J.3_FHWA_RESEARCH_AHC-Vol-I-Final_Draft.pdf

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FOREWORD

The Federal Highway Administration (FHWA) conducted research to document gaps for implementing Automation in Highway Construction and to develop guidance for state transportation departments to assist them in implementing and using automation to improve project delivery. There are two volumes of the final report for each of the two objectives. Part I of the final report (this volume) presents a description of the key automation technologies and the associated benefits, challenges, and solutions. Part II of the final report presents an overview of enabling technologies and policies for automation in highway construction, along with implementation strategies, design procedures and practical guidelines to properly generate 3D models for uses in construction and other phases of highway project delivery.

Jorge E. Pagán-Ortiz

Director, Office of Infrastructure

Research and Development

Notice

This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The U.S. Government assumes no liability for the use of the information contained in this document.

The U.S. Government does not endorse products or manufacturers. Trademarks or manufacturers’ names appear in this report only because they are considered essential to the objective of the document.

Quality Assurance Statement

The Federal Highway Administration (FHWA) provides high-quality information to serve

Government, industry, and the public in a manner that promotes public understanding. Standards and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its information. FHWA periodically reviews quality issues and adjusts its programs and processes to ensure continuous quality improvement.

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1. Report No.

FHWA-XX-NN-NN

2. Government Accession No.

N/A

3 Recipient Catalog No.

N/A

4. Title and Subtitle

AUTOMATION IN HIGHWAY CONSTRUCTION:

Final Report - Part I

Implementation Challenges at State Transportation Departments and Success Stories

5. Report Date

July 2015

6. Performing Organization Code

N/A

7. Author(s)

Helga N. Torres, J. Mauricio Ruiz, George K. Chang, Jennifer L. Rutledge, and

Sabrina Garber

8. Performing Organization Report No.

N/A

9. Performing Organization Name and Address

The Transtec Group, Inc.

6111 Balcones Drive

Austin TX 78731

10. Work Unit No. (TRAIS)

N/A

11. Contract or Grant No.

DTFH61-13-C-00026

12. Sponsoring Agency Name and Address

USDOT-Federal Highway Administration

Office of Infrastructure R&T

Infrastructure Analysis and Construction Team

6300 Georgetown Pike, HRDI-20

McLean, VA 22101

13. Type of Report and Period Covered

Draft Final Report

14. Sponsoring Agency Code

N/A

15. Supplementary Notes

Contracting Officer’s Representative: Richard Duval

16. Abstract

Automation in Highway Construction includes an increasing number of technologies that collect, store, analyze, and process information to make, support or execute an appropriate action or decision that results in enhanced construction outcomes. The goals of automation in highway construction are to increase the speed, efficiency, and/or safety during the construction process. This is in conjunction with components, processes, and software that assist in a more efficient system of construction.

The primary objectives of this project were to address gaps identified for implementing automation in highway construction and to develop guidance for state transportation departments to assist them in implementing automation to improve accelerated project delivery. There are two volumes of the final report for each of the two objectives.

Part I of the final report (this volume) presents a description of the key automation technologies part of this study and the associated benefits, challenges, and solutions.

Part II of the final report presents an overview of enabling technologies and policies for automation in highway construction, along with implementation strategies. The Part II report also includes design procedures and practical guidelines to properly generate 3D models for downstream uses in construction and other phases of highway project delivery.

17. Key words

Automation in highway construction, intelligent construction, systems, technologies, challenges, opportunities

18. Distribution Statement

No restrictions.

19. Security Classif. (of this report)

Unclassified

20. Security Classif. (of this page)

Unclassified

21. No. of Pages

22. Price iii

Contents FOREWORD ................................................................................................................................... i

ACKNOWLEDGMENTS

DISCLAIMER

1. INTRODUCTION

1.1 OBJECTIVE

1.1 REPORT ORGANIZATION

1.2 ACRONYMS

2. KEY AUTOMATION TECHNOLOGIES

3. AUTOMATION TECHNOLOGY IMPLEMENTATION AT STATE

TRANSPORTATION DEPARTMENTS

3.1 REMOTE SENSING (LiDAR AND 3D LASER SCANNING)

3.1.1 Implementation Efforts at State Transportation Departments

3.1.2 Success Stories

3.1.3 Technology Costs and Resulting Savings

3.2 UNDERGROUND UTILITIES LOCATION

3.2.1 Implementation Efforts at State Transportation Departments

3.3 3D DESIGN

3.3.1 Implementation Efforts at State Transportation Departments

3.3.2 Success Stories

3.3.3 Technology Costs and Resulting Savings

3.4 CONSTRUCTION AUTOMATION

3.4.1 Implementation Efforts at State Transportation Departments

3.4.2 Success Stories

3.4.3 Technology Costs and Resulting Savings

3.5 FIELD TECHNOLOGY AND INSPECTION

3.5.1 Intelligent Compaction

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3.5.2 Non-Destructive Testing (NDT) Devices for Quality Assurance

