This research project would aim to develop a Primer or Guidance document to help agencies tasked with managing infrastructure (including pavement and bridges) to assess their current data, data collection processes, and data needs to best position them to be able to take advantage of burgeoning artificial intelligence techniques to develop increasingly accurate predictive models regarding their infrastructure.

The quality of data is extremely important – “garbage in, garbage out” - and quality of data in terms of accuracy and precision is already getting much needed attention. However, while many agencies are actively improving collection of accurate and more data, collection the right quality data for accurate and precise prediction requires an additional level of scrutiny.

Collection of more accurate and precise data will undoubtably increase the accuracy of predictions, accurate predictive modeling also relies on understanding the underlying variables that affect the predictions. For example, variables that might affect the structural deterioration (for instance in the next time period) of an infrastructure element such as a pavement management section, might include:
- Structure information such as layer thicknesses and materials
- Environmental conditions such as temperature means and variation, rainfall etc.
- Load information such as traffic and truck traffic
- Current condition such as current cracking, rutting and roughness information
- Current condition such as layer properties and structural strength
- Information on previous maintenance, rehabilitation and reconstruction actions

Similar attributes would be considered significant variables for deterioration prediction in bridges, and this would also apply to many other non-bridge, non-pavement types of infrastructure assets.

Statistical analysis of this type of data for predictive analysis purposes is not new and Analysis of Variance (ANOVA) techniques have been used in this area for decades. However, with the advent of automated data collection techniques and with the quantity of available data growing at a considerable rate (so called ‘Big Data’), various types of AI such as artificial neural networks (ANNs) and deep learning techniques, are beginning to supersede some of these traditional statistical techniques. The ‘training’ portions of these techniques will require accurate and repeatable data as well as information on significant variables.

In addition, one the most valuable aspects of AI is the ability these types of techniques to continuously learn and improve. In this respect, it is again very important for agencies to understand how this learning could be accomplished, not just initially but continuously over time, using processes that involve continuous updates (e.g. through crowd sourcing). Agencies would therefore benefit considerably by having guidance available to help them set up their data capture and governance techniques to best benefit from AI modeling, training and continuous learning in the future.

Ideally, an agency would collect data that has the necessary attributes to facilitate an AI analysis and have processes in place that would allow continuous learning such that predictive modeling for the agency would continue to be trained and improved as the AI continued to learn. The current reality is such that condition data that is being collected may not be easily utilized in an AI analysis. The consequence is that the complicated decision-making process that highway agency executives depend upon may not be producing the level of accuracy in condition and funding projections that is required to make funding decisions in their investment strategies.

Synthesize best practices for workforce development and training in order to enhance the capabilities of a TAM team/staff or attract internal staff to become involved in TAM program/implementation.

Document and provide examples of condition assessments for all types of assets.

Create case studies addressing noteworthy applications of big data analytics to TAM.

This is a note test.

Develop a framework, recommended actions, and synthesis of noteworthy practices for agencies to use in incorporating change management strategies in TAM practice.

• Asset conditions are typically determined currently in separate silos - leading to asset treatments that are applied on varied schedules by asset (pavement, bridges, culverts) even over the same corridor.
• Significant resources may be misallocated on treatments applied at the wrong time due to lack of coordinated corridor planning.
• Corridor planning can organize the asset treatments — while also looking at environmental issues, congestion, and safety
• There may be other issues such as operation needs in a corridor as well.
o “Project delivery” can be achieved more efficiently because projects are organized into a corridor delivery strategy. Projects can be peeled off as funding is available
o Public can be engaged all at once instead of multiple times for multiple projects.
o Minimize contractor costs

Develop guidance on an asset management corridor planning process to prioritize and schedule project delivery for cost effectiveness while also considering mobility/accessibility issues, drainage, and more.

