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Emerging technologies hold the promise of transforming asset data collection for transportation asset management such as the use of drones for inspections, LiDAR field data collection, continuous monitoring of real-time sensor data, and more. While the technology has been transforming, MAP-21 and the Fast Act jump started at many agencies in attaining an inventory of infrastructure assets and transportation data. At the same time, accessibility and affordability to collect high volumes of asset inventory data, such as LiDAR point cloud data, present the problem of how agencies can visualize and manage such large amounts of data and integrate the many layers for each transportation asset management plan. Now that the need for such data is federally recognized, further research is needed to understand what the latest technologies for asset analysis can offer an agency as well as how frequently that information needs generated.
Research is needed in the following areas:
• Address the adoption and practical application of these technologies and the rapid pace of technological advancement.
• What level of extraction detail and frequency interval is needed to support TAM at both the state and local levels and how can the condition assessment be applied to the performance measures of both pavement and non-pavement assets?
• Further investigate what tools are capable of visualizing asset extraction layers, as well as presenting such data to all stakeholders in powerful GIS formats with standardized TAM graphics for universal interpretation.
Among the many difficulties raised by COVID-19, the pandemic does have the potential of affecting asset management practices in diverse ways. On the one hand, reduced traffic might reduce road maintenance costs; on the other hand, ordering more goods might increase truck traffic and thus increase deterioration. Even if deterioration were the same, the road agency would always have the option of utilizing a less expensive treatment alternative and thus reduce the capital needs and maintenance budget.
● FHWA case study on fiscal management during pandemic (focus on accomplishing work opportunistically vs. narrow risk-management focus)
● 2020 State DOT COVID-19 Response Survey: Use of Transportation Data and Information for Decision Makers https://www.tam-portal.com/document/dot-covid19-data-survey/
● Survey and interview State DOTs and others as to their practices during COVID. For example: observe their budget outlays, activities performed and data collection.
● Focus on uncertainty in general - such as funding uncertainty; the results could be utilized for good practices not just in times of widespread disease, but also for times of economic austerity such as a recession. Note: The visualization committee (AED80) has been kicking around a research idea related to how to VISUALIZE uncertainty. Could be a good opportunity to collaborate with that TRB committee. Anne-Marie McDonell and Matt Haubrich are both on AED80 so feel free to reach out.
● Potential to focus on risk management with respect to federal TPM target-setting (rather than risk management with respect to funding uncertainty).
Question of understanding impacts vs. position for post-pandemic
Several economic optimization methods are linked with TAM project selections. One of the economic indicators in measuring them is the ROI (which can be defined in various ways), but there are others such as NPV, IBC, FYRR and more. This research needs statement refers to the need of connecting prioritization / different approaches to asset management (such as optimization) and TAM project selections and economic indicators.
There are several known methods of estimating the maintenance backlog – via budget (raising the network to a given level within a given number of years), length or percentage of the network under a given maintenance standard (such as PCI, PSI, IRI or other indicator),
This question is usually dealt with in road assets but can be expanded to bridges and other assets as well. It is part of a life cycle cost analysis when the evaluation is performed on different treatments which are differentiated by their frequency (usually every X years) and thus influencing their cost. Many Asset Management Systems incorporate this kind of analysis.
• FHWA TAM Expert Task Group summary of this topic
• Potential R&I-sponsored research effort addressing equity
This synthesis will assess the use of equity, economic, and environmental indicators in TAM calculations and decision-making.
The objectives of this research will examine broadly:
• How State DOTs and MPOs are linking and including asset management decision in their traditional planning processes
• How asset management and the TAMP can be better integrated within an agency’s traditional planning process,
• What resources are needed to support State DOTs and MPOs to better connecting their TAMPs with the required planning documents.
Research is needed on the importance of data governance from the conception of a project’s data dictionary, through the inventory and condition assessment and continuing with the data management and integration into transportation asset management systems. A question worth pursuing is whether all aspects of language, wording, numbering, and measurement units should be standardized or if template guides could be developed for each agency to standardize their unique asset type requirements, but in a nationally recognized format for easy translation.
After establishing governance routines for asset data collection and management, the next phase of research would involve the security aspects of an agency’s data as well as the quality assurance measures applicable to grow confidence in the data’s quality. A full review of best practices for data security procedures could break the barrier of IT to asset manager. Additionally, once definitions and governance procedures are established, the quality assurance process becomes more stream-lined and gives better confidence to the decision makers.
Asset managers know the data they need, and the data collection methods have been identified. What is needed is guidance on how to use the available data collection methods to meet the needs of asset managers.
