Date of Award:

5-2015

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Civil and Environmental Engineering

Committee Chair(s)

Kevin Heaslip

Committee

Kevin Heaslip

Committee

Ziqi Song

Committee

Ryan Dupont

Abstract

In the scope of transportation asset management, the maintenance and rehabilitation (M&R) performed on asphalt roads at the local government level requires careful planning and intelligent use of limited funding. For this reason, a Pavement Management System (PMS) is incorporated and used as a tool for local government leaders to make the best decision given their annual budget. The PMS process is a repeatable process which consists of determining present day pavement condition, evaluating future deterioration, performing an economic analysis of possible M&R treatments and finally implementing a proper M&R plan to keep the asphalt pavement network in good condition.

The PMS procedure has been incorporated into various software packages to facilitate the process and store historical records of asset management. Currently there is a wide range of methods and techniques utilized to successfully implement a PMS for local governments. The research presented in this thesis investigates the sensitivity of the software package results to data collection procedures, and the effects data collection procedure has on the final economic analysis recommendations.

In this research, two PMS software packages were utilized for analysis: the TAMS software package developed by the Utah LTAP Center at Utah State University and the Micro PAVERTM software package developed by the Army Corps of Engineers. Statistical models were utilized to determine the effect that the nine condition distresses for TAMS and the 20 condition distresses for Micro PAVERTM had on the estimated recommended M&R cost provided by the software's economic analysis results, respectively. The results of this thesis illustrate the differences and similarities both PMS software packages have in terms of the data collection methodologies, and their respective influence on the software package's economic analysis. This research also investigates the possibility of utilizing statistically produced models as a direct cost estimator given pavement condition data.

The findings and methods of the conducted research will enable local governments to be aware of the types of distresses that are more sensitive to the estimated recommended M&R cost. This might provide incentive for careful consideration when recording certain distress observations that have a higher influence to the future results of the economic analysis than others.

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