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Procedures and models for estimating preconstruction costs of highway projects.
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  • Abstract:
    This study presents data driven and component based PE cost prediction models by utilizing critical factors retrieved from ten years of historical project data obtained from ODOT roadway division. The study used factor analysis of covariance and correlation matrix to investigate the significance of factors affecting preliminary engineering cost and identify the correlation among them. A combination of three models; regression models, decision tree models and neural network models developed to obtain the optimum roadway PE cost model is presented as a function of three entities a) engineering hours required per number of sheets, b) number of sheets and c) cost per engineering hours for various plan development task outputs. An Excel-based program called Roadway PE Cost Estimator which allows ODOT engineers to estimate a reasonable PE cost is also presented in the study.

    The results of this project is expected to significantly influence how efficiently and economically highway projects are planned, executed and managed in the early stages of a project. The developed system allows the engineer to estimate the values for the respective entities; number of sheets, work effort (engineering hours) required per number of sheets, cost per engineering hour, and total cost for a project based on factors such as project length, location, route type and project type. In addition, this system not only allows engineers to easily manipulate the requirements for a specific plan development task, but also help them configure contingencies, as to whether any of the entities are either under/over-estimated, or if there exists misallocation of resources (engineering hours assigned to the respective skilled manpower or number of sheets assigned at a specific level especially when negotiating PE costs with consulting firms.

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