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Use of Automated Machine Guidance within the Transportation Industry (2018)

Chapter: Chapter 11: Future of AMG in Infrastructure Construction

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Suggested Citation:"Chapter 11: Future of AMG in Infrastructure Construction." National Academies of Sciences, Engineering, and Medicine. 2018. Use of Automated Machine Guidance within the Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/25084.
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Suggested Citation:"Chapter 11: Future of AMG in Infrastructure Construction." National Academies of Sciences, Engineering, and Medicine. 2018. Use of Automated Machine Guidance within the Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/25084.
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Suggested Citation:"Chapter 11: Future of AMG in Infrastructure Construction." National Academies of Sciences, Engineering, and Medicine. 2018. Use of Automated Machine Guidance within the Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/25084.
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Suggested Citation:"Chapter 11: Future of AMG in Infrastructure Construction." National Academies of Sciences, Engineering, and Medicine. 2018. Use of Automated Machine Guidance within the Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/25084.
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Suggested Citation:"Chapter 11: Future of AMG in Infrastructure Construction." National Academies of Sciences, Engineering, and Medicine. 2018. Use of Automated Machine Guidance within the Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/25084.
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Suggested Citation:"Chapter 11: Future of AMG in Infrastructure Construction." National Academies of Sciences, Engineering, and Medicine. 2018. Use of Automated Machine Guidance within the Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/25084.
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Suggested Citation:"Chapter 11: Future of AMG in Infrastructure Construction." National Academies of Sciences, Engineering, and Medicine. 2018. Use of Automated Machine Guidance within the Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/25084.
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Suggested Citation:"Chapter 11: Future of AMG in Infrastructure Construction." National Academies of Sciences, Engineering, and Medicine. 2018. Use of Automated Machine Guidance within the Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/25084.
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Page 133
Suggested Citation:"Chapter 11: Future of AMG in Infrastructure Construction." National Academies of Sciences, Engineering, and Medicine. 2018. Use of Automated Machine Guidance within the Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/25084.
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Page 134
Suggested Citation:"Chapter 11: Future of AMG in Infrastructure Construction." National Academies of Sciences, Engineering, and Medicine. 2018. Use of Automated Machine Guidance within the Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/25084.
×
Page 134
Page 135
Suggested Citation:"Chapter 11: Future of AMG in Infrastructure Construction." National Academies of Sciences, Engineering, and Medicine. 2018. Use of Automated Machine Guidance within the Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/25084.
×
Page 135
Page 136
Suggested Citation:"Chapter 11: Future of AMG in Infrastructure Construction." National Academies of Sciences, Engineering, and Medicine. 2018. Use of Automated Machine Guidance within the Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/25084.
×
Page 136
Page 137
Suggested Citation:"Chapter 11: Future of AMG in Infrastructure Construction." National Academies of Sciences, Engineering, and Medicine. 2018. Use of Automated Machine Guidance within the Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/25084.
×
Page 137
Page 138
Suggested Citation:"Chapter 11: Future of AMG in Infrastructure Construction." National Academies of Sciences, Engineering, and Medicine. 2018. Use of Automated Machine Guidance within the Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/25084.
×
Page 138
Page 139
Suggested Citation:"Chapter 11: Future of AMG in Infrastructure Construction." National Academies of Sciences, Engineering, and Medicine. 2018. Use of Automated Machine Guidance within the Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/25084.
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NCHRP Project 10-77 125 CHAPTER 11: FUTURE OF AMG IN INFRASTRUCUTRE CONSTRUCTION INTRODUCTION Rapid technological developments are propelling AMG towards new capabilities that are radically expanding and shifting the roles and identities of traditional surveyors, design engineers, agencies, contractors, and equipment providers. New paradigms are emerging for conceptualizing sites, designing new and different projects, constructing projects, and ultimately using and maintaining them. The future of AMG is one that will likely be abundant with innovative technologies, with advanced software, improved data interoperability, and new autonomous machine capabilities. To fully benefit, these developments must be stewarded proactively by a broadly inclusive AMG owner-designer- surveyor-engineer-construction community. How this community interact and work together is yet to be defined, but may require new models, training, and even development of new educational disciplines/professions. The following highlights some of the emerging AMG technologies and presents a creative consider the future at what might be possible. Whatever the future AMG landscape looks like, it will require planning and new ways of interaction to garner the full potential of this technology. New partnerships, research and development, and training across the AMG community will be key to accelerating AMG innovation. Also, building of discussion elsewhere in this report is the topic of data interoperability and future needs. EMERGING AMG TECHNOLOGIES This section of the report highlights technologies identified from the information review and expert contact group that are emerging AMG technologies. Figure 11-1 shows the GEOPAK/Inroads being used for 3D designs. This tool generates the 3D surface first, then 2D cross sections are generated later for sheeting and earthwork process. 3D design is an important cornerstone of the AMG process and is still emerging within agencies as identified in the project survey. Many agencies are in the process of considering 3D design and developing internal guidelines for it use. Figure 11-1 Example 3D Design Software used to Generate 2D Cross Sections (courtesy Brian Smith, Iowa DOT)