BIM standards need to account for the fact that we have less data on existing assets than newer assets. However, it is existing infrastructure that has the most needs.
● FHWA - Identifying Data Frameworks & Governance for Establishing Future BIM Standards
● AED80 has a subcommittee on BIM, who has a sub-sub committee on BIM & AM
● PIARC TC 3.3 has a group working on TAM/BIM integration.
● NCHRP Report 831: Civil Integrated Management (CIM) for DOTs.
● Guidance on establishing BIM data governance and quality standards to support asset management.
● Recommend standards for data transfer between data collection and asset management systems.
● Develop maturity scales for BIM implementation and establish appropriate maturity level for integration of TAM
● Research on BIM applications to support DOTs' data governance specific to the collection of data by one part of the agency can be used directly by other parts of the agency
● Evaluate cost effectiveness of collecting and managing data through BIM at a sufficient level of quality.
● Aligning the focused but detailed project-level data with network-wide but less detailed TAM data.
Due to external stakeholder requirements and expectations (e.g., MAP 21 and FAST Acts) as well as internal DOT uses, DOTs typically collect pavement condition data (i.e., roughness, cracking and rutting or faulting depending on the pavement surfaces) on an annual cycle. However, disruptions of typical agency activities related to COVID-19 have resulted in data collection challenges, focusing attention on potential impacts of missing a data collection cycle. DOT may also face unforeseen workforce, contracting, data collection or processing challenges or other issues which could result in missed pavement data collection. In these cases, DOTs would benefit from understanding the range of potential impacts as well as potential mitigation strategies available to address these issues. Furthermore, in times of reduced budget, DOTs may desire to reduce the frequency of data collection, however should be informed of the potential impacts of that decision.
In the recent past, the FHWA sponsored a project which resulted in publications analyzing the impact of pavement monitoring frequency on pavement performance prediction and management system decisions (Haider et al. 2010, 2011). This study analyzed pavement sections from the Long Term Pavement Performance database and recommended monitoring cracking at a 1-year interval and roughness every 1 to 2 years. The proposed study will further investigate this issue and expand the analysis on the implications of missing a data collection cycle in their transportation management plans. Given that the FHWA reporting requirements are fairly recent, there is not much in the transportation literature about the impact of missing a data collection cycle. Furthermore, little information is available on potential strategies available to mitigate the impact of incomplete condition data.
1. Evaluate the impacts of incomplete/missing annual pavement data collection to various aspects of agency asset and performance management, including technical considerations, such as network-level condition summary and performance forecast, maintenance, rehabilitation, and reconstruction decision-making, and condition deterioration and treatment improvement modeling.
2. Consider the effect of incomplete/missing data on the organization and processes, such as federal performance reporting and transportation asset management planning requirements, as well as impacts to other internal and external stakeholders and decision-making processes.
3. Analyze and derive recommendations on mitigation strategies that DOT could implement to minimize the impact of incomplete condition data.
Proposed research activities include:
1. Conduct a literature review to document:
○ DOT motivations and/or requirements for annual data collection.
○ Potential technical and organizational impacts or issues associated with missing an annual data collection.
○ Techniques available to mitigate the impacts of missing the collection.
○ DOTs known to currently (or in the recent past) complete pavement data collection on a 2 or more year data collection cycle.
2. Building from the literature review, survey State DOTs to capture:
○ DOT motivations and/or requirements for annual data collection
○ Potential technical and organizational impacts or issues associated with missing an annual data collection
○ Techniques available to mitigate the impacts of missing the collection.
○ DOTs that currently (or recently) collected pavement data on a 2 or more year data collection cycle
○ DOTs which have previously missed their established collection cycle
3. Conduct follow up interviews/surveys with DOTs that have longer collection cycles or which had previously missed an annual pavement data collection to understand perceived vs. actual impacts (both technical and organizational) and any mitigation strategies they employ.
4. Summarize literature review, survey results and follow up interviews to guide ongoing research activities
5. From a representative set of DOTs, collect available pavement condition and work history data, pavement deterioration and improvement benefit models
6. Utilize collected data to complete a statistical evaluation of the impact missing a year of data collection with respect to forecasted vs. actual performance results, and ability to identify priority investment areas based on previous year’s data collection, as well as other issues identified through the survey
7. Identify potential strategies to mitigate the impacts of incomplete condition data
8. Document survey results and evaluation outcomes
9. Produce a technical report summarizing impacts of, and potential mitigations for, missing an annual pavement collection cycle
Desired products include:
● Detailed listing of current requirements and/or motivations for annual pavement data collection
● Summary of perceived and actual impacts of missing an annual data collection against the listed motivations, supported with a statistical evaluation of actual DOT datasets where applicable
● A summary of potential mitigation strategies that can be employed to reduce the identified impacts
State DOTs perform data collection with a certain frequency based on the data condition type. Due to the unpredicted situation we are facing in 2020 many DOTs have missed their data collection schedule and this would directly affect the uncertainties and potential emerging risks in asset management. State DOTs need effective ways to address this incompletion in data to improve their ability in decision-making and ultimately continue their asset management plans. Studies have shown that monitoring intervals and data collection frequency have an effect on performance predictions. A part of the uncertainty in performance prediction is due to the frequency of distress data collection.
