyx Ellipse

To facilitate the trials, MagicSBAS

PERFORMANCE MEASURES FOR MOBILITY MANAGEMENT PROGRAMS

Appendix A - Cost Estimate Spreadsheet

ELEMENTS OF SURVEYING FOR CADASTRAL MAPPING

GPS Based Low Cost Intelligent Vehicle Tracking System (IVTS)

Subdivision Mapping: Making the Pieces Fit David P. Thaler, GIS Analyst A geographit White Paper, June 2009

How To Improve Safety

Creating a Seamless Model of the Littoral and Near Shore Environments

SIAMA. SIAMA Asset Management Technologies Advanced Inspection Technology

ArcGIS Mobile Application User s Guide

Performance of a Deeply Coupled Commercial Grade GPS/INS System from KVH and NovAtel Inc.

Integration of Inertial Measurements with GNSS -NovAtel SPAN Architecture-

Sign Inventory and Management (SIM) Program Introduction

STATE OF ALASKA DEPARTMENT OF NATURAL RESOURCES DIVISION OF MINING, LAND AND WATER. GENERAL SURVEY INSTRUCTIONS EASEMENTS Authority 11 AAC 53

FLEET MANAGEMENT SYSTEM FOR TRAFFIC CONTROL DEVICES.

TRAFFIC ACCIDENT STUDY GUIDE 2010

Commercial Motor Vehicle Safety and Security Systems Technology Wireless Mobile Communications

Organically Growing an Asset Management System in the City of Novi, Michigan

COMPACT GUIDE. Camera-Integrated Motion Analysis

Crash data may not contain complete information, some elements may be unknown

SONOBOT AUTONOMOUS HYDROGRAPHIC SURVEY VEHICLE PRODUCT INFORMATION GUIDE

VEHICLE TRACKING SYSTEM USING GPS. 1 Student, ME (IT) Pursuing, SCOE, Vadgaon, Pune. 2 Asst. Professor, SCOE, Vadgaon, Pune

Table of Contents 1. Introduction Installing Sxblue Server Principle of Operation Server Configuration

ADSP Sensor Survey For RTLS Calibration How-To Guide

Asset Data: A New Beginning, A New AURIZON. OmniSurveyor3D - The one source of truth

Collided Vehicle Position Detection using GPS & Reporting System through GSM

Waypoint. Best-in-Class GNSS and GNSS+INS Processing Software

LIDAR and Digital Elevation Data

Remote Sensing, GPS and GIS Technique to Produce a Bathymetric Map

INITIAL SITE INSPECTION OF MOTORCYCLE COLLISIONS WITH ROADSIDE OBJECTS IN NEW JERSEY

Storm Drainage Systems

ORDINANCE NO THE CITY COUNCIL OF ALEXANDRIA HEREBY ORDAINS:

USER S MANUAL. ArboWebForest

Mobile Laser Scanning for Oilfield Asset Mapping and Management

port may have a cover that, prior to installing the tracking device, will need to be removed.

Improving Distribution Reliability with Smart Fault Indicators and the PI System

AAA AUTOMOTIVE ENGINEERING

GPS LOCATIONS FOR GIS: GETTING THEM RIGHT THE FIRST TIME

Transcription:

Cost-Effective Collection of a Network-Level Asset Inventory Michael Nieminen, Roadware

Introduction This presentation is about using a mobile vehicle to collect roadway asset (feature) data. Asset/Feature types include: Signs Guardrails (Guiderails) Catch basins Traffic signals Bus stops/bus shelters Medians Fire hydrants Parking meters Utility poles Trees

Introduction Trend: Increased utilization of GIS-based Asset Management Systems (AMS). AMS advantages: Keeps asset data together in one place. Provides easy access to data. Provides visual representation of features along with their location within the network. An AMS requires input data for all assets.

Introduction Existing inventories have usually been collected manually. Keeping inventory up-to-date this way is a challenge. Existing asset inventories: Usually not Geo-referenced. Data not always collected in a consistent manner. Data spans many years. Data out of date. Not representative of current state of assets.