3.5.3 Field Inspection

3.5.4 Implementation Efforts at State Transportation Departments and Success Stories .. 69

3.5.5 Technology Costs and Resulting Savings

4. 3D AND DIGITAL DATA MANAGEMENT

4.1 CIVIL INTEGRATED MANAGEMENT (CIM)

5. AUTOMATION TECHNOLOGY IMPLEMENTATION PLANNING

5.1 WISCONSIN DOT

5.2 OREGON DOT

6. SUMMARY AND CONCLUSIONS

7. REFERENCES

APPENDIX A. CASE STUDY, WISDOT-SE FREEWAYS ZOO INTERCHANGE

A.1 INTRODUCTION

A.1.1 Background: 3D Efforts in Wisconsin

A.2 WISDOT SOUTHEAST FREEWAYS AND AUTOMATION/3D TECHNOLOGIES .. 98

A.3 ZOO INTERCHANGE PROJECT

A.4 SURVEYING

A.5 3D DESIGN / MODELING

A.6 DESIGN-CONSTRUCTION REVIEWS

A.7 3D CONSTRUCTION / MODELING

A.8 CONCLUSIONS

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Tables Table 1. Original and revised technologies lists

Table 2. Summary of identified LiDAR technology challenges and solutions (1/2)

Table 3. Summary of identified LiDAR technology challenges and solutions (2/2)

Table 4. Summary of identified challenges and solutions for underground utilities location

Table 5. Summary of identified challenges and solutions for 3D design

Table 6. European research projects on AMG (after Heikkila and Tiitinen 2013)

Table 7. Summary of identified challenges and solutions for Automated Machine Guidance and

Control

Table 8. Comparison of two traditionally-surveyed projects against two machine-control guided projects (http://www.machineguidance.com.au/Survey-Cost-Comparison)

Table 9. Summary of identified challenges and solutions for field technology and inspection

(1/2)

Table 10. Summary of identified challenges and solutions for field technology and inspection

(2/2)

Table 11. Kansas DOT summary of electronic deliverables challenges and decisions (Hovey and

Lubliner 2012)

Table 12. Summary of initiatives, goals, efforts, priorities, and lead sections (1/2) (Vonderohe

2009)

Table 13. Summary of initiatives, goals, efforts, priorities, and lead sections (2/2) (Vonderohe

2009) vi

Figures

Figure 1. Key automation technologies throughout highway project delivery

Figure 2. The total information process of 3-D road construction – one description level

(Heikkila and Jaakkola 2003)

Figure 3. An example of terrestrial mobile LiDAR system

Figure 4. A terrestrial static LiDAR system (Olsen and Chin 2012)

Figure 5. View of point cloud from terrestrial mobile laser scanning system (www.lidarusa.com).

Figure 6. Point Cloud Processing Pipeline (after Gant et al. 2014)

Figure 7. Summary of existing LiDAR guidelines (Williams et al. 2013)

Figure 8. Static laser scanning of bridge structure at Oregon DOT (Wright and Brinton 2009). . 19

Figure 9. View of I-80 test section (Searle and Sridharan 2014)

Figure 10.View of Pilot Section along I-22: Corridor X (Russell 2012)

Figure 11. 3D underground utility map (Sundt 2011)

Figure 12. Comparison between 2D plan view and 3D model for Northwest PATH Pedestrian

Tunnel, Toronto, Canada (courtesy of Hatch Mott McDonald)

Figure 13. 3D view of a surface model for AMG (courtesy of Construction Engineering

Solutions, LLC)

Figure 14. Traditional 2D design workflow vs. 3D workflow (after Arena 2014)

Figure 15. Example of mill and inlay project and 3D data uses in construction (Arena 2014)

Figure 16. Example of concrete placement and 3D data uses in construction (Arena 2014)

Figure 17. Example of drainage work and 3D data uses in construction (Arena 2014)

Figure 18. Example of median work and 3D data uses in construction (Arena 2014)

Figure 19. 3D design view of the Mitchell Interchange I-94/I-43 Corridor (WisDOT 2012)

Figure 20. Intersection of U.S. 19 / State Route 9 and State Route 60, Lumpkin County, GA

(Bing Maps)

Figure 21. Comparison between 2D plan view and visualization with 3D modeling for Option 1:

Stonepile-Centered Roundabout (courtesy of GDOT VERG)

Figure 22. Comparison between 2D plan view and visualization with 3D modeling for Option 2:

Offset Roundabout (courtesy of GDOT VERG) vii

Figure 23. Automated Machine Guidance equipment for earthworks

Figure 24. GNSS guided subgrade motor grader

Figure 25. Automation technology use throughout a highway project timeline

Figure 26. An example of Intelligent Compaction for asphalt

Figure 27. An example of GPR

Figure 28. An example of paver-mounted thermal profile system, PAVE-IR

Figure 29. An example of PCC real-time profiler

Figure 30. An example of concrete maturity meter

Figure 31. Temperature and maturity monitoring with handheld reader

Figure 32. Temperature sensors placement before concrete pour

Figure 33. 3D models for automation of road construction. (Heikkila and Jaakkola 2006)

Figure 34. 3D CIM Concept Illustration (Parve 2014)

Figure 35. WisDOT 3D initiatives dependency diagram (Vonderohe 2009)

Figure 36. Oregon DOT Construction Machine Automation implementation plan (Singh et al.

2010)

Figure 37. WisDOT Summary of 3D initiatives (Vonderohe 2009)

Figure 38. Zoo Interchange Schedule of Construction (WisDOT 2012)

Figure 39. Zoo Interchange Integrated Survey

Figure 40. Snapshot of a Portion of the Zoo Interchange CIM Project Modeling Matrix

Figure 41. Zoo Interchange PxP 3D Model Delivery Schedule (Parve and Johnson 2013)

ACKNOWLEDGMENTS

This project is possible due to the funding from FHWA and the assistance from state transportation departments leading efforts to implement Automation in Highway Construction.

A partial list of agency contacts for this study is presented below.