Data curing methods could significantly help state DOTs use their previous data to forecast the missing ones. Private industries can help state DOTs perform data curing and data mining strategies. COVID-19 has caused a pause in asset management procedures, however the gap in data collection can be filled with the improvement in machine-learning products. It is therefore increasingly important for state DOTs to benefit from the technology-based services private industries offer and decrease the risk of incomplete data.
The target audience for the research results is state DOT asset management and data quality management champions, whether self-designated or officially appointed. These individuals are likely already on board with the need for data curing and are aware of its benefits, but have been unable to convince executives or other senior decision-makers to sustainably implement data curing. There is a need for AASHTO and TRB committees to embrace the need for data curing. There is a possibility that TRB’s Pavement Management System committee will be interested in this subject, it is worth contacting them and explaining the objectives.
AASHTO TC3 Program
Better define the needs for education, training and workforce development related to transportation asset management and transportation performance management. Develop resources as needed for the following sub-areas:
Education—Writing curriculum for undergraduate and graduate courses
Training—For DOT and MPO staff in-depth career training, NHI, etc.
Workforce Development—e.g., TC3
Implementation of NCHRP 08-118: Risk Assessment Techniques for Transportation Asset Management
Implementation of NCHRP 08-129: Incorporating Resilience Concepts and Strategies in Transportation Planning
NCHRP 23-06 must be completed: NCHRP 23-06 [Active] A Guide to Computation and Use of System Level Valuation of Transportation Assets
This project could feed into the proposed NCHRP Risk and Resilience Program.
1. Identify six transportation agencies to use the guide.
2. Develop case studies on its application and use.
3. Further refine and develop the guide based upon its use in the six transportation agencies.
< a href="https://apps.trb.org/cmsfeed/TRBNetProjectDisplay.asp?ProjectID=4901">NCHRP 23-09 [Active] Scoping Study to Develop the Basis for a Highway Standard to Conduct an All-Hazards Risk and Resilience Analysis
The product of this research program will be a collection of tools and techniques that transportation agencies can for all-hazards risk and resilience analysis similar to what has been produced for the Highway Capacity Manual and the Highway Safety Manual.
Integrating Risk and Resilience into the Performance Management Decision-Making Process
Evaluate current federal PM3 measures
NCHRP 20-24(20), (37), (97), (127)
NCHRP 20-24(37): This project, Measuring Performance among State DOTs: Sharing Good Practices, put in place a foundation on which the first set of national performance measures were created. A similar program needs to established on which to further develop relevant national-level performance measures.
1. Evaluate current federal PM3 measures
2. Identify and address in detail specific challenges for the measure
3. Provide recommendations to improve existing measures and/or identify metrics that better reflect conditions.
1. Evaluate current federal PM2 measures, both pavement condition measures and bridge measures, for performance thresholds, and overall performance measure with respect to: Consistency, Usefulness, and Alignment.
2. Identify and address in detail specific challenges for each condition measure 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.) 3. Provide recommendations to improve existing measures and/or identify metrics that better reflect conditions 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.
State departments of transportation (DOT) and other transportation agencies face a range of challenges in determining how best to invest in their existing pavements, bridges, and other physical assets, and in projecting what the impact of those investments will be over time. Addressing these challenges requires considering both specific planned or potential investments at a project or asset level, as well as overall expenditures and conditions for systems of assets – that is, at a network level. Evaluating assets at both the project and network levels is consistent with best practice in Transportation Asset Management (TAM), and is required by recent Federal regulations in performance and asset management. For instance, 23 Code of Federal Regulations (CFR) Part 490 requires state DOTs to set network-level performance targets for future pavement and bridge conditions for the National Highway System (NHS) based on expected funding. Also, 23 CFR Part 515 requires state DOTs to develop TAM plans for their NHS pavements and bridges including financial plans and investment strategies, implying further project-level analysis.
