Development of a Regression Model to Predict Preliminary Engineering Costs

Preliminary engineering (PE) for a highway project encompasses two efforts: planning to minimize the physical, social, and human environmental impacts of projects and engineering design to deliver the best solution. PE efforts begin years in advance of the project’s actual construction operations, often five years or more. An efficient and accurate method to estimate PE costs would benefit transportation departments by facilitating funding allocation projections. Lacking an effective tool to estimate PE cost based on project characteristics, departments of transportation typically estimate PE costs as a fixed percentage of estimated construction costs disregarding other project-specific parameters. By analyzing 505 North Carolina Department of Transportation (NCDOT) bridge projects awarded for construction from 1999 through 2008, a multiple linear regression model was developed to link variation in PE costs to a set of distinctive project data. Published bid summaries, bridge inventory and assessment reports, NCDOT’s project management system, and published environmental reports were used as sources of project data. The model explained approximately 60 percent of the PE cost variation between projects. Results indicate that right-of-way costs, regional location, and scope delineators are among the project-specific parameters that most influence PE costs of bridge projects. By considering numerous parameters (expressed as independent variables) a more accurate prediction for future projects’ PE costs can be developed.