The successful implementation of transportation asset management (TAM) by local governments facilitates the optimization of limited resources. In fact, the use of a data-driven TAM program can help to identify and prioritize needs, identify and dedicate resources for the preservation of infrastructure, and provide policy decision makers with the data to support good decisions.
Recently, researchers Henry Brown and Carlos Sun from the University of Missouri-Columbia’s Transportation Infrastructure Center examined the use of TAM systems at the city level. With the cooperation of the City of Grandview, Missouri, a TAM program was implemented there.
The implementation process included an examination of current TAM practices, review of TAM software systems, deployment of a TAM system, analysis of existing pavement and service request data, inventory of existing pavement condition, formulation of a pavement preservation plan, and development of a framework for ensuring that the implemented TAM was sustainable. Existing pavement conditions were inventoried using the PASER system, which involves rating pavements visually on a scale of 1 to 10.
Pavement preservation plans were developed for both the near-term (2016 through 2020) and long-term (2021 through 2040). The near-term analysis included the evaluation of eight scenarios to compare the average PASER values. A decision tree methodology was developed and utilized to select specific pavement treatments for the next five years based on a “mix of fixes” approach. The long-term analysis assessed the possible impacts of two discount rates and a vote in 2021 to increase the sales tax to fund transportation projects. Additional recommendations for sustaining the TAM system were provided.
The flexible framework developed in this research can be used by other communities to help local governments maximize limited resources.
The research was funded by the City of Grandview, Missouri, and the Midwest Transportation Center (MTC), which sponsors a competitive research program to fund projects focused on State of Good Repair in infrastructure with attention to safety and Data Driven Performance Measures for Enhanced Infrastructure Condition.
Read the full report here.
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