As transportation agencies are using their existing pavement and bridge management systems, they are finding that no one management system supports the full range of network and project-level analyses required to meet the demands of TAM practice and Federal regulations. Thus, to support TAM and meet Federal requirements agencies typically rely on multiple systems and approaches with different data requirements, analytical approaches and underlying assumptions. A common approach is to use pavement and bridge management systems to predict network-level conditions, typically projecting conditions out 10 or more years in the future, while making near-term project level decisions in a more decentralized manner using mix of expert judgment and heuristic approaches. In concept the network-level analysis can be used to guide project-level decisions, and specific project plans can often be incorporated in a network level analysis. However, in practice the network and project-level analyses are often performed largely independently from one another incorporating different data, factors and constraints.
The approach of using multiple approaches for network and project level asset analyses has numerous pitfalls. These include, but are not limited to: generating unrealistic predictions of network level conditions; developing projects that do not reflect optimal asset lifecycle plans developed at a network level; waste of staff time through inefficient business processes or duplication of effort; and omission of critical assets from one or more analyses (e.g., for lack of data or a dedicated management system). Guidance is needed to assist agencies in making better use of existing systems to integrate network and project-level analysis, as well as to define a framework for future asset management tools that will enable integrated network and project-level analyses across multiple asset classes, potentially using multi-objective approaches.
The goal of this research is two-fold: to provide guidance on how transportation agencies can best use existing management systems and tools to integrate network and project-level analysis and provide a framework for an improve asset modeling approach that better integrates the project and network levels incorporating multiple asset types and consideration of multiple objectives. The research is intended to be of immediate value in helping transportation agencies better comply with Federal requirements to set performance targets and develop asset management plans. Also, it will help agencies to extend asset management approaches to additional systems and assets, besides the NHS pavement and bridge assets addressed through the Federal regulations. In addition, the research will help define improved approaches for asset management models for public agencies, researchers and system developers to use in developing the next generation of asset management systems.
Research is needed addressing risk analysis/vulnerability quantification and application to multiple transportation modes for purposes of scenario planning at MPO and DOT levels. There is significant variability across agencies with regards to how the agencies analyze risk and their practices for assessing vulnerability. Even basic elements such as methods that agencies use to collect data are not consistent across agencies, further complicating any potential analysis.
This research should:
• Identify pertinent data sources, data types, as well as relevant collection and analysis methods employed by transit agencies.
• Provide a synthesis of examples or State of the Practice applications for MPOs/DOTs.
• Outline communication strategies to the relevant decision-makers.
There are standard practices used internationally for incorporating asset valuation into an organization’s financial statements that have not been adopted in the US. These are important to asset management to support long-term financial planning, leading to improved financial sustainability. Improved practices in asset valuation will allow agencies to use financial valuation and acknowledge that sustainability is not only about maintaining financial capacity (cash) and infrastructure capital (condition).
The objectives of this research are to examine methods for evaluation of system assets. Thorough research should:
• Identify international practices and determine how they can be applied in the US
• Better marry engineering and accounting in financial planning
• Demonstrate benefits through a case study (may be fictional)
Enterprise-wide asset management is a multi-disciplinary, cross-functional, inter-departmental and partner-dependent undertaking that forms the basis of how an organization does business. How does an asset owner ensure that all of those involved in successful asset management are aligned, taking responsibility, and contributing to the effort?
The focus of this research is to support a scan tour or peer exchange addressing organizational alignment for TAM. This falls into three distinct but equally necessary categories: a review of previous knowledge, a inter-agency gathering to assess differing organizational models and policies to TAM, and finally a report or summary of the findings.
State departments of transportation (DOTs) and other transportation agencies are challenged to deliver greater transportation asset management (TAM) performance – even as available resources are increasingly constrained. Agencies recognize that established business processes, organizational structures, technical methodologies, tools, and systems must adapt to meet these challenges. Agencies must increasingly pursue tailored solutions that consider a variety of perspectives and factors – and work in a more collaborative fashion. At the same time, decision processes are more open and desired outcomes are more likely to be measured and reported. Taken together, these dynamics elevate the challenge of effectively implementing TAM for DOTs and other government transportation agencies. As a result, the state of the practice is uneven: TAM is adopted in some organizations but not others, and in some organizations to a greater degree than others.
Research is needed addressing the question: “What are the organizational/cultural factors that were in place before and/or during implementation that created a successful TAM program?” Develop a guidebook to convey lessons learned. Key point: must use an organizational development or similar consulting firm. Not the usual suspects!
