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Infrastructure Investment and Transportation Asset Management: The Use of Spatial Systems in Managing Maintenance

  • Last Updated: January 16, 2014
  • Greg Arbour
  • 2 min read

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It is clear that transportation infrastructure will be one of the biggest investments over the next decade by governments around the world. However, one of the largest expenditures that governments need to track is not necessarily the actual transportation projects themselves, but the billions of dollars spent on managing thousands of transportation assets. Currently, US federal and state transportation agencies are using geographic information systems (GIS) in combination with transportation asset management software to manage the scheduled maintenance of these assets. GIS is a computer-based mapping system that allows data to be displayed on maps and analyzed based on spatial factors. GIS software packages can be used to view base maps of geographic sections (e.g. cities, counties, states, countries) with “layers” of attribute data (such as characteristics about those sections) over top [1]. GIS complements traditional transportation asset management software by allowing agencies to visualize assets and asset data using maps and geospatial analysis [2]. Fully integrated transportation asset management platform systems allow transportation agencies to evaluate how investment decisions today will affect the condition of physical infrastructure in the future through a combination of data, software tools, cloud computing, mobile applications, processes, and analysts.


As agencies increasingly incorporate these more advanced tools, the ability to expand the advanced analytics in transportation asset management and maintenance software to include identification of patterns and relationship, construction and interaction with models, and full communication of findings between different agencies and departments has become the new norm. For example, using a geographic and spatial context to examine the differences between time of day/week/month/year can have great relevance when evaluating transportation infrastructure usage, optimization and planning [4]. Agencies also utilize spatial optimization to generate and compare project alternatives (for example determining the shortest distance or minimum elevation change to reduce costs of a new roadway project [5]). With the use of more advanced maintenance systems, the result of this analysis process is a series of decision tree outcomes (scenarios) which then need to be summarized and presented for final analysis and decision-making by departments and agencies.

Governments can add richness to the asset inventory data by integrating with spatial components of those physical assets through GIS to view maintenance data on a map either in print or on screen. The following are some of the current advantages of using up-to-date maintenance and asset management software for government agencies (particularly US state transportation agencies):

  • Asset inventory data. New cloud computing and asset management systems provide visual cues that an asset or a group of assets is located in a geographic expanse;
  • Current asset attributes. Maintenance software allows agencies to track asset attributes such as the age, model, or condition of the assets;
  • Future asset attributes. Embedded advanced analytics and algorithms allow asset management and maintenance software to evaluate projections of what the condition or form of an asset will be at a date in the future;
  • Asset optimization and cross-asset optimization [6]. GIS in combination with transportation asset management and maintenance software is used to strategize and optimize individual asset life cycles as well as to better coordinate the timing and scheduling of cross-asset activities. For example, some agencies are recognizing the ability of GIS to look at strategic scheduling of maintenance across asset classes to avoid utility repairs on newly resurfaced roadways and other costly non-coordinated maintenance activities. The ultimate goal is to find a solution that considers all asset classes simultaneously, considers existing conditions, predicts future conditions, and allows evaluation of different budget scenarios and resource constraints. An example of this is when a critical maintenance project is not implemented due to budget constraints while a less critical project, funded by a different budget based on asset category, goes forward. Within their respective budget realms, the prioritization may have been optimal in a narrow, short-term sense, but overall, the maintenance program is not allocated efficiently.


[2] FHWA, “Asset Management Overview.” Notes from the Director.




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