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.

This thesis presents (a) results of a field evaluation of the Traffic Speed Deflectometer (TSD) in the United States (b) deflection thresholds to classify the pavement structural condition obtained from the TSD for a small subset of the Pennsylvania secondary road network. The results of the field evaluation included: (1) repeatability of the TSD, (2) ability of the TSD to identify pavement sections with varying structural conditions, and (3) consistency between the structural number (SNeff) calculated from the TSD and SNeff calculated by the Pennsylvania Department of Transportation (PennDOT). The results showed consistent error standard deviation in the TSD measurements and that the TSD was able to identify pavement sections that varied in structural condition. Comparison of the SNeff calculated with TSD measurements, using an empirically developed equation by Rohde, with the SNeff calculated by PennDOT’s Pavement Management System based on construction history showed similar trends, although the TSD-calculated SNeff was higher. In order to develop deflection thresholds, a model that related the pavement surface condition to pavement surface age and structural condition was developed. Structural condition thresholds were then selected so that the pavement surface condition predicted from the model for a 10-year-old pavement surface fell within one of the three condition categories (Good, Fair, and Poor), to identify pavements in good, fair and poor condition. With Overall Pavement Index(OPI) characterizing the surface condition and Deflection Slope Index(DSI) characterizing the structural condition, the DSI threshold that separates structurally good from structurally fair pavements was determined as follows: (1) the OPI threshold that separates pavements with good surface condition from those with fair surface condition was obtained from the Pennsylvania Pavement Management System (PMS) and (2) the DSI thresholds were calculated using the determined OPI value and the model equation. / Master of Science / This thesis presents (a) some of the results of a field evaluation of the Traffic Speed Deflectometer (TSD) in the United States (b) deflection thresholds to classify the pavement structural condition obtained from the TSD for a small subset of the Pennsylvania secondary road network. The results of the field evaluation included: (1) repeatability of the TSD: which is the variation in repeated TSD measurements on the same section of the road, (2) ability of the TSD to identify pavement sections with varying structural conditions, and (3) consistency between the structural number (SNeff) calculated from the TSD and SNeff calculated by the Pennsylvania Department of Transportation (PennDOT). The pavement structural number is an abstract number expressing the structural strength of the pavement. The results showed that the TSD measurements were repeatable and that the TSD was able to identify pavement sections that varied in structural condition. Comparison of the SNeff calculated with TSD measurements, using an empirically developed equation by Rohde, with the SNeff calculated by PennDOT Pavement Management System based on construction history showed similar trends, although the TSD-calculated SNeff was higher. In order to develop deflection thresholds to categorize pavements in different condition: good, fair and poor, a model that related the pavement surface condition to pavement surface age and structural condition was developed. Structural condition thresholds were then selected so that the pavement surface condition predicted from the model for a 10-year-old pavement surface fell within one of the three condition categories (Good, Fair, and Poor), to identify pavements in good, fair and poor condition. With Overall Pavement Index(OPI) characterizing the surface condition and Deflection Slope Index(DSI) characterizing the structural condition, the DSI threshold that separates structurally good from structurally fair pavements was determined as follows: (1) the OPI threshold that separates pavements with good surface condition from those with fair surface condition was obtained from the Pennsylvania Pavement Management System (PMS) and (2) the DSI thresholds were calculated using the determined OPI value and the model equation.