The relationships between TAM and economic development, safety, mobility, etc. need to be better understood. This will help activities such and the connectivity between long range plans, transportation improvement programs, and transportation asset management plans. Research and evaluation of agency practice and results is required to consider how these agency activities and expenditures relate back to an agency’s goals and objectives. For example, how do system-wide goals for level of service and condition translate into individual project selection and asset management application? This research will focus on understanding the TAM relationships to broader transportation goals and how best to make the connections stronger from planning, programming, project delivery, to maintenance/operations.
This research will focus on understanding TAM’s relationship to other transportation goals such as economic development, safety, environmental sustainability, mobility, and livability. Two products are sought through this research: 1) Framework for understanding the relationships between TAM and broad transportation goals. 2) Guidance on how to ensure TAM connectivity to broad transportation goals throughout the transportation decision-making cycle.
As TAM tools and techniques advance, organizational capabilities in transportation agencies have to advance also to realize the benefits of asset management. Many organizational models and role types exist for TAM programs. People are an integral ingredient for realizing the positive outcomes that are possible with asset management. Transportation agencies today could use assistance in improving organizational capacity to adopt asset management benefits.
This research will focus on understanding successful organizational models for TAM program so that guidance can be provided on how to improve organizational capacities. Two products are sought through this research: 1) Understanding of current organizational models for TAM programs 2) Catalog of possible organizational models for TAM programs that transportation agencies could consider for improving TAM capabilities.
With the current financial state and shrinkage of resources, there is an urgent need to know what is the value and future cost of maintaining assets. Maintaining assets have an obvious value, but there is a cost associated with both choosing to maintain assets, as well as a cost associated with choosing not to do so. Attempting to determine the expected long-term costs of maintaining an asset, as well as the predicted value of having a well-maintained asset, is a considerable challenge for a transportation agency.
The objective for this research is to examine the costs and value associated with maintaining assets, and then to develop a usable model for forecasting the cost and value. Such a model must include, but not be limited to:
• A framework for quantitatively assessing the value of an asset that has been properly maintained.
• A tool for calculating the long-term costs of maintaining an asset, in line with industry standards for safety and reliability.
In addition to developing the model, the research should also establish guidance targeted at helping practitioners conduct forecasting analyses and communicate the results.
Well set up asset inventory is essential to reduce long-term costs in any agency. By tracking assets, lifecycle costs should be able to be reduced. An accurate asset inventory is a key element in meeting MAP-21 requirements. With the emergence of asset tagging and tracking technologies it is imperative to have a common standard in how these technologies should be developed and applied to support asset lifecycle management. Which of these technologies is the most efficient at reducing costs is still an open question.
The proposed research will:
• Evaluate various technologies for tagging and tracking assets and capturing asset history. Each proposed tracking technology should be evaluated for various factors, such as cost, ease of use, efficacy, and time required to implement.
• Create a standard for transportation asset tagging and tracking that can be used intermodally and across agencies.
• Develop a business case to demonstrate the lifecycle savings that can be achieved by transportation entities. This case study may be fictional if a suitable real-world example cannot be identified due to the new nature of the technologies.
Due to legislative mandates and advances in organizational practices, transportation planning agencies have engaged in intensive data collection activities. The resulting data has been used, to some extent, by these agencies to guide their resource allocation decisions for their infrastructure assets. However, there still remains vast amounts of underutilized data that, if leveraged appropriately, could be used by planning agencies to improve the cost-effectiveness of their infrastructure maintenance and preservation activities. As a result, it is important that planning agencies gain better insights regarding the types of data frequently available within infrastructure management systems that can be used to reduce the life-cycle costs of an agency’s assets.
The proposed research will:
Treatment selection is related to treatment timing. An asset that is identified to have a particular treatment but the treatment, but the treatment is delayed can be improperly treated if the treatment is not reevaluated. If a more dynamic method for selection could be applied at the right time, the end results could be greatly improved, but a concrete methodology to accomplish this is lacking.
The proposed research will first develop a methodology that will allow dynamic changes to treatment plans. Then, the research must test the methodology, as well as identify and quantify cost savings benefits of using the methodology or tool.
Existing standards have been developed by ISO and are being used by various groups. Now there is federal legislature with requirements for asset management plans. The goal of this research is to establish relationships between these existing standards and the legislature requirements.
Identify linkage between ISO standards and MAP-21 TAMP requirements. Identify gaps or inconsistencies and propose solutions. The proposed solutions may include guidelines for agencies, research needs, modification to the standards, or agency specific standards that address agency specific needs.