NCHRP Project 10-77 126 Figure 11-2 shows color plans. Although it may not seem like a significant departure from black and white plans, the concept of color is to add an additional dimension to the information conveyed in plan sheets. The colors shown in the plans are attributes with stored information as follows: • Light brown is the area that is getting graded • Green is the existing pavement in this stage • Blue represents the proposed paving in this stage • Red represents drainage and sign structures • Cross hatching shows the pavement removal areas (a) (b) Figure 11-2 Example of Color-Coded Plans (a) Plan View (b) Alignment with Geotechnical Information (courtesy Brian Smith, Iowa DOT).

NCHRP Project 10-77 127 Figure 11-3 shows yet another application of color sheets with a photo and line drawings to highlight a construction feature. Color in this case makes it easier to see the orange line, soil types, and vegetation. Although it may not seem like a significant innovation, use of color as part of design drawings has been limited due to concerns about reproduction, users’ ability to see distinction between colors, and overall reliance on color being consistently presented through all phases of design and construction. (a) (b) Figure 11-3 Example of Black and White versus Color Design Sheet with Notes (courtesy Brian Smith, Iowa DOT). Figure 11-4 shows the application of not only integrating color imagery, but linking the geospatial data in the image to x, y, z coordinates as captured from a stationary terrestrial laser scanner. Laser scanners are becoming less expensive, easier to use, and hold greater potential for integration into site evaluation, as-built recording, and design processes. Data generated from airborne LIDAR are also increasing becoming available for large area model generation, volumetric calculations, corridor mapping, and other engineering applications. Figure 11-5 shows examples of LIDAR imagery for defining a corridor and for large area flood mapping. The seemingly data rich environment of the future will facilitate innovative ways of implementing AMG technologies.

NCHRP Project 10-77 128 (a) (b) (c) Figure 11-4. Laser Scan Images showing (a) Integrated Digital Color Photo with x, y, z Geospatial Coordinates (b) Rendering for Volume Calculations, and (c) Digital Image with x, y, z Coordinates and Calculated 2 ft Contour Intervals (images courtesy CEER, ISU).

NCHRP Project 10-77 129 Figure 11-5. LIDAR Application to (a) Map Corridor, and (b) Define Larger Area Flooding (images courtesy of Iowa DOT). Figure 11-6 shows yet a further application of modeling complex geometries, which have been sources of uncertainty with AMG construction equipment due in part to lack of data. Powerful software tools are allowing for improved fidelity in model surfaces. In the future, these types of constraints should be virtually eliminated by knowledgeable designers. Using the model data, visual renders are also contributing to the AMG process. Figure 11-7 shows an example of a project rendering that was used for meeting to provide a clear representation of the project to the public. The visual nature of these renderings will facilitate important ways for communicating complex projects. It is even possible now to present the results with a polymer formed or printed physical scaled model. Figure 11-8 presents yet another evolution of the AMG process where multi-dimensional computer simulations allow users to embed themselves into the project and operate equipment to develop project level experience. This concept has the potential to allow both the designer and the contractor to optimize the building process. Unfortunately, there is very little theory developed to optimize and automate the site level construction processes. Figure 11-9 shows a relatively low cost unmanned aerial vehicle (UAV), or drone, with a high definition remote controlled camera. These devices hold promise for providing up-to-date color imagery of construction projects and getting information in challenging conditions, for example, a landslide. Use of these types of devices remains somewhat controversial due to privacy issues and partially restricted by FAA guidelines (see https://www.faa.gov/uas/). Figure 11-10 shows an image that illustrates the concept of integrating terrain information into visualization and adding data analytic capabilities to process productivity information and various machines. Data is available via wireless and mobile platforms. The emerging future of AMG is one supported by easy access to data via the cloud and wireless devices. By making the data available in the cloud it allows multiple users to access information real-time. Figure 11-11 shows how intelligent compaction data is collected via wireless cellular and displayed on a server with Google Earth in the background. This process occurs in near real-time allowing multiple users to access the information via a password protect website.

