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Journal Article

Citation

France-Mensah J, Kothari C, O'Brien WJ, Khwaja N. Data Brief 2019; 25: e104367.

Affiliation

Center for Transportation Research, The University of Texas at Austin, 1616 Guadalupe, Suite 4.202, Austin, TX, 78701, USA.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.dib.2019.104367

PMID

31489352

PMCID

PMC6717169

Abstract

State Highway Agencies (SHAs) have different functional groups that work towards improving the functional and physical performance of highway assets. These functional groups often propose multiple inter-related highway projects on the same network. However, the respective information systems of such functional groups lack interoperability capabilities between them. This data article is related to an earlier study by France-Mensah et al. (France-Mensah et al., 2017) that explored the integrated visualization of highway projects proposed by different functional groups working in the same highway agency. This dataset provides a spatially integrated set of maintenance and capital planning projects which is rarely available due to organizational silos which often exist in highway agencies. The data includes approximately 700 highway projects with over 16 attributes that includes spatial, temporal, cost, and description attributes. The highway projects are located in the Fort Worth District of the Texas Department of Transportation (TxDOT) which is responsible for a large network (approximately 9000 lane miles) of highway assets. The agency currently oversees around $4 billion in construction projects and spends around $120 million annually for asset preservation. An analysis of the fund allocations categorized by different project types for pavement and bridge assets is presented. The data presented can be used to compare competing approaches or policies for cross-asset allocation, spatial-temporal projects coordination, and safety planning in the infrastructure management domain.


Language: en

Keywords

Cost allocation; Highway projects; Maintenance and rehabilitation (M&R); Visualization

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