Incorporating Resilience Considerations in Transportation Asset Management Planning and Project Selection Process
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2026-09-01
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Subject/TRT Terms:
- Transportation system management
- Asset management
- Infrastructure
- Material resilience
- Risk assessment
- Climate change
- Weather conditions
- Bridges
- Pavements
- Project management
- Pilot studies
- Geographic information systems
- Transportation asset management
- Infrastructure resilience
- Vulnerability assessment
- Extreme weather
- Project prioritization
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Edition:September 2024-August 2026
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Description:This research develops and demonstrates a resilience-based transportation asset management (TAM) framework for the Texas Department of Transportation (TxDOT) to incorporate resilience into asset assessment and project screening. The study (i) reviewed current TAM and resilience practices, (ii) assessed climate-related vulnerability for bridges and bridge-class culverts, roadways, and selected retaining walls, (iii) developed asset-specific resilience measures that integrate hazard vulnerability, asset condition, functionality, and recovery-related factors, and (iv) incorporated asset-level resilience into a GIS-based project-prioritization framework. The project selection method links candidate projects to nearby transportation assets, aggregates multi-hazard resilience needs, and combines resilience need with project criticality and expected effectiveness to support priority screening. A software tool was developed to automate resilience estimation, mapping, sensitivity analysis, and risk-resilience ranking comparisons. The pilot studies evaluated selected Wichita Falls roadway segments under extreme cold and extreme heat and Houston District bridges under inland flooding. In the Wichita Falls pilot, existing pavement condition and functional performance had the greatest influence on roadway resilience, and extreme heat produced more priority changes than extreme cold. In the Houston pilot, inland-flood vulnerability had the greatest influence on bridge resilience, while bridge component condition also affected results. Both pilots identified assets whose priorities increased when resilience was considered. The results indicate that resilience-based TAM can supplement conventional risk-based screening by identifying assets with weaker capacity to maintain or recover functionality after disruption. The framework and software are intended for planning-level screening to support maintenance, rehabilitation, adaptation, and further engineering review. Additional asset, hazard, hydraulic, cost, treatment history, and recoverability data would improve future district- and statewide applications.
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Main Document Checksum:urn:sha-512:20f08ce337a3644684b630d6c3c33a69dd0bb425f386a372cfb310dcec51acba5680d3cbded083681be85a9709d771a41b22f7794e60f92a82d5035f4f90bcfc