• Conduct a review and evaluation of existing agency corridor planning processes with respect to transportation asset management
• Synthesize noteworthy practices in asset management corridor planning
o Identify potential case studies targeting specific corridor planning scenarios
o Develop a framework for corridor plans that can be applied for better asset management and resource allocation
• Conduct targeted stakeholder outreach (interviews or similar) to validate and further develop noteworthy practices and framework (consider whether research statement addresses inclusion of international practice)
• Develop asset management corridor planning guide outline and complete how-to guide
o Identify steps for agency necessary to address, for example: potential project areas; asset inventory/proposed treatment schedule; traffic volume/transit analysis; land use inventory and future land use; drainage issues; financial resources, schedule and coordination).
o Identify candidate case studies
• Drawing upon review and outreach efforts, develop 3-6 case studies for inclusion in the guide
• Plan and deliver three regional workshops to present guide and framework and advance corridor planning at DOTs/MPOs

• Asset management corridor planning how-to guide including case studies
• Workshops to introduce guide and advance corridor planning

Agencies have made progress in implementing TAM within their agencies. The impact of TAM will be much greater if stakeholders are engaged as a part of the decision-making and TAM approaches were collaborative for given geographic areas.

Develop communication tools and methodologies for engaging stakeholders in TAM program activities such as strategies development, performance management implementation, and budget development.

• Collect existing documentation of best practices related to TAM stakeholder engagement and communication
• Consider conducting a synthesis of practices used by agencies to communicate successfully the importance and value of TAM
• Package communication and other engagement resources from existing examples in a way that makes it possible for other agencies to use it for their stakeholder communication and engagement needs
• Assess the stages of maturity in communication and engagement and determine what actions and resources are most relevant to advance practice given current practices
• Develop guidance on when stakeholder engagement is important and what processes and products are most useful at each engagement opportunity
• Develop new resources that support the guidance

• Communication portfolio that allows asset owners/managers to draw on best practices from others during TAM program activities to engage stakeholders
• Stakeholder communication and engagement guidance

• Recent NCHRP research products have documented data governance techniques and provided tools for agencies to assess their current data governance practices and identify strategies for improvement.
• NCHRP 08-115 (publication pending) included data governance as one of several foundational activities for improving use of data and information for transportation asset management. An NCHRP 20-44 proposal is in process to conduct pilot implementations of the guidance and assessment tool developed through that project, and produce supplemental guidance materials based on the pilots.
• Many DOTs are implementing data governance – through establishing governance bodies, defining data stewardship roles and putting standard processes in place. The AASHTO Data Management and Analytics Committee has established a Chief Data Officer (CDO) peer group to enable ongoing sharing of data governance practices.
• This project would build on the established base of prior and ongoing work on data governance. It would focus specifically on providing specific examples or models that can be applied to help advance asset management practice through data governance.

Provide support to implement the data governance practices and processes recommended through NCHRP 08-115, Guidebook for Data and Information Systems for Transportation Asset Management.

• Conduct outreach to identify implemented examples of transferable TAM-related data governance practices. These might include:
o role/responsibility descriptions for asset data stewards and asset management system owners,
o charters for TAM advisory bodies or governance groups,
o asset data-related policies or guidance documents,
o flowcharts or process descriptions for initiating new asset data collection efforts,
o work products related to establishment of data glossaries, catalogs or standards,
o asset data quality management plans or process descriptions, and
o asset data MOUs or agreements.
• Conduct a series of follow-up interviews to document the processes by which each of the identified examples were developed, and to seek permission for sharing the examples.
• Make the documented examples accessible (via the AASHTO TAM Portal and/or the AASHTO Data Management and Analytics Committee website)
• Conduct a webinar highlighting selected examples – featuring the DOT staff who were involved in their implementation.
• Recommend an ongoing mechanism for periodically refreshing the body of examples collected through this effort.

• Library of documented examples
• Webinar slides and recording
• Recommended approach for ongoing updates to the body of examples

• It’s difficult to communicate the value of an asset management approach to the public.
• In many cases agency leaders and stakeholders, including the public, may not see discernable benefits from TAM, reducing support for a preservation-focused investment strategy and/or improved systems and data required to support a TAM approach.
• Research has been performed in the past regarding how to calculate the return on investment (ROI) of TAM systems and how to communicate the value of preservation. Also, private sector entities use a separate set of approaches for evaluating the benefits of providing transportation as a concession.
• Additional research is needed to quantify the benefits of TAM generally, and incorporate consideration of other factors such as sustainability, equity, resilience, etc.

