Use of Weigh-in-Motion Data for Pavement, Bridge, Weight Enforcement, and Freight Logistics Applications (2020)

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36 The objective of this synthesis is to document how transportation agencies use WIM data as a tool to support decision making for asset design and management, weight enforcement, and freight logistics. This chapter briefly summarizes the project findings developed from the literature review, the agency survey, and the follow-up case examples. Additionally, it discusses impediments to using WIM data as a tool, the knowledge gaps identified, and the research areas that have potential to fill those gaps. Summary from Literature Review, Survey, and Case Examples The literature review documents WIM uses for pavement design, bridge design, and asset management and load rating; commercial vehicle weight enforcement support; and freight planning and logistics. The DOT survey (with a 90% response from U.S. state DOTs) provides a good snapshot of the state of the practice for WIM in the United States and Canada. Most DOTs are collecting WIM data with a wide variety of sensor types and use them in a variety of applications. Many agencies use WIM data to aid in pavement design, although most are not currently using a Pavement ME Design application. WIM for bridge and asset management purposes is used much less often. The case examples of five selected agencies provide a broader picture of the WIM use than the survey could. Most DOTs have selected sensor types based on data quality and maintenance requirements. Road closure limitations drive some decisions as well. Due to dwindling funding, personnel, and expertise, some DOTs are moving to contract maintenance, leasing equipment, or a pay-for-data model. A few innovative uses of WIM data emerged, primarily in the research or exploratory phase that support calibration and freight planning. Impediments to Using WIM Transportation agencies may face different types of impediments to using WIM systems, stemming from technology, funding, or organizational structure, as outlined here: • WIM systems are costly. Some agencies can justify the installation costs, but find the ongoing costs of maintenance and calibration harder to justify to budget writers. Some agencies have enlisted other users for funding, such as internal groups focused on traffic data, intelligent transportation, transportation planning, and freight planning, or looked to external sources, such as law enforcement. Some agencies have also found that much of the information a WIM C H A P T E R 5 Conclusions and Further Research

Conclusions and Further Research 37 system can provide can be gained with ATRs for much less cost. However, if weight informa- tion is needed, only a WIM system will provide this information. • Agencies need an appropriately sized WIM network, with enough stations to provide effective coverage, to obtain useful data. Without an adequate network, users see little use in the data. Maintenance also is needed to replace sensors and calibrate systems. Without maintenance, users lose faith in the accuracy of the data and then do not use it. Lack of available funding, both for initial installation and ongoing maintenance of stations, is seen as a constraint to acquiring useful data. • Many times, the DOT staff collecting the data are unsure of how others in the agency use it—that is, whether for pavement, bridge design, etc. Conversely, the DOT staff that could use the data do not know the extent and accuracy of the data they can access. One DOT indi- cated that where and when the DOT can supply good WIM data to their internal customers, those customers want more. Knowledge Gaps and Research Areas to Address Those Gaps In the future, DOTs may need to focus on acquiring additional WIM data, reducing network costs, and acquiring other types of data than are currently being collected. Additionally, other ways to use the data may develop. Below are some knowledge gaps that merit future study, discussion, and research. WIM calibration is a significant issue to ensure the acquisition of accurate data and is a costly and time-consuming activity. Most DOTs have calibration processes, but many are looking for ways to optimize calibration. More research is needed to help DOTs optimize calibration procedures and automate the process to include the concepts of pairing WIM and static scale or on-board weight sensor information (TRB, 2017). A common concern of DOTs is that their WIM network cannot assess the transportation network adequately. Some DOTs are working to expand their network and others are redevelop- ing networks. Research is needed to help DOTs determine the optimal number and location of WIM stations in their state to better represent the infrastructure use. DOT staff collecting WIM data are sometimes unclear on the use of the data by others in the agency. Additionally, the DOT staff that could use the data do not know the extent and accuracy of the data available to them. This disconnect necessitates a means to help various areas in a DOT understand the data and how it could be useful to them. One approach that shows potential is visualization techniques, which can help users connect data across an agency. More research is needed to show the data to various internal divisions within transportation agencies and how the data fit together to inform better decisions. More research is needed to connect data (similar to the work done by the Albany Visualization and Informatics Lab, University at Albany–SUNY). Transportation agencies are beginning to use WIM to aid in freight and corridor planning. Many DOTs are not satisfied that their network can give them the data required. Research is needed to see how additional databases can be acquired and used in this effort, as well as the application of data mining and AI analysis of current data from WIM and other data collection sensors in a DOT’s network. Some past research has investigated a pay-by-weight-distance replacement for gas taxes using WIM. This approach may become more critical as vehicle engines increasingly transition to non-taxed fuel sources, or to ensure that the trucking industry pays a use fee according to the infrastructure consumption they produce. More research is needed on this and other fee struc- tures for the future.