Pavement structural condition plays a critical role in the rate of pavement deterioration, yet most state highway agencies' network-level decision-making processes are primarily based on surface distresses. Despite the limitations of the traditional structural condition measuring devices, some states have experimented with stationary deflection devices for network-level applications. Over the past decade, continuous deflection devices have become capable of measuring the network-level pavement structural condition information. However, since the traffic speed deflection devices use newer technology, there is a need for guidelines on how the state agencies could make use of this information for pavement management decision-making. This dissertation developed processes and enhanced tools to incorporate the pavement structural condition from the TSD into Virginia's network-level pavement management process This first part of the study developed pavement deterioration models for a subset of road networks in Virginia, to show that the pavement structural condition as measured by the TSD has an impact on the rate of deterioration of the surface condition. A structural condition matrix was then developed to augment the treatment selection process currently used by VDOT. Application of the augmented matrix on the tested Interstate network resulted in reducing the percentage of the network requiring CM and increasing the percentage requiring PM and RM. The second part of the study investigated the possibility of using pavement deflection measurements obtained from the TSD for network-level structural evaluation of pavements in Virginia. The study reported that the structural condition obtained with the TSD can replace the structural condition obtained from the FWD that is currently used in the VDOT PMS. The effective structural number (SNeff) calculated from the TSD and FWD had similar distribution, and the calculated consistency between the TSD SNeff and FWD SNeff was higher than the consistency between the SNeff from two repeated sets of FWD measurements. The third part of the study simulated the network level decision-making approaches based on both the structural condition parameter and the surface condition parameter, considering cases with and without the pavement treatment interval. The study reported that network-level decisions based on the pavement surface condition alone can result in significantly different treatment selection, compared to decisions based on the pavement structural condition. The study reported savings of 9% and 11% for cases with and without considering the pavement treatment intervals, using decision-making based on the structural condition. / Doctor of Philosophy / Pavement structural condition plays a critical role in the rate of pavement deterioration, yet most state highway agencies' network-level decision-making processes are primarily based on surface distresses. Despite the limitations of the traditional structural condition measuring devices, some states have experimented with stationary deflection devices for network-level applications. Over the past decade, continuous deflection devices have become capable of measuring the network-level pavement structural condition information. However, since the traffic speed deflection devices use newer technology, there is a need for guidelines on how the state agencies could make use of this information for pavement management decision-making. This dissertation developed processes and enhanced tools to incorporate the pavement structural condition from the TSD into Virginia's network-level pavement management process' This first part of the study developed pavement deterioration models for a subset of road networks in Virginia, to show that the pavement structural condition as measured by the TSD has an impact on the rate of deterioration of the surface condition. A structural condition matrix was then developed to augment the treatment selection process currently used by VDOT. Application of the augmented matrix on the tested Interstate network resulted in reducing the percentage of the network requiring CM and increasing the percentage requiring PM and RM. The second part of the study investigated the possibility of using pavement deflection measurements obtained from the TSD for network-level structural evaluation of pavements in Virginia. The study reported that the structural condition obtained with the TSD can replace the structural condition obtained from the FWD that is currently used in the VDOT PMS. The effective structural number (SNeff) calculated from the TSD and FWD had similar distribution, and the calculated consistency between the TSD SNeff and FWD SNeff was higher than the consistency between the SNeff from two repeated sets of FWD measurements. The third part of the study simulated the network level decision-making approaches based on both the structural condition parameter and the surface condition parameter, considering cases with and without the pavement treatment interval. The study reported that network-level decisions based on the pavement surface condition alone can result in significantly different treatment selection, compared to decisions based on the pavement structural condition. The study reported savings of 9% and 11% for cases with and without considering the pavement treatment intervals, using decision-making based on the structural condition.

With the growing need to maintain roadway systems for provision of safety and comfort for travelers, network level decision-making becomes more vital than ever. In order to keep pace with this fast evolving trend, highway authorities must maintain extremely effective databases to keep track of their highway maintenance needs. Florida Department of Transportation (FDOT), as a leader in transportation innovations in the U.S., maintains Pavement Condition Survey (PCS) database of cracking, rutting, and ride information that are updated annually. Crack rating is an important parameter used by FDOT for making maintenance decisions and budget appropriation. By establishing a crack rating threshold below which traveler comfort is not assured, authorities can screen the pavement sections which are in need of Maintenance and Rehabilitation (M&R). Hence, accurate and reliable prediction of crack thresholds is essential to optimize the rehabilitation budget and manpower. Transition Probability Matrices (TPM) can be utilized to accurately predict the deterioration of crack ratings leading to the threshold. Such TPMs are usually developed by historical data or expert or experienced maintenance engineers' opinion. When historical data are used to develop TPMs, deterioration trends have been used vii indiscriminately, i.e. with no discrimination made between pavements that degrade at different rates. However, a more discriminatory method is used in this thesis to develop TPMs based on classifying pavements first into two groups. They are pavements with relatively high traffic and, pavements with a history of excessive degradation due to delayed rehabilitation. The new approach uses a multiple non-linear regression process to separately optimize TPMs for the two groups selected by prior screening of the database. The developed TPMs are shown to have minimal prediction errors with respect to crack ratings in the database that were not used in the TPM formation. It is concluded that the above two groups are statistically different from each other with respect to the rate of cracking. The observed significant differences in the deterioration trends would provide a valuable tool for the authorities in making critical network-level decisions. The same methodology can be applied in other transportation agencies based on the corresponding databases.