Develop a framework and guidance for calculating and communicating the overall benefit of improved asset management approaches to transportation agencies, transportation system users, and society of improved asset management approaches. The framework should address monetized benefits, as well as issues such as equity, sustainability, and resilience. Illustrate use of the framework and examples through a set of pilot studies of U.S. agencies.

• Literature and practice review
• Develop TAM benefit framework
• Prepare guidance for implementing the framework
• Perform a set of pilots to test and refine the guidance, as well as to help illustrate the benefits of TAM
• Provide updated examples of effective communication of TAM benefits
• Prepare a guidebook detailing the framework, guidance, pilots and communication examples.

• Guidebook for calculating and communicating the benefits of a TAM approach
• Spreadsheet or web-based tool transportation agencies can use to perform their own calculations following the guidance.

Managing risk is a critical component of asset management. On a day-to-day basis transportation asset managers spend much of their time responding to or mitigating a large number of risks, which may range from external events that damage transportation infrastructure to unplanned changes to budget or workloads resulting from unexpected events. Various recent and on-going research efforts aim to improve approaches for risk management for transportation agencies. However, most of these efforts treat risk management as a high-level activity. Further research is needed to develop quantitative, repeatable approaches at the appropriate staff level, to assessing and identifying the highest priority risks transportation agencies face in managing physical assets. This project aims to develop such approaches to assess risks (e.g., financial, strategic, operational, political, environmental, technological, social justice risks) and incorporate them into life cycle analysis and planning efforts.

The objectives of this research are to:
• Generate risk identification techniques to determine high risk threats at project and network levels,
• Develop quantitative, repeatable approaches for assessing likelihood and consequences for these threats,
• Develop visual, interactive characterization methods (e.g., dashboards) to reflect an agency’s level of risk and the effectiveness of proposed mitigation actions,
• Allow risk and resilience to be on par with traditional performance measures.

High risk threats to be studied include, but are not limited to, extreme events (e.g., earthquakes, fires, hurricanes, avalanches, tornadoes), asset failure (structural and operational), financial, strategic, political, environmental (e.g., sea level rise, flooding), technological, and social justice risks.

The final deliverables could include guidebook with a spreadsheet or a framework for assessing high risk threats and incorporating the results into TAM efforts. The guidebook should feature a comprehensive review of existing literature and current practice. It should present a standard definition of resilience as well as step-by-step instructions to develop models, methods, and metrics for estimating resilience of highway systems to high risk threats. Pilot studies should be conducted with select agencies to test the guidance and calculation procedures.

The target audience for the research results is asset management and risk-management champions at state and local government transportation agencies. The results of this project will potentially empower these individuals in convincing other decision makers in these agencies to take actions that not only align with traditional performance management objectives but also that result in lower risk and higher resilience for the whole transportation system. The results of this project can also be effective in communicating the rationale behind risk-based decisions to the general public. Due to legal implications of identifying and documenting risks, the research and final product should include advice on how to protect the agency from litigation if they cannot implement a recommended action.

Risk assessment is at the core of implementing a risk-based asset management approach. Therefore, FHWA and AASHTO view this as a subject of great importance. In addition, risk management cuts across all areas of a state DOT’s business and just about any AASHTO Committee and any state DOT and local agency could realize benefits from these research results.