Lance Parve, Wisconsin DOT

Brad Hollister, Wisconsin DOT

Alexa Mitchell, Missouri DOT

Ron Singh, Oregon DOT

David Arena, Oregon DOT

Michael Kennerly, Iowa DOT

Brian Smith, Iowa DOT

John Russell, Alabama DOT

Glenn Williams, Georgia DOT

Richard McDaniel, Eastern Federal Lands Highway Division

In addition, Mr. Lance Parve with the Wisconsin DOT co-authored the case study presented on

APPENDIX A. CASE STUDY, WISDOT-SE FREEWAYS ZOO INTERCHANGE, which portrays how lead agencies are implementing and using automation in highway construction.

DISCLAIMER

This report represents the results of research conducted by the authors and does not necessarily represent the views or policies of the state transportation departments whose policies and practices have been referenced.

The main automation technology vendors and manufacturers as of December 2014 were listed for illustrational purposes; however, this report does not provide a complete list. The authors and the FHWA do not endorse these products or manufacturers. Trade or manufacturers’ names appear herein solely because they are considered essential to this report.

1. INTRODUCTION

This report addresses gaps identified for implementation of automation technology from highway project development through construction. In addition, guidance is presented to assist state transportation departments in determining how to implement and use automation to improve accelerated project delivery. The study involved collecting, organizing, and analyzing data from various state transportation departments.

This effort focused on five key technology areas, taking into consideration that to be able to fully implement automation during the construction phase of a highway project, technologies

(systems, components, processes, software, etc.) are implemented prior to construction during the planning, surveying, and design phases. These key technology areas are:

1. Remote Sensing o LiDAR, 3D laser scanning, others

2. Underground Utilities Locating Technologies

3. 3D Design

4. Machine Control and Automation / Automated Machine Guidance

5. Field Technology and Inspection o Intelligent Compaction o Non-Destructive Testing for QA/QC

Ground penetrating radar (GPR), infrared thermal profilers, real-time smoothness profilers, and concrete temperature and maturity meters o Inspection

Telematics, smart phones, tablets, etc.

As shown in Figure 1, these key technologies are utilized throughout the different highway project delivery phases: planning, surveying, design, and construction.

Figure 1. Key automation technologies throughout highway project delivery.

1.1 OBJECTIVE

The main objectives of this document are to:

Document automation in highway construction success stories and best practices, and best uses for individual technologies;

Document the types of costs and resources required by industry and agencies for implementation of these technologies, and their associated return on investment (ROI);

and

Document automation technology challenges in the areas of surveying, utilities, real time verification, and data management.

1.1 REPORT ORGANIZATION

Section 2 of this report describes how the five key automation technology areas were selected.

Section 3 presents a description for each of the automation technology areas and the associated benefits, challenges, and solutions. Section 3 also provides an overview of state transportation departments’ implementation efforts and success stories for the individual automation technologies, along with an overview of the cost and resulting time / cost savings for the different technology categories. Section 4 provides an overview of efforts to define and promote 3D and digital data management. Section 5 provides an overview of the automation technology implementation plans developed by two lead state transportation departments.

Section 6 presents a summary of conclusions and recommendations to continue development and implementation of automation technology for highway construction.

APPENDIX A. CASE STUDY, WISDOT-SE FREEWAYS ZOO INTERCHANGE presents a case study developed with the assistance from Wisconsin DOT to illustrate the usage of automation technology throughout the different phases of the Zoo Interchange project in

Milwaukee.

A separate document includes the Part II report for this effort, which presents an overview of enabling technologies and policies for automation, along with implementation strategies for state transportation departments. Following, the Part II report presents design procedures and guidelines to properly generate 3D models for downstream uses in construction and other phases of highway project delivery (Maier et al. 2015).

1.2 ACRONYMS

AASHTO American Association of State Highway and Transportation Officials

ACI American Concrete Institute

AGC Associated General Contractors

AMG Automated Machine Guidance

ASTM American Society for Testing and Materials

BIM Building Information Modeling

CAD Computer-aided design

Caltrans California Department of Transportation

CIM Civil Integrated Management

CORS Continuously Operating Reference Stations

DOT Department of Transportation

DTM Digital terrain model

FHWA Federal Highway Administration

GDOT Georgia Department of Transportation

GIS Geographic information system

GNSS Global navigation satellite system

GPR Ground penetrating radar

GPS Global positioning system

IC Intelligent Compaction

ICST Intelligent Construction Systems and Technologies

LiDAR Light detection and ranging

MLS Mobile LiDAR system

MnDOT Minnesota Department of Transportation

MoDOT Missouri Department of Transportation

NCHRP National Cooperative Highway Research Program

NDT Non-destructive testing

ROI Return on investment

SHRP Strategic Highway Research Program

TRB Transportation Research Board

USGS United States Geological Survey

WisDOT Wisconsin Department of Transportation

2. KEY AUTOMATION TECHNOLOGIES

This effort began with the review and screening of the technologies described in the first generation of the FHWA Intelligent Construction Systems and Technologies (ICST) Strategic

Roadmap (Roadmap) taking into consideration the recommendations from the Transportation

Research Board (TRB) Committee for Intelligent Construction Systems and Technologies:

Program Review (Ralls et al. 2013a; Ralls et al. 2013b). The TRB ICST committee’s recommendations included a new definition of ICST, as “Systems and technologies that collect, store, analyze, and process information, make, and execute an action or decision that results in quality construction. This is in conjunction with components, processes, and software that assist in a more efficient system of construction.”

