Increasing demands, shrinking financial and human resources, and increased infrastructure deterioration have made the task of maintaining the infrastructure systems more challenging than ever before. Life-cycle cost analysis (LCCA) is an important tool for transportation infrastructure management, which is used extensively to support project level decisions, and is increasingly being applied to enhance network level analysis. However, traditional LCCA tools cannot practically and effectively utilize expert knowledge and handle ambiguous uncertainties. The main objective of this dissertation was to develop enhanced LCCA models using soft computing (mainly fuzzy logic) techniques. The proposed models use available "real-world" information to forecast life-cycle costs of competing maintenance and rehabilitation strategies and support infrastructure management decisions. A critical review of available soft computing techniques and their applications in infrastructure management suggested that these techniques provide appealing alternatives for supporting many of the infrastructure management functions. In particular, LCCA often utilizes information that is uncertain, ambiguous and incomplete, which is obtained from both existing databases and expert opinion. Consequently, fuzzy logic techniques were selected to enhance life-cycle cost analysis of transportation infrastructure investments because they provide a formal approach for the effective treatment of these types of information. The dissertation first proposes a fuzzy-logic-based decision-support model, whose inference rules can be customized according to agency's management policies and expert opinion. The feasibility and practicality of the proposed model is illustrated by its implementation in a life-cycle cost analysis algorithm for comparing and selecting pavement maintenance, rehabilitation and reconstruction (MR&R) policies. To enhance the traditional probabilistic LCCA model, the fuzzy-logic-based model is then incorporated into the risk analysis process. A fuzzy logic approach for determining the timing of pavement MR&R treatments in a probabilistic LCCA model for selecting pavement MR&R strategies is proposed. The proposed approach uses performance curves and fuzzy-logic triggering models to determine the most effective timing of pavement MR&R activities. The application of the approach in a case study demonstrates that the fuzzy-logic-based risk analysis model for LCCA can effectively produce results that are at least comparable to those of the benchmark methods while effectively considering some of the ambiguous uncertainty inherent to the process. Finally, the research establishes a systematic method to calibrate the fuzzy-logic based rehabilitation decision model using real cases extracted from the Long Term Pavement Performance (LTPP) database. By reinterpreting the model in the form of a neuro-fuzzy system, the calibration algorithm takes advantage of the learning capabilities of artificial neural networks for tuning the fuzzy membership functions and rules. The practicality of the method is demonstrated by successfully tuning the treatment selection model to distinguish between rehabilitation (light overlay) and do-nothing cases. / Ph. D.

Increasingly tighter budgets, changes in government role/function, declines in staff resources, and demands for increased accountability in the transportation field have brought unprecedented challenges for state transportation officials at all management levels. Systematic methodologies for effective management of a specific type of infrastructure (e.g., pavement and bridges) as well as for holistically managing all types of infrastructure assets are being developed to approach these challenges. In particular, the intrinsic characteristics of highway system make the use of multi-objective optimization techniques particularly attractive for managing highway assets. Recognizing the need for effective tradeoff tools and the limitations of state-of-practice analytical models and tools in highway asset management, the main objective of this dissertation was to develop a performance-based asset management framework that uses multi-objective optimization techniques and consists of stand-alone but logically interconnected optimization models for different management levels. Based on a critical review of popular multi-objective optimization techniques and their applications in highway asset management, a synergistic integration of complementary multi-criteria optimization techniques is recommended for the development of practical and efficient decision-supporting tools. Accordingly, the dissertation first proposes and implements a probabilistic multi-objective model for performance-based pavement preservation programming that uses the weighting sum method and chance constraints. This model can handle multiple incommensurable and conflicting objectives while considering probabilistic constraints related to the available budget over the planning horizon, but is found more suitable to problems with small number of objective functions due to its computational intensity. To enhance the above model, a hybrid model that requires less computing time and systematically captures the decision maker's preferences on multiple objectives is developed by combining the analytic hierarchy process and goal programming. This model is further extended to also capture the relative importance existent within optimization constraints to be suitable for allocations of funding across multiple districts for a decentralized state department of transportation. Finally, as a continuation of the above proposed models for the succeeding management level, a project selection model capable of incorporating qualitative factors (e.g. equity, user satisfaction) into the decision making is developed. This model combines k-means clustering, analytic hierarchy process and integer linear programming. All the models are logically interconnected in a comprehensive resource allocation framework. Their feasibility, practicality and potential benefits are illustrated through various case studies and recommendations for further developments are provided. / Ph. D.

