Independent Cost Estimates for Design and Construction of Transit Facilities in Rural and Small Urban Areas

Abstract

Estimating design and construction costs in a consistent, reliable, and accurate way is critical for an organization since the information generated is the basis for projecting program funds, prioritizing projects by financial analysis, determining required funds, and providing a baseline for project control. This research focused on cost estimating methods and database development for design and construction of rural and small urban area transit facilities, which are usually small, numerous, and geographically dispersed. The objectives of this study were to determine the distinct characteristics of rural and small urban area transit facilities, collect actual historical cost data, and develop a cost estimating database and prototype tool to assist agencies with preparing conceptual estimates. This research included a literature review, telephone interviews, and an online survey. A cost estimating database was constructed based on historical cost data collected through the survey. Analysis of historical cost data was the basis for development of the cost estimating prototype tool. The general conclusions are: 1) project design and construction costs depend on various factors, such as facility types, project size, location, and facility features; 2) many construction projects for rural and small urban area transit facilities were suspended or delayed due to lack of funding; 3) most transit projects in rural and small urban areas include more than one type of facility; 4) state departments of transportation (DOTs) and transit agencies rely on estimates prepared by consultants; 5) both design and construction costs are estimated based on similar projects; 6) risk factors were identified through telephone interviews, and the frequency of the risk factors was obtained from the online survey; and 7) in order to address project risks, contingency is estimated as a percentage of construction cost. The ranges of contingency percentage given by the interviewees and survey results provided a reference for determining the default contingency range for the cost estimating prototype tool.