New Data Collection New AMS often means new data collection is required across the entire network.

Data Collection Options Manual, walking surveys Used when very detailed information about each asset is required. Semi-automated, vehicle-based collection Cost-effective approach for large-scale data collection when more basic information about each asset is required. Advantage: Relatively low cost of data collection can be further divided among several departments for optimal use of available funds.

Vehicle-based Collection What sort of data can be captured? Standard attributes are: - GPS Positions Asset Type (e.g. MUTCD code for signs) Asset Dimensions (e.g. width, height) Basic Condition Rating (good, fair, poor) Digital image for each asset Any other data that can be visually determined from images captured along the roadway such as color, type, additional location information, etc.

Vehicle-based Collection Typically a data collection vehicle will have: High-resolution digital cameras GPS receiver Inertial sensor system (e.g. POS/LV) Distance measuring instrument Roadware s ARAN Vehicle

Vehicle-Based Collection Panoramic imagery is collected at regular intervals along the roadway (e.g. every 4mmi, or 21.12 ft). Any assets that appear in the images can be inventoried.

How It Works During collection, the vehicle s onboard GPS system stores a record of the vehicle position. All images are geo-referenced to the location at which they were captured. Back in the office, during the extraction process, features in the images are marked using the Surveyor software. Based on the location identified in the image, the software calculates (triangulates) the location of the identified feature in relation to the vehicle position. Vehicle GPS Street centerline

Surveyor Software By using the mouse and clicking on the image to identify points, the user marks asset positions (and dimensions if desired) on the images and records information about the asset.

Surveyor Software Surveyor software allows the user to input attributes to associate with the feature.

End Result: GIS-Referenced Data for Roadway Assets

Implementation The process: 1. Routing 2. Data collection (e.g. with ARAN vehicle) 3. (Post-processing GPS data) optional 4. Import video and data into Surveyor database 5. Survey assets from video using Surveyor software 6. Export asset database for transfer into AMS

2. Data Collection The use of reference stations during data collection is recommended but not necessary. Commercially-available CORS network Own and operate a base station If a reference station is used, GPS data would be post-processed with POSPac software prior to asset extraction.

3. Post-processing GPS Data The post-processing step involves copying files collected by the base station to the same computer as the ARAN files. POSPac software is run through several semi-automated steps to produce SBET files. One week s worth of data can take up to 1 day to process, including computing time.

4. Data Importing ARAN data and digital images are first uploaded to a server. A utility software called Data Importer links the digital images, data, and optional post-processed GPS files into one Access database. One week s worth of data collection can be imported into the database in ~1 hour.

5. Asset Extraction Surveying the assets from the digital images is the most time-consuming part of the process. Completely dependent on the number and type of assets selected for inventory. Run rates range from 0.5 miles/hr to 3.0+ miles/hr. 1,000 miles of inventory could take anywhere from 40 to 250 man-days.

6. Export Asset Data Surveyor provides an Export Wizard that allows the user to export some or all of the asset types in the database to output tables or Shape files. The exported data is readily imported into Asset Management Systems or other GIS systems. A complete network-level database can be exported in 1-3 hours.

GPS Positional Accuracies What are the GPS positional accuracies of assets inventoried with the ARAN? Answer: It depends on the accuracy of the vehicle GPS. The software used to mark the assets (Surveyor) adds only a small error component (20 to 50 cm).

GPS Positional Accuracies There are four GPS options on the vehicle: Real-time GPS subject to signal anomalies 5-20 meter accuracy not useful for asset inventory Real-time Differential GPS (RT DGPS) 1-3 meter accuracy Inertially-aided Real-time Differential GPS 1.0-1.5 meter accuracy Inertially-aided Post-processed Differential GPS 0.4 1.0 meter accuracy

Real-Time Differential GPS Uses a differential correction signal broadcast from a service such as OmniSTAR to adjust position in real-time. The base station receiver is located at an accurately surveyed point. The data collection vehicle logs the longitude and latitude of its position as it travels, and adds a correction to the coordinates based on the signal broadcast by the base station. 1-3 meter accuracy