NCHRP Project 10-77 130 Figure 11-6. Examples of 3D Surface Renderings showing Complex Geometries (courtesy of McAnich Corporation and Iowa DOT) Figure 11-7. 3D Rendering and Visualization of Project (courtesy Brian Smith, Iowa DOT)

NCHRP Project 10-77 131 Figure 11-8. Simulated Construction Environment that Allows User to Operate Machine (image courtesy X,Y,Z Solutions) Figure 11-9. Inexpensive UAV with High Definition Camera.

NCHRP Project 10-77 132 Figure 11-10. Integrated Data Analytics and Mobile Viewing (image courtesy of AGTEK). Figure 11-11. Intelligent Compaction data as viewed from On-line Viewer (image courtesy of Trimble). Beyond the emerging advances with software modeling, simulation, and different ways of collecting and visualization information, machine systems continue to improve and advance opportunities to implement AMG solutions. Although now commonplace in earthwork operations, paving (PCC and HMA), milling, joint cutting, and excavation are all emerging AMG solutions (Figure 11-12). Figure 11-13 shows the application of a relatively new stringless paving process. This innovation is making it more feasible to do the white topping projects (Harrington, 2010) and eliminate the need to setup string lines. Eliminating string lines reduces staging areas and improves safety among other benefits. The equipment and field application of PCC stringless paving is discussed in Cable et al. (2009). For many of these technologies it is innovative equipment manufacturers that are developing AMG concepts and will continue to be the drivers behind modern technology for the foreseeable future.

NCHRP Project 10-77 133 Figure 11-12. Examples of AMG Machine Application.

NCHRP Project 10-77 134 (a) (b) Figure 11-13. AMG Application for PCC Paving (a) Site Level Setup and Equipment, and (b) PCC Stringless Paving Operations (images courtesy of Dale Harrington). THE FUTURE AMG PROFESSIONAL As discussed in Chapter 6, educational and training opportunity are provided by several sources, yet no sole source delivers all the required training. Several AMG stakeholders have realized the importance of training for the future success of AMG. Currently, FHWA hosts a website that promotes information for 3D engineering modeling (https://www.fhwa.dot.gov/construction/3d/). The website includes information on web-based training, webinars, workshops, field demonstrations, and has experts to serve their technical support center. Several concise technical briefs are provided. This program was established because of the “potential to cost-effectively accelerate highway pavement construction.” This

NCHRP Project 10-77 135 program was primarily designed to support the needs of agency design engineers and agency AMG implementers. AASHTO’s Technology Implementation Group also supports a website with basic information about AMG, AMG benefits, agency contacts, and small library of information (http://aii.transportation.org/Pages/AutomatedMachineGuidance.aspx) The way a road is designed, engineering and constructed today, is in a sequential and compartmentalized fashion. The disparate, sequential and compartmentalized fashion in which design, engineering and construction tasks place is inefficient and is the result of non-technical factors. The future picture that is developing is of an AMG process that is a seamless integration from project begin at the design concept phase, that progresses iteratively through design development and pre-design phases to bid documentation and beyond. DATA, STANDARDIZATION, AND INTEROPERABILITY As discussed elsewhere in this report, there is a need for new standards for representing sites, so that AMG can dislodge itself from iteratively re-inventing the wheel when it comes to site data formats and data interoperability. Developing a coherent standard for data can enable an iterative link between the design phases of a project and on-site construction. This bottleneck is the central challenge to enhancing interoperability between the components that comprise AMG. Remarkably, contour lines remain the topographic representation of choice also in the digital medium. Contour lines have been the standard for relief topographic representation for several centuries. They were developed primarily as a static representation of relief, first underwater (bathymetric lines), then on land (Konvitz, 1987). The AMG community is unique in its need to work between existing and proposed states of a project. While the contour line will live on in the palette of options, there is an opportunity to develop new standards now for the digital medium; to arrive at a new representation of topography for the 21st Century, and one that will fill the AMG community’s needs to work iteratively between existing and proposed: Contour lines have survived because they satisfy the following criteria: 1) 3D 2) compact/portable 3) editable 4) quantitatively accurate 5) reproducible Yet they suffer some serious disadvantages (Weibel, 1987 and 1992): 1) Planimetric 2) They are a secondary data source (reduced accuracy, cartographic generalization, etc.) 3) Interpolation: Contours are above all a graphical method of relief depiction, but a very poor sampling method. 4) Oversampling along contours, undersampling across 5) Terrain shape must be inferred in a holistic search process across multiple contours. To exploit this split, one can imagine an intermediate data type that represents the set of proposed geometries considered for a design, which can exist separately from the existing and proposed site data. What might these be? Here we have a proposed site design that consists of a set of line segments. The advantages of line segments over known topographic data formats (e.g., xyz points, grids, contour lines, TIN, TRN) are that line segments are: 1. Compact, 2. Simple and intuitive, 3. A uniquely digital solution, not an automation of analog methods, 4. Separate intermediate data descriptions of site change that decouple internal from external representations,