Agencies have a need to tell a better story. The utility of a well-thought out story, called a marketing plan, is to convert the non-believing decision makers and public. A well-conceived plan must translate the technical issues to something that resonates with public. For example, Ohio has marketing toolbox for continuous improvement with tools designed specifically for internal and external users. Although Asset Management is the right thing to do, the public still does not rally behind the cause. A possible solution is heavy branding and thorough communications plans.
The focus of this research can be divided into three main categories. Firstly, prior information must be collected and organized. This is accomplished through:
• Case studies and examples of best practice
• Creating a synthesis of state’s best practices
The next step is to build tools that allow for better asset management marketing, such as:
• Communication, sales, and/or a media science application to help craft a way to tell the story
• Creating a marketing plan that can be used to educate and train
• Training to Speak a language that all can understand
• Communicating the secondary benefits of TAM
Finally, follow-ups of the methods must be conducted to measure efficacy. This could include examining:
• How effective are the marketing and communication? Is the message being received?
• How has public perception changed?
Autonomous vehicles, colloquially referred to as self-driving cars, have a large potential to impact transportation networks in the near future. Semi-autonomous vehicles with various degrees of autonomy are already a reality. The industry is still a relatively nascent one, and therefore several large questions still exist. The expected capabilities and limitations of these vehicles are not yet established, nor is a timeline for implementation. The capacities and speed of implementation of autonomous vehicles are also greatly affected by the infrastructure on which they operate.
The objectives of this research are to quantify the expected abilities of autonomous vehicles, to establish an expected timeline of integration within the greater transportation networks, and to examine what infrastructure changes are most beneficial for autonomous vehicles.
The capacities of autonomous vehicles are not yet quantified. The research should:
• Determine what types of roads are suitable for such vehicles.
• Examine safety for both drivers/passengers, and other users of the roadways, such as pedestrians and cyclists.
• Explore limitations, such as fog or extreme conditions.
• Establish a timeline for adoption. Since the technology is expected to change rapidly, current capabilities will change.
The infrastructure requirements for autonomous vehicles are greatly dependent on the capabilities of the vehicles. Nevertheless, certain changes can be expected to improve the safety and usefulness of the vehicles, such as:
• Repainting roadways to help the vehicles operate.
• Installing RFID that could communicate with the vehicles directly.
• Determining what challenges would face a mixed-stream road of autonomous vehicles and vehicles under driver operation.
Transportation Asset Management (TAM) brings with it new fields and emerging technologies. These innovations require employees to have a different skill set then what was previously necessary. Co-ordination cross departments and silos is mandatory. Effective data management and effective use of systems and analytics is essential. With all of these new employee skills being critical to effective operations, transit agencies face the difficulty of recruiting, training, and maintaining a TAM staff.
The primary focus of this research is, at a most basic level, to help agencies strengthen their work force. This should be accomplished by researching areas where:
• Agencies lack a comprehensive list of necessary skills for a given position
• Agencies lack a comprehensive list of which positions are most critical to keep fully staffed. In an era of shrinking budgets, effectively prioritizing hiring decisions is crucial.
• There is a gap in knowledge regarding existing certifications.
Data-driven analytics are increasing critical to the success of any transportation agency. The recent NHS expansion impact on data collection, collaboration, and by extension, the entire decision making process. This leaves a fundamental question: How do we help agencies comply with FHWA requirements to manage across jurisdictions.
The research should focus of two primary areas of focus. The researchers must develop a guidebook for data integration across jurisdictional lines, as well as review the existing standards for civil data. This could include projects such as Civil Integrated Management (CIM) and the researchers must document the positive and negative ramifications of the various standards.
Emerging technologies hold the promise of transforming asset data collection for transportation asset management. Applications of these technologies include the use of drones for inspections, LiDAR field data collection, continuous monitoring of real-time sensor data, and more. Research is needed to address the adoption and practical application of these technologies and the rapid pace of technological advancement.
Emerging technologies hold the promise of transforming asset data collection for transportation asset management such as the use of drones for inspections, LiDAR field data collection, continuous monitoring of real-time sensor data, and more. While the technology has been transforming, MAP-21 and the Fast Act jump started at many agencies in attaining an inventory of infrastructure assets and transportation data. At the same time, accessibility and affordability to collect high volumes of asset inventory data, such as LiDAR point cloud data, present the problem of how agencies can visualize and manage such large amounts of data and integrate the many layers for each transportation asset management plan. Now that the need for such data is federally recognized, further research is needed to understand what the latest technologies for asset analysis can offer an agency as well as how frequently that information needs to be generated.
Cell phones / Collector Apps
Vehicle, AAV, or drone
More specific to TAM and data collection than synthesis 508
Includes an aspect of data management to prepare data for use in appropriate TAM systems.
