Estimating cost per lane mile for routine highway operations and maintenance
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2011-01-01
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Edition:Final Report; 12/14/06-3/31/2010
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Abstract:The disparity between maintenance budgets and maintenance requirements causes agencies to make difficult choices
about maintenance priorities. There is a growing need to effectively link maintenance costs and condition to provide clear
evidence of impacts due to budget tradeoffs decisions. The focus of this research was to develop mathematical relationships
between expenditures for highway maintenance and the resulting maintenance condition by analyzing historic cost and
condition data. The research involved analyzing maintenance condition and cost data over three years, 2004, 2005, and 2006
from the state transportation agencies in Michigan, Ohio, and Wisconsin for highway components including pavement,
shoulders, roadside vegetation, drainage, signs, and pavement markings. The maintenance management systems at the states
use different categorization schemes for their maintenance activity costs and different rating systems for maintenance
condition, thus direct comparison between states was not possible.
The primary result of this research is a set of probabilistic distribution functions for annual maintenance costs for a
wide range of maintenance activities. Confidence intervals can be constructed around the average using the chosen level of
confidence (i.e., 95%). The functions are useful for sensitivity and simulation analyses.
The researchers hypothesized that data would reveal relationships between cost and condition. A regression tree
analysis approached was used to search for relevant model equations. However, the statistical analysis of the data revealed
weak evidence of these relationships. This finding is common for all three of the states that were investigated. There are at
least two clear limitations of the data. First, to see trends overtime, three years of data may not be enough. Furthermore,
even with budget cuts, noticeable deterioration in condition, deficiencies, or maintenance backlog may take longer than three
years. Second, the available cost and condition data are aggregated over many highway miles. Maintenance management and
cost records generally do not include precise highway locations where maintenance was performance, the specific activities
that were performed, nor the precise cost and timing of those activities. Consequently the trends and relationships between
cost and condition are “washed out” by the lack of precision.
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