Background Information

 Emerging technologies, such as the use of drones for inspections, LiDAR field data collection, and continuous monitoring of real-time sensor data (among others), hold the promise of transforming asset data collection for transportation asset management. As this technology has been evolving and improving, federal regulation, specifically, MAP-21 and the FAST Act, has pushed many agencies to collect and utilize a detailed inventory of infrastructure assets and transportation data. With the collection of high-volume asset inventory and condition data, such as LiDAR point cloud data, the accessibility and affordability of data collection has become a clear issue for agencies, particularly as they aim to manage and visualize collected data for both strategic and operational transportation asset management planning purposes. Therefore, research and guidance on the benefits and applications of these emerging technologies as well as how frequently that inventory and condition data need to be collected or assessed is necessary.
The focus of this research would be on the following:
• Address the adoption and practical application of these emerging collection technologies and the rapid pace of technological advancement.
• Provide guidance on the level of detail and frequency interval necessary for data collection to support TAM at both the state and local levels.
• Determine how condition assessment can be applied to the performance measures of both pavement and non-pavement assets.
• Further investigate and recommend tools capable of visualizing asset extraction layers, as well as presenting data to stakeholders in powerful GIS formats with standardized TAM graphics for universal interpretation.
• The research should consider any refinements that would need to occur in network level asset management data collection to make the data useful for compliance (i.e. ADA), safety (i.e. bridge clearances) or engineering (design or construction) purposes.

Literature Search Summary

• PROJECT: Best Practices on Collecting Asset Information from the Construction Stage, South Carolina Department of Transportation, 2021, Proposed 2021-10-01
• PROJECT: Automated Guardrail Inventory and Condition Evaluation, Massachusetts Department of Transportation, 2021, Active 2021-01-18
• Highway Asset and Pavement Condition Management using Mobile Photogrammetry, Transportation Research Record: Journal of the Transportation Research Board, 2021
• Automated Real-Time Roadway Asset Inventory using Artificial Intelligence, Transportation Research Record: Journal of the Transportation Research Board, Volume 2674, Issue 11, 2020, pp 220-234, 2020-11
• Computer Vision for Rapid Updating of the Highway Asset Inventory, Transportation Research Record: Journal of the Transportation Research Board, Volume 2674, Issue 9, 2020, pp 245-255, 2020-09
• GIS Tools and Apps—Integration with Asset Management, 2020, 155p, 2020-02
• PROJECT: A Method for Pavement Marking Inventory and Retroreflectivity Condition Assessment Using Mobile LiDAR, Massachusetts Department of Transportation, $200,000, 2019, Active, 2019-10-21
• SCDOT Asset Data Collection Assessment, 2019, 99, 2019-08
• PROJECT: GIS Tools and Applications: Integration with Asset Management, Minnesota Department of Transportation, $59,021.12, 2019, Completed, 2019-04-19
• Novel Cloud and Mobile Technology for Road Asset Management in Saint Lucia, 26th World Road Congress, 2019, 9, 2019
• Implementation of Road Asset Management System in Saint Lucia, 26th World Road Congress, 2019, 16, 2019
• Innovative Approaches to Asset Management, 2019, 110, 2019
• Machine Learning Powered Roadside Asset Extraction using LiDAR, TAC 2018: Innovation and Technology: Evolving Transportation - 2018 Conference and Exhibition of the Transportation Association of Canada, 2018
• Life-Cycle Approach to Collecting, Managing, and Sharing Transportation Infrastructure Asset Data, Journal of Construction Engineering and Management, Volume 143, Issue 6, 2017-06
• Highway Asset Inventory Data Collection Using Airborne LiDAR, Transportation Research Board 96th Annual Meeting, 2017, 15
• Evaluation of High-Speed Mobile Technologies for Sign Inventory and Maintenance, Transportation Research Board 96th Annual Meeting, 2017, 13, 2017
• Implementation of Aerial LiDAR Technology to Update Highway Feature Inventory, 2016, 133, 2016-12
• Guide for Efficient Geospatial Data Acquisition using LiDAR Surveying Technology, 2016, 12, 2016
• LEVERAGING CONSTRUCTION INSPECTION AND DOCUMENTATION FOR ASSET INVENTORY AND LIFE CYCLE ASSET MANAGEMENT Transportation Research Board 95th Annual Meeting, 2016, 20, 2016
• Handbook For Including Ancillary Assets in Transportation Asset Management Programs, Federal Highway Administration, 2018

Objectives

Working backward from the key decisions that need to be made across stakeholder groups over an asset’s lifecycle, this project seeks to identify current practices and recommend ongoing improvements in relation to collecting, storing, sharing, and maintaining asset inventory and condition data (“data management”). With a focus on implementation, the project will build on existing research by identifying the pros and cons of different data management methods and technologies, so that decision makers across departments can collaborate more effectively when planning and investing in data management approaches. The practice of data management is evolving at a rapid pace, given the proliferation of new technologies that are being used increasingly alongside traditional approaches. In parallel, agencies are recognizing the multi-stakeholder nature of asset management, as departments such as compliance, safety, engineering, operations and environmental begin to see the benefits of access to reliable, accurate asset information. This project will answer key data management questions such as: What data should be collected to address all stakeholder needs? How, when, and how often? Using which technologies and platforms? At what cost? And why?
It will also provide guidance to agencies on the most appropriate approaches to collecting, storing, sharing and maintaining asset data, based on the needs of the various stakeholders involved in data-based decision-making.

Keywords/Terms

Link to 2021-2026 AASHTO Strategic Plan

Urgency and Potential Benefits

Inventory and condition data collection and data management are continuously changing in response to changing demands of state and local agencies. However, despite these changing demands, inventory data is constantly being used by multiple stakeholders to make decisions (planning, operations, safety, contractors). While the inventory data may not necessarily be accurate or timely due to these agency constraints or because the agency’s collection processes lack maturity (i.e. ancillary assets), this data is still being used to make decisions at all levels within an agency, yet there is little consensus on how to manage data related to those assets.
The benefits of this research are that it will provide a complete view of inventory and condition issues across asset classes; support agencies with lessons learned from others (from data collection to post-processing/extraction and related decision making) and enable collaboration on new approaches, particularly for secondary asset data management; support implementation of TAMPs by helping to ensure data is reliable and accurate; support preparation for emerging technologies such as CAVES, which will be dependent on secondary assets, such as striping, roadside units (RSUs) and signals.

Implementation Considerations

Methods to incorporate products into practice:
- Web-based training for agency staff
- Case studies from peer agencies
- Assessment of existing technologies including functionalities, pros/cons, and costs
Intended audience:
- Decision makers at all organizational levels and across departments/disciplines
- Contractor and consultant community

Author(s)

Others Supporting Problem Statement

Potential Panel Members

Person Submitting Statement

Notes