Unit price contracting is a standard contracting method for transportation projects. In such contracts, State Department of Transportation (DOT) estimators prepare an Engineer’s estimate of construction cost, which is used to compare the bids received and select the winning bid. This Engineer’s estimate is mostly dependent on historical bid data available from projects completed by the DOT in the past and experience of an estimator. The estimators adjust the unit prices of construction cost items to reflect project characteristics such as size, quantity of material, location etc. The historical data available to estimators contain unit prices of major construction cost items for some geographic locations where projects have been recently completed. However, the location of an upcoming project is highly likely to be different from any locations of recently completed projects. Hence, the estimator must use unit price data of different project locations to estimate unit prices for an upcoming project at a new location. The reliability of such estimate is questionable since there is no clearly defined procedure or methodology or technique that the estimators may use to adjust unit price for new locations. Geospatial interpolation is a promising method for quantifying the unit price for new locations from known values at various locations. The platform of geographic information systems (GIS) has tools for powerful spatial interpolation using techniques like inverse distance weighting (IDW), kriging, spline, natural neighbor, etc. In this study, the unit prices of five major highway construction pay items from the locational bid data obtained from Iowa Department of Transportation are visualized in GIS environment and spatially interpolated across the geographical map of Iowa using IDW. The difference in estimated and interpolated values of input points gives the error in interpolation and the average error is used to compare the interpolation techniques. Various factors are employed in the techniques to improve the resulting interpolation surface. Lower average error signifies the interpolation surface is better for that particular cost item.

The geo-statistical interpolation methods have an interactive layer, which can be used to obtain a unit price at any location by just clicking on that location. Other than acting as a tool to quantify unit prices GIS platform is used to identify best parameters for each item, which improve the unit price interpolation.

This study is an effort to make the unit price estimation process more visual, quantified, reliable, and also to facilitate effective use of data from the past. Validation is performed by conducting interviews with contractors that have performed paving works in Iowa on projects of Iowa DOT.