The Roadmap listed technologies recommended during a 1.5-day FHWA ICST stakeholder workshop in 2011, which are not necessarily “intelligent” but accelerate construction, improve quality, reduce cost, or improve safety. Table 1 illustrates how the list of technologies was revised to focus on technologies meeting the definition for ICST along with 3D, advanced, and geospatial technologies currently being investigated and/or implemented by state transportation departments to support and enhance the use of automation in highway construction.

Table 1. Original and revised technologies lists.

ICST Roadmap List 1BRevised List of Automation Technologies

a. Telematics (Connected Sites, SiteLINK, iCON, etc.)

b. Concrete Temperature and Maturity Meters

c. Modern Barrier Systems for Construction Traffic Control

d. Traffic Management Modeling Software

e. Digital Signatures

f. Automated Machine Guidance (AMG)

g. Low Distortion (Planar) Coordinate Systems

h. Remote Sensing (aerial photography, satellite imagery, LiDAR, and ground based stationary or mobile 3D laser scanning, etc.)

i. Intelligent Compaction (Soils and HMA)

j. Stiffness Measuring Devices

k. Advances in Paving Technologies

l. Non-Destructive Testing (NDT) Devices for Quality

Assurance

m. Recycled Pavement Materials

n. Accelerated Bridge Construction (ABC) Techniques

o. Advanced Heavy Lift Construction Equipment

p. 3D/4D Engineered Models

q. Earth Centered/Earth Fixed (Spherical) Coordinate

Systems

r. Transportation Information Modeling (term was used at the ICST workshop. FHWA is now using CIM.)

s. Accurate Identification of Subsurface Utilities

t. Advanced Warning and Speed Control Devices

u. Automatic Work Zone Condition Updates

1B

a. Remote Sensing

i. LiDAR, 3D laser scanning, others

b. Underground Utilities Location

c. 3D Design

d. Machine Control and Automation

i. Automated Machine Guidance

e. Field Technology and Inspection

i. Intelligent Compaction

ii. NDT for QA/QC ground penetrating radar

(GPR), infrared thermal profilers, real-time smoothness profilers, concrete temperature and maturity meters

iii. Inspection

Telematics, smart phones, tablets

The development of some of the automation technologies listed above such as Machine Control and Automation dates back to the 1980s. Skibniewski and Hendrickson (1990) report on the significant potential and feasibility of automation and robotics for road construction and maintenance, if substantial investment and research was carried out in the 1990s. Note that

Skibniewski and Hendrickson (1990) discussed similar benefits as the ones that are being observed with automation in highway construction today: cost savings, improved productivity, quality, and safety.

In addition, the concept of automation in highway construction throughout project development

(planning, surveying, design, construction, and maintenance) has been under investigation and development for more than a decade by highway agencies worldwide. Heikkila and Jaakkola

(2003) defined “the total information process of 3-D road construction” with the diagram in

Figure 2, which includes four of the five key automation technologies included in this study.

Figure 2 shows that the process begins with 3D measurements of the existing conditions during surveying (LiDAR/3D laser scanning), followed by 3D design, machine control and guidance during construction, and 3D measurements for QC.

Figure 2. The total information process of 3-D road construction – one description level

(Heikkila and Jaakkola 2003).

3. AUTOMATION TECHNOLOGY IMPLEMENTATION AT STATE

TRANSPORTATION DEPARTMENTS

For this effort, a detailed literature review was conducted to identify the benefits, challenges, solutions, and available standards/specifications for each of the key automation technologies.

The findings are discussed in the following subsections. Next, in an effort to document the success stories from lead state transportation departments with respect to the different automation technologies, a site visit was conducted to Wisconsin DOT followed by a series of conference calls and correspondences with Iowa, Missouri, and Oregon DOTs. Alabama and

Georgia DOTs explained that they are at the beginning stages with automation and 3D technologies implementation; nevertheless they also shared information on their implementation efforts. Their feedback is presented in subsequent sections covering each automation technology. APPENDIX A. CASE STUDY, WISDOT-SE FREEWAYS ZOO INTERCHANGE presents a case study that illustrates how Wisconsin DOT is using automation technology throughout the different phases of a major interchange reconstruction project.

Note that all of the lead state transportation departments interviewed have established a network of GPS / GNSS Continuously Operating Reference Stations (CORS), which facilitate the implementation and use of automation in highway construction. These efforts, many in cooperation with other agencies such as the National Geodetic Survey, support the implementation and use of automation technology from surveying, to mapping utilities, to construction. Projects located in areas covered by a CORS network do not require surveyors and contractors setting up a base station, which facilitates project control development and results in time and cost savings. Additional time and cost savings are presented if the contractor equipment is able to connect to the CORS networks for AMG and inspection purposes.

The following subsections present a description for each of the key five automation in highway construction technologies and the associated benefits, challenges, and solutions. An overview of state transportation departments implementation efforts and success stories is also presented. At the end of each subsection, available cost and resulting time / cost savings information is presented for each technology. Note that cost and ROI information is scattered and many of the case studies available have been conducted at a project level, not representing agency wide figures.

3.1 REMOTE SENSING (LiDAR AND 3D LASER SCANNING)

In this report, the term remote sensing is used to describe 3D remote data acquisition using technologies such as LiDAR and other 3D imaging devices. Other remote sensing technologies include ground penetrating radar, road profilers / scanners, and other sensors (i.e. sign reflectivity). The accuracy and precision varies for each of these different technologies. For example, 3D laser scanners measure millions of data points per second and generate a very detailed “point cloud” data set. Remote sensing manufacturers and solution providers include

FARO, Leica Geosystems, RIEGL, Trimble, Topcon, and Z+F.