Synthesis 508 - Data Governance
Research is needed in the following areas:
● Address the adoption and practical application of these technologies and the rapid pace of technological advancement.
● What level of extraction detail and frequency interval is needed to support TAM at both the state and local levels and how can the condition assessment be applied to the performance measures of both pavement and non-pavement assets?
● Further investigate what tools are capable of visualizing asset extraction layers, as well as presenting such data to all stakeholders in powerful GIS formats with standardized TAM graphics for universal interpretation.
AI is coming – are we ready? With the MAP-21/FAST Act legislation, and the renewed emphasis on Transportation Asset Management Plans (TAMPs), projections made by management systems will come under increasing scrutiny as agency executive leadership is asked to make large scale funding decisions based on these projections. This scrutiny as well as the inherent complications in predictive modeling of asset deterioration, presents an opportunity for the use of Artificial Intelligence (AI) in this type of analysis.
AI is becoming ubiquitous in the realm of automation and pattern recognition and shows promise in improving predictive modeling for infrastructure managed by highway agencies. Because data collected over time is especially valuable for deterioration modeling, it is very important for agencies to start collecting the right data, and putting in place the right quality control, as early as possible so that this data is ready for immediate use as more research into AI techniques for predictive modeling is conducted.
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.
A number of approaches are commonly used to manage risk, including conducting visual inspections of existing infrastructure, using design standards with conservative safety factors for new infrastructure, and applying best practices for minimizing risks of project cost and schedule overruns. Research is needed to determine how to build on existing practices to better assess the risks to transportation assets, better quantify consequences of different risks, and better prioritize investments explicitly acknowledging uncertainty in future events.
Risk (R) is generally quantified with the equation above. It is essentially a value for the expected outcome returns of a decision weighted by the probability (p) of each consequence (C) of event i. How do we calculate R if neither p nor C is certain? Do current methods address this effectively?
Investment decisions are widely made using discounted cash flows (DCF). It is assumed, that given a certain decision made in Year 0, Costs and Benefits can be assumed for a number of years to come, i.e. C is known and p is assumed 1 for all i. If the project is considered risky, the discount rate is increased accordingly. However, defining the future in- and outflow of cash with such deterministic certainty is unrealistic. Not only is the consequence (C) uncertain, but also their occurrence. This is because infrastructure is often affected by stochastically occurring events.
We can ignore the uncertainty by using expected values. Imposing an assumed expected value will nevertheless almost certainly lead to arriving at a wrong risk estimation (see figure X). This is called the “flaw of averages” (Savage, 2012). The error due to the “flaw of averages” exponentiates when systems are non-linear because outputs using expected inputs do not equal expected outputs. Ultimately, it can be said that ignoring the uncertainty and the consequent existence of a distribution instead of a deterministic expected value, is a fallacy.
Another approach to compensate for increased risk is overdesigning infrastructure. This reduces the probability of failure to negligent values, but may lead to infrastructure being overly expensive or redundant. This also ignores the fact that infrastructure owners are not passive, but actively observe their condition and relevant external factors and trends that affect the condition level of the infrastructure. Based on this, the fundamental assumptions of DCF do not seem appropriate.
The ultimate objective is to provide the decision-maker with tools that add value to the decision-making process and improve the robustness of the infrastructure network as a whole. In that sense, novel approaches for the evaluation of risk will be sought to capture the stochastic nature of interdependent infrastructure. A graph theory approach to evaluate criticality of network node failure as shown by Buldyrev and colleagues (2010) may prove interesting for the evaluation of consequences, and thus the real option value for the infrastructure, simulated by network programming methods.
Continue to deliver TAM peer exchanges at the regional and national levels.
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.
Document and provide examples of condition assessments for all types of assets.
Create case studies addressing noteworthy applications of big data analytics to TAM.
Research effective corridor planning strategies that promote sustainable capital asset improvements that impact asset class performance and other performance areas.
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
• Boadi, Richard S; Amekudzi, Adjo A. Risk-Based Corridor Asset Management: Applying Multiattribute Utility Theory to Manage Multiple Assets. Transportation Research Record: Journal of the Transportation Research Board, Issue 2354, 2013, pp 99–106 https://trid.trb.org/view/1241970
• Anderson, Scott A; Rivers, Benjamin S. Corridor Management: A Means to Elevate Understanding of Geotechnical Impacts on System Performance. Transportation Research Record: Journal of the Transportation Research Board, Issue 2349, 2013, pp 9-15 https://trid.trb.org/view/1241789
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.
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.
• 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.