Real-Time Differential GPS Differential Correction Signal Moving Receiver Base Station and Transmitter

Inertially-Aided Real Time DGPS Integrating GPS and inertial systems (e.g. POS/LV) improves data availability dramatically. Inertial systems use gyroscope orientation and trajectory data to provide coordinate fill-in during periods of GPS outage. Without the use of inertial technology, situations occur where it is not possible to obtain a GPS position for the roving receiver. 1.0-1.5 meter accuracy

Inertially-Aided Post-processed DGPS For data applications requiring the highest possible positional accuracy and coordinate availability, GPS data is collected using inertially-aided GPS receivers (on the data collection vehicle) and short base-line reference stations. This configuration provides both excellent coordinate availability through inertial fill-in, and accuracy through post-processing. Best results are obtained when using short base line reference stations when the base station is within 40 KM (~25 miles) of the vehicle. 0.4 1.0 meter accuracy

Case Study: City of Hamilton The City of Hamilton in Ontario, Canada implemented a Hansen AMS. The system required an initial input of accurate asset data. Roadware was selected to collect digital videolog and asset inventory on the City s 6,500 lane-km (~4,000 lanemile) network. Hamilton required that GPS positional accuracy would be +/- 1.5 m (under 5 feet).

Asset Attributes Collected Signs GPS position Sign dimensions (width, height) Digital image of each sign MUTCD code, sign category, sign text Curb present? (Y, N) Side of road sign is on (Left, Right, Overhead) Illumination device attached? (Y, N) Multiple signs on same post? (Y, N) Catch basins GPS position Digital image of each catch basin Catch basin type (Single, Double) Grate type (selection from list provided by the City)

Routing and Setup The City of Hamilton provided a database of roads that were to be surveyed. Roadware determined the most efficient routing to collect the data. An inertially-aided GPS system was chosen (POS/LV) to meet the accuracy requirements for the project. A short base-line reference station was also used. Postprocessing increased accuracy even further.

Control Sites Five control sites were established within the City. An independent survey crew performed a traditional land survey to establish the accurate position of 78 individual features across the five sites. (Accuracy +/- 2 cm)

City of Hamilton Control Sites Five control sites distributed throughout the city

Control Site Methodology At the beginning of data collection, all five sites were collected by Roadware s vehicles. The traditionally surveyed features were marked using Surveyor. The positions computed by the software were compared to the ground truth data collected by the survey company. One control site was re-collected by the ARAN each week and comparisons were performed to verify that expected accuracies were being maintained.

City of Hamilton Five Control Sites Looking at an example in detail: The traditionally surveyed points served as Roadware s Ground Truth. Ground truth with Surveyor 2.0 results.

Positional Accuracy Meets Project Specifications This site was run 3 times during the project. Average errors: 08/22/04 1.13 m PASS 10/17/04 0.69 m PASS 11/27/04 0.58 m PASS

Control Site Results Site RT DGPS IA RT DGPS PP IA DGPS Cootes Drive -rural, open skies Dalewood Ave. -subdivision, tree cover King St. - urban, few obstruct. James St. -urban canyon Sulphur Springs -rural, high tree cover 1.55 13.2 1.84 N/A 51.8 0.62 0.88 1.10 1.84 1.05 Average error magnitudes, measured in metres (m) 0.41 0.80 0.72 1.09 0.80

Limitations of Vehicle-Based Collection Some assets may not be visible in the camera views. Obstructed by traffic or parked vehicles Covered by leaves or other debris Detailed data (such as asset serial numbers) cannot be determined. Asset condition cannot be assessed in detail.

The Benefits are still apparent City of Hamilton Results of Data Collection

Just ask the City of Hamilton City of Hamilton Results of Data Collection Roadware collected digital videolog plus 55,000 signs and catch basins on the City s 6,500 lane-km (~4000 lane-mile) network with GPS positional accuracy better than +/- 1.5 m.

Another Example: City of Detroit

Questions