This Is AuburnElectronic Theses and Dissertations

Data Usage Optimization for Cost Estimating in Asphalt Paving Projects Using a Cost Indexing System




Pakalapati, Karthik Chowdary

Type of Degree

Master's Thesis


Civil Engineering


During the last decade, the transportation construction industry has seen an increase in the implementation of historical bid-based cost estimating practices by various state transportation agencies (STAs). The American Association of State Highway and Transportation Officials (AASHTO), provides basic guidelines on the preparation of construction cost estimates using bid data from previous transportation construction projects. The process presented in the AASHTO guidebook includes a number of assumptions whose validity does not seem to have been challenged in the existing literature. One of these assumptions, and the one addressed in this thesis, refers to the optimal number of year of historical data to be used for estimating purposes. The primary objective of this study is to develop a methodology to assist the Alabama Department of Transportation (ALDOT) with the definition of optimal look-back periods for data retrieval to maximize estimating accuracy in asphalt paving projects. According to AASHTO guidelines, a one- or two-year lookback period is commonly used for bid-based estimating purposes, and sometimes, it could be extended if the last two years do not provide sufficient data. However, no guidance is provided on how to determine whether to use one, two, or more years of data. How can a STA estimator know how many years of data would be required to maximize estimating accuracy? This is the main question to be answered in this thesis. Taking into consideration that the amount of data is irrelevant if it is not appropriately collected, clean, and processed, the proposed look-back determination process is presented along with a data-driven cost estimating methodology designed to maximize the effectiveness of bid- base estimates. The optimal look-back period is determined, and the application and effectiveness of the cost estimating methodology is demonstrated, using ALDOT’s historical bid data for all projects awarded between 2011 and 2016 (2122 contracts). A moving-window analysis algorithm has been designed to measure the performance of the estimating model over 6 years and for different look-back periods ranging from 1 to 5 years. The moving-window algorithm includes a number of research techniques, including advance data cleaning procedures, non-linear regression, time series analysis, and various statistical significance testing approaches. The proposed bid-based estimating methodology has been designed to counteract the impact of inflation on estimates produced with data from previous projects. Thus, the author has also developed an innovative construction cost indexing system (CCIS) intended to adjust past construction prices based on observed fluctuations in the construction market. The thesis presents a comparative analysis conducted to select the most suitable cost indexing approach among 20 alternatives, including twelve different versions of the CCIS (developed in this study) and eight existing construction cost indexes (CCIs) currently used in the construction industry. The twelve different versions of the CCIS were developed by taking into consideration three different index recalculation periods (i.e. quarterly, semi-annual, and annual) and four types of inputs for each recalculation period (i.e. all bids, median values on a project basis, average values on a project basis, and only awarded bids). The use of the look-back period determination process and the proposed data-driven cost estimating methodology are illustrated in this thesis as they are applied to the most relevant pay item used in ALDOT’s paving projects: “Superpave Bituminous Concrete Wearing Surface Layer, 1/2" Maximum Aggregate Size Mix, ESAL Range C/D – Item ID 424A360.” It was found that unit prices for the case study item (item 424A360) are more accurately estimated using two years of historical bid data and a quarterly CCIS calculated with all bids received by ALDOT for this item. Even though these findings are only applicable to the case study item, the thesis presents the process in a detailed manner, so that it could repeated for other cost items, on an as needed basis.