NCHRP Project 10-77 136 5. Mathematically equivalent so geometric control is achieved (i.e., 1 path + 1 blade = exactly 1 surface), and 6. Another criterion for geometric control because any geometry can be achieved with the blade + path metaphor. This is a brief discussion of geometric representation, but similar discussions are necessary for analysis, visualization, and project management issues (among others). These will most probably involve taking on Big Data, as solutions will require exceptional technologies to efficiently process large quantities of data within tolerable elapsed times. Real or near-real time information delivery is one of the defining characteristics of big data analytics. AMG participation in these developments will be key to the success both interoperationally and algorithmically. AMG IN THE FUTURE: CONCEPT FOR LAND DRONES How far can AMG be pushed to safely automate the road building process? The following is an account of what the future may have in store for AMG. Imagine a land drone that is part Mars Rover (Fig. 11-14), part autonomous vehicle, part docking station, part wireless information hub, part land laboratory. Figure 11-14. Autonomous Mars Rover (http://news.nationalgeographic.com/news/2012/08/120806- mars-landing-curiosity-rover-nasa-jpl-science/) Like the Mars Rover the AMG land drone is remotely maneuverable over many kids of terrain. It is tough from the point of view of weather and elements. It can operate day or night, continuously round the clock. It is heavier than a Mars Rover, and has a different mobility system, where it rolls or creeps, and has more agility and degrees of freedom than traditional earthmoving equipment. The central part is the “brain” of the unit. Its perimeter may change in a modular fashion like a docking station, which may receive or deposit tools, samples, information, and in general interact with the world physically. Shovels, graders, paving “trailers”, etc. could be docked with n configurable alternative combination. The central brain would possess the system’s center of gravity, and would “know” how to use/wield/control its modular changeable docked parts. The central brain could also serve as a mobile lab to monitor analyze air/soil/core samples from its environment. It would also control position, precision, navigation, speed, etc. The modules docked onto the drone’s perimeter would either be pre-equipped for a specific project site, or shovels or equipment or lab samples could be added or exchanged from locally sited drone portals.

NCHRP Project 10-77 137 The AMGP would drive and control the system remotely from the safety and comfort at a remote location observing and driving like how an airline pilot flies an airplane. Engagement would be passive or intensely active depending on task complexity and conditions. The drone would be involved from project inception of the “simple road” with route planning and testing and analysis and mapping, and through design development and testing, and iterative passes of construction. It would also play a role in post-construction monitoring and surveying and failure detection and road repair. The system would be designed for obstacle avoidance and safe operations. Data flow would be to and from the cloud to the drone, where data would be backed up, processed analyzed, distributed. Multiple or single machines could access and participate in a project in a distributed fashion; multiple land drones could be operational simultaneously. For the simple road to be designed and built, a route first needs to be determined. At the same time, preliminary designs for the road profile and its key features are being developed or adapted. These tasks occur with high precision real-time updated multi-dimensional imagery and digital models exchanged with the cloud by the AMGP team to and from the land drone unit. A multi-dimensional interactive environment is used, where quantitative, qualitative and iterative correction and revisions are closely integrated. Tasks being accomplished include: • Survey and mapping of existing conditions, • Survey and mapping of alternative routes, • Cadaster research, • Imminent domain application and acquisition, • Design development, • Construction planning, and • Construction execution, • Post-construction review and • Maintenance tasks, including • Failure detection and repair at varying time points after project completion. Each task possesses both a remote “file” component and an active site component, which can be remotely achieved with the land drone. The look and feel of the GUI available to the AMGP for site design would possess three main characteristics: 1. See 3D: The ability to visualize and interactively see a multi-dimensional model of the site or project area of interest, including at a minimum: a. Topography, b. Water systems, c. Plant systems, and d. Weather/phenomenological effects. 2. Control 3D: The ability to geometrically edit/manipulate/sculpt/modify/control user- specifiable sub-areas of the model. The AMGP uses a site design toolbox that consists of three categories of tools: a. Library of Shape Primitives: library of parameterized forms, both found and constructed. For example, for topography: i. a set of exit ramps, ii. a set of drainage culvert geometric features iii. a set of embankment geometries based on soil type, etc. b. Operators: functionality to edit/modify site geometry. Translate, rotate, rescale, extrude, skin, patch, clip, trim, copy, Boolean add/subtract/maximize/minimize, exaggerate, warp, morph, merge, knit, append, etc. c. Simulations within a dynamic, real-world physically based site context near or far from the project. Iteratively evaluate options to evaluate scale, slope, comfort, aesthetics, etc.