• Synthesis 508 Data Management and Governance Practices
• NCHRP Report 920 Management and Use of Data for Transportation Performance Management: Guide for Practitioners
• NCHRP Report 814 Data to Support Transportation Agency Business Needs
• NCHRP 20-44 (12) Building Capacity for Self-Assessment of Data Effectiveness for Agency Business Needs (new project)
• NCHRP 08-115 Guidebook for Data and Information Systems for Transportation Asset Management
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.
• 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.
• NCHRP Synthesis 330, Public Benefits of Highway System Preservation and Maintenance
• NCHRP Report 742, Communicating the Value of Preservation: A Playbook
• NCHRP Report 866, Return on Investment in Transportation Asset Management Systems and Practices
• TCRP Report 206, Guidance for Calculating the Return on Investment in Transit State of Good Repair
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.
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.
Risk management has been studied quite extensively in the transportation sector. Risk management encompasses four major steps: Risk identification, risk assessment, risk mitigation, and continuous updating of results. Risk assessment focuses on determining the magnitude of risk, which is directly proportional to the likelihood and consequences of an event to occur. Risk assessment has been a major area of study in pavement and bridge management efforts. In recent decades, the focus has shifted from assessing risk in single networks towards more holistic risk assessment approaches.
Between 2012 and 2013, Federal Highway Administration (FHWA) published a five-part report series on Risk Based Asset Management. These reports focus on: (1) Overview of risk management, (2) Managing risk at different levels, (3) Strategic risk management (risks to agency objectives), (4) Managing risk to critical assets, and (5) Managing external threats such as climate change and extreme weather risks. These reports played an important role in introducing risk management concepts into asset management efforts. In 2016, American Association of State Highway and Transportation Officials (AASHTO) published the Guide for Enterprise Risk Management. In this Guide, risk management is defined as “the systematic application of policies, procedures, and practices to the identification and management of uncertainty or variability on achievement of agency objectives.” In addition, the Guide introduces four levels at which risks need to be managed: Strategic, Program, Project, and Activity levels. Enterprise Risk Management is defined as management of risks at all levels. Other research projects (recently completed, active, or pending) in this area include:
• NCHRP 08-113: Integrating Effective Transportation Performance, Risk, and Asset Management Practices
• NCHRP 08-118: Risk Assessment Techniques for Transportation Asset Management
• NCHRP 20-44(02): Implementation of the AASHTO Guide for Enterprise Risk Management
• NCHRP 20-123(04): Development of a Risk Management Strategic Plan and a Research Roadmap
• NCHRP 08-129: Incorporating Resilience Concepts and Strategies in Transportation Planning
• NCHRP 23-09: Scoping Study to Develop the Basis for a Highway Standard to Conduct an All-Hazards Risk and Resilience Analysis.
Managing risk at program (or network) and project levels is particularly important to achieve desired performance levels and to improve resilience of a transportation system. While existing research efforts in this area are highly significant, there is a need for developing more practical and repeatable risk assessment calculation methods for project and network level risks. This proposed study will build on these recent efforts, particularly NCHRP 23-09, and serve as the next phase in risk assessment and management.
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.
While existing reporting mechanisms allow agencies to see the parts of their network that are in good and poor condition, risks associated with different threats and the impact of failure are not reported as an explicit performance measure. Competing design documents, financial implications, legal concerns, maintenance practices, focus on building new capacity rather than managing existing infrastructure, and other factors that affect decision making procedures may counter-act risk-based TAM practices. Issues related to social justice and equity, and consequences of failures make risk-based TAM even more important. Creating harmony in the TAM decision making space in consideration of risk and resilience represents an urgent need. A practical, quantitative, and repeatable risk assessment process could play a major role in addressing this need.
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.
Because DOTs are only two years into implementing the pavement performance measures and metrics, the urgency is great to make sure the measures in use are as meaningful, consistent and implementable as possible. Currently, the performance measures have not achieved widespread use as the primary performance criteria for decision-making, leading to two sets of metrics being used by many agencies. In addition, DOTs must make performance predictions and justifications based on the federal performance measures. Making any changes to the measures as soon as possible will allow DOTs to build up datasets on which to base predictions of future performance.
Potential benefits to improving the federal pavement performance measures and metrics include:
• Metrics that better define pavement failure mechanisms and therefore condition
• Metrics that result in more consistent results across pavement types and pavement widths
• Broader adoption of the measures by DOTs as part of decision-making criteria
• Less confusion among the public, senior executive staff, and legislative bodies, along with non-DOT owners of NHS assets by having one set of metrics instead of two (federal and state-specific)
• 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.
• To be completed at 9/9 research workshop