Benefits of this technology begin with survey data collection time and cost savings followed by increased productivity (e.g., less re-work) throughout the entire project delivery process. There is improved quality with the increased level of detail, accuracy, and scalability. For example, when high definition surveys are provided to contractors during the pre-bid stages, the increased accuracy and detail reduces uncertainty and allows them to submit more competitive bids. More accurate earthwork volume calculations are also possible.

Another benefit of using remote sensing is improved safety since the non-contact technologies minimize or eliminate the time field crews are exposed to traffic and other dangerous conditions.

Also, non-contact technologies minimize or eliminate impacts to environmentally sensitive areas.

Finally, the use of remote sensing technology during survey phases provides a building block for information modeling in design, and as-built construction documentation.

Cawley et al. (2013) state that more than half of the state transportation departments are using some type of LiDAR technology based on a 2012 survey. The LiDAR technology includes three different forms: airborne, terrestrial mobile, or terrestrial static. Airborne LiDAR makes use of airplane or drones equipped with laser scanners, GPS, and inertial measurement unit (IMU) to enable accurate and detailed capturing of the 3D geometry of ground surfaces and objects via aerial surveys. The level of detail can be enhanced using a smaller beam width, multiple pulses in the air, and full waveform digitization.

Terrestrial mobile LiDAR systems (MLS), also referred to as mobile laser scanning systems, are being widely investigated and implemented at state transportation departments. For transportation applications, mobile systems offer increased accuracy when compared to airborne systems, and offer increased efficiency when compared to static systems. Therefore there is strong interest in MLS. Figure 3 shows an example of an MLS. Typical components of an MLS include a vehicle, multiple 3D/LiDAR scanners, positioning hardware (GPS/GNSS receiver, inertia measurement unit (IMU), distance measurement indicator (DMI)), cameras (photo/video), data acquisition system, and in-vehicle computer monitor.

Figure 3. An example of terrestrial mobile LiDAR system.

Some transportation applications require a static scanning system for high definition surveys.

Figure 4 shows an example of a terrestrial static LiDAR system. The scanner is mounted on a tripod and data can be acquired from the side of the road. Multiple positions are usually required to fill in occlusions. Geo-referencing of the scan data is accomplished through reflective targets set up over control points or through a GPS / GNSS mounted on top of the scanner. A camera is also mounted or integrated into the system to obtain calibrated images with Red, Green, and Blue

(RGB) colors, corresponding to each scan position.

Figure 4. A terrestrial static LiDAR system (Olsen and Chin 2012).

Key products of laser scanning systems include a geo-referenced point cloud and the associated high resolution imagery, which are used to produce CAD models and Digital Terrain Models

(DTMs). A screen shot of a laser scan point cloud from a terrestrial mobile laser scanning system is presented in Figure 5.

Figure 5. View of point cloud from terrestrial mobile laser scanning system (www.lidarusa.com).

Note that point cloud processing requires the use of multiple software packages, knowledgeable technical staff, and increased processing time to integrate LiDAR data into transportation workflows. Figure 6 shows a brief overview of the point cloud processing activities. Figure 6 http://www.lidarusa.com/ illustrates that point cloud processing is not a dynamically-linked process, but rather one that involves importing/exporting files between the different software tools that are available.

Figure 6. Point Cloud Processing Pipeline (after Gant et al. 2014).

In general, airborne LiDAR surveys are used for preliminary engineering of highway projects;

mobile laser scanning is used for corridor mapping, shoulder to shoulder; and static laser scanning is used for surveying of highway structures such as bridges and tunnels. The products of laser scanning systems are most relevant to the following automation in highway construction applications:

Engineering Surveys, CAD models and DTMs used for 3D Design, Machine Control and

Automation

Clash detection (i.e. clearance data for overpasses, bridges, signs, power lines)

Periodic scans for estimates of percent completion, quantities, inspection / QC and as-builts at project completion.

Field Data Collection

Point Cloud Processing

(registration, index, clean, view)

View, Measure, Modeling, Terrain

Development

Geometry and Feature Extraction

Stand-alone or Scanner Manufacturer’s Software

Viewing Software Tools www.ayresassociates.com

CAD and Design Software

3.1.1 Implementation Efforts at State Transportation Departments

As with any other emerging and innovative technology, state transportation departments have been conducting research, demonstrations, and/or pilot projects to compare MLS technology to traditional surveying. For example, Iowa DOT (Miller et al. 2012) conducted a comparison of

MLS to traditional surveying using Total Station for an interchange project. This project allowed Iowa DOT to become familiar with MLS issues such as accuracy, specifications, data content itself, data storage, etc. Iowa DOT was able to confirm the reported benefits for this technology over traditional surveying, such as increased accuracy, safety, and efficiency. In addition, Miller et al. (2012) identified the steps / challenges that need to be overcome next, such as developing specifications and software improvements to fully utilize the technology.

Additional recent studies by state transportation departments to understand better transportation applications of LiDAR technology include work by North Carolina DOT (Chang et al. 2014), and Wisconsin DOT (CTC & Associates LLC 2010).