The Moving Ahead for Progress in the 21st Century (MAP-21) transportation bill established federal regulations that require each State Department of Transportation (DOT) to develop a Transportation Asset Management Plan (TAMP), and implement Performance Management. These regulations require all DOTs to utilize nationally defined performance measures for pavements on the National Highway System (NHS). These nationally defined performance measures (referred as PM2 hereafter) are aimed at providing nationally consistent metrics for DOTs to measure condition, establish targets, assess progress toward targets, and report on condition and performance. Furthermore, Federal measures provide the Federal Highway Administration (FHWA) the ability to better communicate a national performance story and to more reliably assess the impacts of Federal funding investments.
State DOTs are expected to use the information and data generated from these Federal measures to inform their transportation planning and programming decisions. However, State DOTs are finding discrepancies between pavement conditions from PM2 measures as compared to their internal, state-developed measures. This discrepancy hampers the adoption of the PM2 pavement measures as the primary input into condition summary reporting and pavement investment prioritization and decision-making. In other words, State DOTs do not have confidence in the Federal measures, primarily because these measures cannot be used to inform decision-making processes such as investment decisions. Furthermore, the resulting differences between state metric-determined and federal metric-determined network conditions creates confusion among the public, senior executive staff, and legislative bodies, along with non-DOT owners of NHS assets.
As mentioned before, FHWA needs to collect consistent Federal measures across all State DOTs to assess the impact of Federal funding investment at the national level. However, State DOTs have been collecting pavement performance data for decades and used this data to inform their pavement management systems and processes to address specific needs. Typically, the data collection processes cover state-owned pavements and not only NHS pavements, which brings another layer of inconsistency. For this reason, there is a need for more flexible metrics that can be aligned to performance measures currently used by State DOTs and support decision-making processes such as investment decisions.

The objective of this research is to:
1. Evaluate current federal pavement condition measures (Ride Quality, Rutting, Faulting, and Cracking), performance thresholds, and overall performance measure with respect to:
a. Consistency – across various pavement types, network designations, and lane configurations
b. Usefulness – in network-level pavement condition summary and asset management decision-making, prioritization, and forecasts; and
c. Alignment – with state established pavement condition metrics

2. Provide recommendations to improve existing measures and/or identify metrics that better reflect pavement failure mechanisms and enhance decision-making taking into account not
only the assessment of current and future condition but also their implications in economic analyses of long-term maintenance and rehabilitation. Evaluate pavement leading indicators as an alternative to the current version of the PM2.

3. Identify and address in detail specific challenges for each condition measure (Ride Quality, Rutting, Faulting, and Cracking) for consistency, including thresholds. For example, determine if wheel path cracking considerations could be revised to provide more consistent results across pavement types (e.g. composite, concrete) and pavement widths (e.g. <12 ft.) 4. Evaluate structural capacity indicators for potential consideration as a Federal measure.

Proposed research activities include:
1. Conduct outreach interviews to State DOTs and evaluate DOT publications (e.g TAMPs) to:
a. Capture current uses for federal and state-specific pavement condition metrics and their relative strengths and weakness with respect to identified network-level uses
b. Quantify the extent of the State DOTs’ differences with current federal pavement metrics
c. Capture alternative procedures states are using to determine and communicate pavement condition and/or failure as well as network-level decision-making
d. Source State DOT condition data sets, including corresponding state and federal ratings and network-level pavement maintenance recommendations

2. Conduct a comparative analysis between state and federal measures and determine the ability to utilize federal measures to replicate network-level decisions.

3. Evaluate alternative methods of federal measure with best practices of state measures to develop a list of alternative methods that could be used for pavement management measures and meet both State and Federal needs.

4. Provide summary and comparison of current vs. alternative methods with respect to evaluation criteria at national and individual state levels

5. Provide guidance on how to enhance the utility of current federal measures and/or condition thresholds and recommend revisions in a format useful to adoption into the HPMS Field Manual

Desired products include:
• Evaluation of federal measure with respect to consistency, usefulness, and alignment
• Guidance on how to increase the utility of current metrics and/or thresholds
• Recommendations for revised pavement condition metrics and/or thresholds
• Recommendations for updated HPMS Field Manual