NCHRP Project 10-77 138 3. Analyze 3D: The. look and feel Geospatial mapping example. The ability to analyze these sub- areas in several key respects, including: a. Cut fill volume quantities, balance calculations and balance recommendations, b. Slope, c. Geotechnical aspects (soils, structure, stability, suitability, recommendations) d. Line of site, e. Drainage, including highest points, lowest points, drainage channels, drainage basins, storm-water run-off, f. ADA compliance, and g. Geospatial mapping. Unlike Euclidean geometries found in architecture, and translated rather easily and directly into BIM and CAD, the geometry of the landscape, and the parameterization of these geometries remains a non-trivial algorithmic challenge, and is a key research area. Perhaps, not enough people in the engineering and affiliated AMG professions yet appreciate what a bottleneck these representational challenges represent to progress. Computing offers tighter integration of these ideas into the iterative design cycle. And this is not just at the workstation, rather the technical integration of field-based heavy equipment and tools means, they too may become part and parcel to the iterative cycle (“end-to-end” AMG capability). This is unprecedented and represents some transformational possibilities in: • The way we work, • The way we conceive of sites, roads, what gets built and • How a design is built, and ultimately • How a design functions in the landscape and how it is experienced. AMG CONTRIBUTION TO SUSTAINABILITY Sustainability and the integration of natural process dynamics and ecological health principles in the AMG process is emergent and will only feature more prominently, as these technologies are looked to as powerful partners to protect and steward environmental health. Example: Linearization of the landscape. CE’s and LA’s are always accused of linearizing the landscape. Perhaps this is because ecological health remains difficult to represent computationally. Visually and in other ways. Simulation of physically-based dynamic ecological systems, therefore, and the novel representational challenges that are being developed will be key to the eventual acceptance and sphere of influence AMG will have. Sustainability priorities will carry the day. CONCLUSIONS Several emerging AMG technologies are making it possible to collect, analyze, and visualize, data, and automate processes. Increasingly, position measurement capabilities and automated features are being integrated into construction machines. Software advancements are making data interoperability better and the future is seemingly very bright for AMG innovations. Computers are uniquely suited to crunching numbers, which allows repetitive and quantitative aspects of tasks to be automated. When the algorithms available to future AMGPs are sufficiently robust and versatile, specialized training (e.g., in volume calculations, geotechnical structure stability, asphalt mix composition, etc.) need not be the sole purview of the traditionally trained professional in these areas. Appropriate “friendly” tools may be available on the AMGP’s desktop that incorporate checks and balances to protect against error. In fact, human error could be minimized in similar ways that the automated cars will reduce the number of human-induced vehicular accidents that occur on highways nationwide.

NCHRP Project 10-77 139 Technology will enable these changes. The AMG community should embrace this potential, rather than see it as threatening. A way to embrace it is to set aside traditional domain loyalties and collaborate to imagine an interdisciplinary scenario that would serve the best interests of building the next generation of roads (building sites, mining pit, etc.). Implications for this include: • New road types and template standards may be possible • A different configuration of stakeholders … • A more adaptable and inclusive process • Smaller footprint of disturbance, thus more sustainable and environmentally responsive. • FAMGP training will be different – interdisciplinary with an underlying dominance of • IT skills and algorithm design will prove to be most influential on progress in AMG

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TRB's National Cooperative Highway Research Program (NCHRP) Web-Only Document 250: Use of Automated Machine Guidance within the Transportation Industry studies automated machine guidance (AMG) implementation barriers and develop strategies for effective implementation of AMG technology in construction operations. AMG links design software with construction equipment to direct the operations of construction machinery with a high level of precision, and improve the speed and accuracy of the construction process. AMG technology may improve the overall quality, safety, and efficiency of transportation project construction.

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