At a national level, Olsen et al. (2013a) developed guidelines for the use of mobile LiDAR in transportation applications. The guidelines (NCHRP Report 748) encompass applications from project planning, design, and construction, to operations and maintenance, and address data collection methods, formatting and management, storage requirements, quality assurance, translation and formatting of derived products, etc. Olsen et al. (2013a) establish data collection categories based on the transportation applications and the required accuracy and point cloud density. Based on NCHRP Report 748, Williams et al. (2013) summarize in Figure 7 the existing LiDAR guidelines, which include work by Caltrans, Texas DOT, Missouri DOT, and the American Society of Photogrammetry and Remote Sensing (ASPRS). Note that Florida

DOT (2013) developed MLS guidelines based on NCHRP Report 748 and Caltrans guidelines.

Figure 7. Summary of existing LiDAR guidelines (Williams et al. 2013).

A summary of the implementation challenges and reported solutions for remote sensing technology, particularly mobile LiDAR, is presented in Table 2 and Table 3. Key references include NCHRP Report 748, NCHRP Synthesis 446, and the WisDOT 3D Technologies

Implementation Plan (Vonderohe 2009; 2013).

Table 2. Summary of identified LiDAR technology challenges and solutions (1/2).

Challenge Solutions

Cost

Olsen et al. (2013b):

Acquire and share between agencies. For example, the Oregon LiDAR consortium coordinates LiDAR acquisition among several state and federal agencies pooling resources to reduce acquisition costs.

o This solution is more applicable to network level applications, and less applicable to project level and automation in highway construction.

Singh (2014a):

Oregon LiDAR consortium consists of high altitude, airborne LiDAR, for coverage of wide areas. Standards are a lot tighter than what is typically used for the rest of the country. Oregon is working to make standards even more stringent and the data more usable for highway engineering.

Lack of Standards, Metadata

Interoperability and integration with existing CAD and GIS systems, as it is data sharing to maximize the investment.

Olsen et al. (2013a):

ASPRS has developed the LAS format (current version 1.4), which is the most commonly used format for airborne laser scanning. This format has been integrated into several software packages.

The ASTM E57 subcommittee developed an additional format E57 for 3D imaging systems. This format has additional benefits, including advanced, integrated image support and internal data structure support. Integration for the E57 format in software is limited; however, support is growing rapidly.

Data Management

Managing and storing the extremely large data sets that result from laser scanning can be a challenge. In addition, a centralized data model to support data sharing is encouraged.

ASTM E57.04 Subcommittee is working to address interoperability and data transfer issues.

WisDOT created regional Survey Data Coordinator positions to facilitate data flow between design and construction and provide assistance with development and implementation of standards and procedures for data collection. As of January 2013, reported challenges:

o Large volumes of data must often be transferred by shipping hard drives.

o For mega projects (i.e. SE Freeways), consultants are managing

LiDAR data.

IT upgrades (i.e. network bandwidth, storage, back up, archival)

Significant office work

Iowa DOT has dedicated IT staff in their design section to support 3D design efforts.

o They are storing raw LiDAR data in a different location, and

LiDAR products for each project (i.e. topography and DTM surface) are stored with the project files (i.e. ProjectWise).

Consultants are using services such as Amazon Web Services (AWS), TopoCloud™, etc. to handle large volumes of point cloud, 3D data. There is a trend for web-based point cloud viewing/rendering, modeling, facilities management, app hosting.

o Challenges: security, down time, login issues, expertise, internet speed / network bandwidth.

http://www.oregongeology.org/sub/projects/olc/default.htm

Table 3. Summary of identified LiDAR technology challenges and solutions (2/2).

Challenge Solutions

Immature Software and Lack of

Automated Processing

Processing often requires use of multiple software packages. It should be noted that knowledgeable technical staff, increased processing time, and new software may all be required to integrate LiDAR data into transportation workflows.

WisDOT, as of January 2013:

o Central office is deciding upon appropriate software platform for raw data reduction and feature extraction and training.

Specialized Training

Full range potential of LiDAR applications across DOTs not fully understood and documented.

TRB LiDAR Webinars (NCHRP Project 15-44)

LiDAR News e-Magazine

SPAR Point Group Webinars and Blogs

Rönnäng (2014) presents a good example of how the 3D laser scanning technology was implemented by Volvo in the manufacturing industry.

Volvo worked with technology vendors and consultants to develop their scanning procedures and workflows, before beginning in-house scanning.

Lack of Guidelines, Specifications

Accuracy, resolution, point cloud density, QC/QA, deliverables.

ASPRS Mobile Mapping Committee is developing guidelines.

WisDOT: in 2012 mobile LiDAR data collected by consultants and a specification was developed based on USGS, Caltrans, and other states.

“Integrated surveys” specification for LiDAR combined with photogrammetric and ground surveys.

NCHRP Project 15-44, Report 748

Pilot projects to develop draft guidelines/specs

Data Collection Issues

Neighboring vehicles can block data collection (MLS).

Rolling Lane Closure may be used to prevent vehicles from blocking the system.

Equipment Availability Information from LiDAR vendors/service providers

3.1.2 Success Stories

Several state transportation departments own terrestrial static systems and a few others like

California and Oregon own mobile systems. A brief summary of recent implementation efforts by Oregon DOT (Singh 2014a), Utah DOT (Searle and Sridharan 2014), and Alabama DOT

(Russell 2012) is provided below.

Oregon DOT

Oregon DOT owns stationary scanning systems that are used for scanning all of the tunnels and bridges in their network. Oregon DOT also owns a mobile scanning system which was initially purchased for asset management, but Oregon DOT is working with the manufacturer to develop procedures and algorithms to improve point cloud density / accuracy and potentially use it for engineering applications in the future. Oregon DOT also participates in the Oregon LiDAR

Consortium which consists of high altitude, airborne LiDAR, for coverage of wide areas.