This topic is of significant interest to AASHTO, TRB, and the DOTs, having ranked third amongst potential NCHRP topics in the recent TAM Research Prioritization conducted as part of the 2020 Mega Meeting of the AASHTO Subcommittee on Asset Management, in cooperation with the TRB Asset Management Committee (AJE30).
The following are organizations and contacts who may be interested in using the results of the research and supporting its dissemination:
• AASHTO Committee on Performance-based Management: Tim Henkel, Chair (Minnesota DOT, (651) 366-4829, [email protected]), Matt Hardy (AASHTO, (202) 624-3625, [email protected])
• AASHTO Subcommittee on Asset Management: Matt Haubrich, Chair (Iowa DOT, (515) 233-7902, [email protected])
• FHWA Office of Asset Management: Steve Gaj (FHWA, (202) 366-1336, [email protected]) Tim Henkel, TAM Expert Task Group Chair (see contact above)
• TRB Asset Management Committee (ABC40): Tim Henkel, Chair (see contact above)

• State departments of transportation (DOTs) and metropolitan planning organizations (MPOs) across the United States are required to establish performance targets as part of their asset management efforts. The target- setting requirements for transportation performance management (PM2) of pavement and bridge condition generally require agencies to consider three factors; the measured condition of the assets, expected deterioration over time and project level accomplishments. The measured condition of the asset is the ultimate measure of progress and an effective way for agencies to demonstrate that they are making progress as required by federal regulations.
• Research assessing the consistency of National Bridge Inventory (NBI) condition metrics has found variability between individual inspectors when inspecting “control bridges” for study. In other words, there is the potential for any given bridge inspector to assess the current condition of same bridge differently. This variability means that the conditions of bridge could improve in the absence of a project just by having a different inspector interpret the field condition differently. A similar potential exists for pavement condition assessments. This demonstrates the potential inconsistencies due to human interaction, but the same could be true of technologies if applied or calibrated differently across agencies.
• Pavement and bridge conditions rely on assessment methods that are subject to variability from one assessment to the next and from one assessor or one technology utilization to the next. This variability may occur in the absence of projects or significant field deterioration. This research project would attempt to evaluate the impact of condition assessment variability on agency wide target setting required for asset management.

The outcome from this effort will benefit quality assurance (QA) methods for data collection and inspection efforts, quantify the variability and sensitivity in target setting for DOTs, and help budget planning for asset inconsistencies.

• Review and summarize existing published research related to the
• consistency of field-assessed pavement and bridges whether based on human interaction or applied automation, and include a review of training programs associated with human and automated assessments. Additionally, review research on the impact of assessed condition variability on target setting.
• Review NBI and Highway Pavement Monitoring System (HPMS) submittals over multiple years to identify examples of spontaneous improvement or rapidly changing conditions from one assessment to the next and assess the sensitivity of condition assessment variability on target setting in transportation asset management.
• Develop a methodology and guidance manual to define the uncertainty associated with variability in condition assessment when setting asset management targets and provide means to rectify inconsistencies in the assessments when they appear.

• According to FHWA’s transportation performance management (TPM), the purpose of transportation asset management is to provide the most efficient investment of funds. This decision-making is being based on data that is subject to variability. Understanding and quantifying (if possible) the impact of data variability will allow federal, state, and local agencies to recognize the importance of data quality and how it might impact their ability to deliver projects and strive for the national transportation goals. The outcomes and benefits are:
o Showcase the importance of quality and consistent data collection methodology
o Tie the data to decision making and funding
o Evaluate the impact of condition assessment variability on agency wide target setting
o Highlight progress on 490.319(c) Data Quality Management Program
o Provide states and federal a baseline expectation for changes in annual variability in measures, failure to reach targets, and/or best practices to avoid data quality issues.

• Since the performance measures are consistently tied to specific data inputs, each state could use this research to understand the potential volatility in target setting and performance measures. The summary of best practices and pitfalls will also allow transportation agencies and vendors to improve inspection protocol. Testing of the data should be a part of the research, with a few select agencies comparing potentially the same data in a single year across multiple sources or reviewing the historic trends of individual data pints to highlight inconsistencies and the impact of those inconsistencies to overall measures and targets.
• This research would best be shared in an open forum or webinar so all agencies and consultants tasked with data management can obtain the information. The AASHTO Performance Management Committee should be interested in supporting this research to ensure that the performance measures produced by transportation agencies are of the highest quality.