Oregon is working to make standards more stringent and the data more usable for highway engineering. Combining all these resources—aerial, mobile, and stationary—provides Oregon

DOT with a lot of useful information in terms of LiDAR and 3D data. They are also working to make it accessible online.

Figure 8. Static laser scanning of bridge structure at Oregon DOT (Wright and Brinton 2009).

Utah DOT case study: Using Asset Management Mapping Grade LiDAR for Design (Searle and Sridharan 2014)

Utah DOT hired consultants to evaluate the accuracy and effectiveness of using existing asset management, mapping grade LiDAR data for design surveys. The pilot project was conducted for a section of I-80, and for a period of six months, the consultants worked on the following tasks: point-cloud calibration, point-cloud accuracy verification, supplemental and design surveys, documentation, and analysis. Searle and Sridharan (2014) reported that accuracies of

+/- 3 cm were achieved which are similar to traditional surveying methods and sufficient for design surveys. Supplemental surveying was needed for vegetated slopes, occlusions, etc.

Savings of using existing mapping grade data for design were reported to be 24% for cost, 22% for time, and increased safety.

Figure 9. View of I-80 test section (Searle and Sridharan 2014).

Alabama DOT: Evaluating Mobile Scanning Data for use within a State DOT (Russell 2012)

The Survey Office at the Alabama DOT investigated the use of mobile scanning to obtain pavement elevations at an accuracy suitable for resurfacing projects involving cross slope correction, checking guard rail heights, clear zones, etc. Typically, those projects would require extensive surveys adding time to the project schedules. Alabama DOT decided to evaluate mobile laser scanning and investigate the potential benefits for this application, as presented by

Russell (2012):

Increased Safety: for the field crews and traveling public since there is no traffic congestion due to lane closures

Time Savings: survey delivery time for an average project (10 miles) was estimated to be 6 weeks or less

Increased Level of Detail, Accuracy, and Scalability: which translate into efficiency and improved quantity estimates, since scanning provides more information on rutting and pavement condition; additional information on guard rails, bridges, overhead utilities, signs, etc.

For this evaluation, Alabama DOT conducted a pilot project to see if the mobile scanning contractors in the state/region were capable of performing this type of work. They worked with the four vendors in the state willing to participate at their expense and scan a section of the future

I-22 (also known as Corridor X, see Figure 10 below) recently surveyed by Alabama DOT with conventional methods (e.g., total station at 50 ft. intervals) and with solid control points in place.

Figure 10.View of Pilot Section along I-22: Corridor X (Russell 2012).

Russell (2012) reports that the point cloud data delivered massive data files which can be difficult to manage even with new software tools. As for the data quality and comparison to the conventional survey, they found that 90% of the scan data tested within 0.05 ft., 70% within 0.03

ft. (absolute accuracy), and 75-85% of the scan data had a relative accuracy of 0.03 ft. +/- across the travel lane. Alabama DOT deemed that the scanned data was suitable for designing resurfacing projects.

3.1.3 Technology Costs and Resulting Savings

The benefits associated with the remote sensing technology were previously described and include: improved safety, time and cost savings, increased productivity, improved quality with the increased level of detail, accuracy and scalability. However, cost-benefit and ROI information is scattered and many of the case studies available have been conducted at a project level, not representing agency wide figures. The bullets below present the information gathered throughout this project.

As of December 2014, remote sensing technology cost ranges from $50,000 to $120,000 for a static scanning system to $250,000 to $1,000,000 for mobile scanning systems.

For the case study presented above in Section 3.1.2, Searle and Sridharan (2014) report savings of using existing mapping grade data vs. traditional surveying for a design project of 24% for cost, 22% for time, and increased safety.

Detailed studies are needed to assess cost-benefit, ROI. For example, when high definition survey data is released to bidders / contractors at advertising, cost savings may not be reflected in lower bids, but in more consistent bids, since contractors spend less time surveying and more time estimating.

o It is difficult to quantify this impact, but it means that there is less risk for bidders.

The use of high definition surveys with 3D laser scanning technology helps reduce construction contingencies.

Hurwitz et al. (2013) conducted a survey to assess the state-of-the-practice regarding mobile LiDAR at state DOTs. With responses from each of the 50 state DOTs, 6 additional transportation agencies and 14 mobile LiDAR services providers, they found that cost is one of the most significant challenges for adoption of this technology, and more evidence and education are need regarding benefit-to-cost comparisons.

Yen et al. (2014) present a cost-benefit analysis for the use of mobile scanning for the following highway applications: roadside feature inventory, bridge clearance measurement, and ADA feature inventory. Yen et al. (2014) explain that these programs are well defined in most state transportation departments and the corresponding data regarding historical and current expenditures is available to conduct such cost-benefit analysis.

o Note that most laser scanning applications for automation in highway construction, such as engineering grade surveys, Machine Control and

Automation, and construction inspection, are still under evaluation and implementation at state transportation departments, and there is not enough data for a comprehensive cost-benefit analysis as conducted by Yen et al. (2014).

3.2 UNDERGROUND UTILITIES LOCATION

Accurate identification of subsurface utilities involves a combination of 3D modeling software and underground location technology such as geophysical techniques. More accurate information regarding existing utilities is needed, especially for urban environments, to identify conflicts during design and avoid guess work and digging during construction. In addition, as-built utility plans can be completed for use in future projects and maintenance.

Figure 11. 3D underground utility map (Sundt 2011).

According to SHRP 2 (2012), “current technologies and tools can only find 80-90% of existing utilities, and finding the other 10-20% and successfully managing utility conflicts require new tools.” Utility conflicts identified during design and construction phases of highway projects result in significant cost, delays, change orders, claims, and damages. Therefore, several SHRP

2 projects were dedicated to develop new tools to help locate and characterize underground utilities, as well as new tools to identify utility conflicts and solutions.

The following bullets list the three SHRP 2 efforts and corresponding products most relevant to automation in highway construction and 3D technologies. It is understood that further development is required to make the prototype technologies developed viable.

R01A Technologies to Support Storage, Retrieval, and Utilization of 3-D Utility Location

Data: State-of-the-art model and guide for using and managing 3D utility data. The system will leverage GIS, GPS/GNSS, and other technologies to acquire, store, visualize, and integrate 3D positional and structural information.

R01B Utility Locating Technology Development Utilizing Multi-Sensor Platforms: Two functional prototypes were developed: a multi-channel ground-penetrating radar system to locate utilities in one pass and a new multi-sensor platform that combines electromagnetic induction and 3D ground-penetrating radar to produce utility location data.

R01C Innovation in Location of Deep Utility Pipes and Tunnels: Two technologies were developed to expand the zone in which underground utilities can be located and identified. Prototype long-range radio frequency ID and low-frequency acoustic location technologies were developed and tested.

There is also an ongoing FHWA research for “Feasibility of Mapping and Marking Utilities” to document the barriers for SHAs managing utility installations within the right-of-way (Quiroga et al. 2015). Table 4 presents a summary of challenges and solutions based on the SHRP 2 projects on utilities and the above referenced FHWA study.

http://onlinepubs.trb.org/onlinepubs/shrp2/SHRP2_S2-R01A-RW-1.pdf http://onlinepubs.trb.org/onlinepubs/shrp2/SHRP2_S2-R01A-RW-1.pdf http://onlinepubs.trb.org/onlinepubs/shrp2/SHRP2_S2-R01B-RW-1.pdf

Table 4. Summary of identified challenges and solutions for underground utilities location.

Challenge Solutions

Unknown or mistakenly recorded utilities

R01(A): State-of-the-art model and guide for using and managing 3D utility data.

Possible Solution:

Requirement for placement of tracers in utility permits. Need specifications for: placement, QA/QC, coordination, inspection, record keeping, etc.

Locating underground utilities across a variety of soil conditions

R01(B): Two functional prototypes were developed: a multi-channel ground-penetrating radar system to locate utilities in one pass and a new multi-sensor platform that combines electromagnetic induction and 3D ground-penetrating radar to produce utility location data.

Locating deep underground utilities

R01(C): Two technologies were developed to expand the zone in which underground utilities can be located and identified. Prototype long-range radio frequency ID and low-frequency acoustic location technologies were developed and tested.

Utility Characterization

Current technology ineffective at finding targets beneath clutter of other utilities and buried objects or significant depths in incompatible soil conditions, as is the case with electromagnetic locating equipment and conductive soils.

Utility marking and radio frequency tagging systems (RFID)

Lack of Return-on-Investment

(ROI) information, Data

Management (storage issues)

Ongoing FHWA research for “Feasibility of Mapping and Marking Utilities”

3.2.1 Implementation Efforts at State Transportation Departments

The state transportation departments that were interviewed under this effort indicated that the implementation of underground utilities locating technology has been limited. Due to existing workflows and policies, transportation departments are subject to inaccurate, low quality information that utility companies are currently providing them. In addition, for highway projects the liability for utility conflicts and relocation is placed on the contractor.

The state transportation departments survey by Quiroga et al. (2015) found similar trends, with only a few agencies using 3D technologies for utility installations. Quiroga et al. (2015) discuss in detail these and other challenges for transportation agency management of utilities in the right-of-way, and trying to transition 3D utilities data. Figure 12 shows a comparison between 2D traditional utility plans and the desired 3D model.

a) Traditional 2D plan view showing outline of tunnel and other underground infrastructure

b) 3D model showing tunnel and other underground infrastructure

Figure 12. Comparison between 2D plan view and 3D model for Northwest PATH Pedestrian

Tunnel, Toronto, Canada (courtesy of Hatch Mott McDonald).

3.3 3D DESIGN

3D design is a key process for implementing automation in highway construction. Singh (2009) explains that the implementation of computer aided design (CAD) software such as MicroStation and AutoCAD, and InRoads and Geopak (for road design) has evolved agencies to ‘pseudo’ 3D surveys and design, since the state of the practice is not producing truly 3D and complete roadway models. For example, all major components would need to be 3D (i.e. bridges and other structures); as also, basemaps would need to depict elements below, on, and above the ground surface (i.e. utilities) within the project limits (Singh 2009). WisDOT (Vonderohe 2013) also refers to this issue, making a distinction between the “3D Surface Model” (mainly for automated machine guidance and controls, see Figure 13) and the “Roadway Model” (documents elements from design to construction).

Figure 13. 3D view of a surface model for AMG (courtesy of Construction Engineering

Solutions, LLC).

Lead agencies are now working towards this concept of complete roadway models, also referred to as 3D Engineered Models, in most cases for major / mega projects and supported by consultant services. Gilson (2014) describes how large transportation projects involve multiple design and construction teams, and the 3D modeling is critical for stakeholder communication and coordination. These 3D Engineered Models are a collection of elements that comprise all aspects from design, and are considered 4D models when schedule information is incorporated and 5D when cost information is added.

Benefits of 3D models from design include creation of more accurate construction documents and 3D as-built plans,…