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.

Sustainability is increasingly becoming a significant part of strategic asset management worldwide. Road agencies are providing guidelines to assess the relative sustainability of road projects. Unfortunately, environmental features of a road project are still considered as stand-alone evaluations, an added value. Very little has been done to integrate environmental impacts as a part of pavement management systems and other decision support tools to choose between different strategies. In this way, being awarded with a "green" certificate for a specific road project could result in the belief that recognition would correspond to the optimal strategy. Furthermore, a road project awarded with a "green" rating during the construction phase does not mean that the project results "green" if a life cycle approach is considered. Indeed, the most environmental friendly strategies may not be the ones with the highest performance. Using "greener" materials or performing recycle-related practices may lead to a lower performance over the life cycle and therefore produce an increase in maintenance needed, which could in turn result into more congestion due to work zones and higher total emissions. Therefore, construction and maintenance strategies should be analyzed according to three main parameters: cost, performance or effectiveness, and environmental impacts. The cost analysis part takes into account outflows over the service life of the pavement according to the well-known Life Cycle Cost Analysis methodology. The cheapest maintenance technique over the analysis period was expounded and sensitivity analyses to involved factors were conducted. Performance assessment was developed according to experimental on site data gathered and analyzed over several years to develop deterioration pavement models. Effectiveness of maintenance treatments is further provided and compared to the volume of traffic. In addition, environmental impacts related to maintenance and rehabilitation strategies were analyzed. Emissions were computed over the life cycle of the pavement from the manufacture of raw materials for the initial construction, placement, and maintenance phase. Finally, an optimization procedure was developed for including environmental impacts into a Pavement Management System. A methodology to set a multi-attribute approach system, computing costs, performance, and eco-efficiency over the life cycle of the pavement, is therefore proposed. / Ph. D.

The objective of this research was to develop a structural index for use in network-level pavement evaluation, which facilitates the inclusion of the pavements structural condition in many pavement management applications. The primary goal of network-level pavement management is to maintain an acceptable condition of the pavements within the network using available, and often limited, resources. Pavement condition is described in terms of functional and structural condition, and the current widespread practice is to only consider the functional condition during network-level evaluation. This practice results in treatments that are often under-designed or over-designed when considered in more detail at the project-level. The disagreement may be reduced by considering the structural capacity of the pavements as part of the network-level decision process. This research was conducted by identifying various structural indices, choosing an appropriate index, and then applying data from the state of Virginia to modify the index and show example application for the index. It was concluded that the Modified Structural Index best met the research objectives. Project-level and network level data were used to conduct a sensitivity analysis on the index, and example applications were presented. The results indicated that the inclusion of the Modified Structural Index into the network-level decision process minimized the errors between network-level and project-level decisions, when compared to the current network-level decision making process. Furthermore, the Modified Structural Index could be used in various pavement management applications, such as network-level structural screening, and developing structural performance measures. / Master of Science

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.

A pavement investment and management process has a dynamic structure with cause and effect. Better investment decisions for maintenance will increase the condition of the flexible pavement and will end up with a better level of service. Therefore, better investments decisions on pavement maintenance will increase the economic growth and global competition for the area. However, improper allocation of money and resources would end up with further deteriorations of the facilities. So asset management encourages highway maintenance managers to spend their scarce budget for the maintenance that is really needed. A well-developed pavement management simulation model will allow highway maintenance managers to consider the impact of choosing one maintenance policy alternative versus another through what-if analysis and having informed decisions. Discrete event simulation (DES) is an alternative method of analysis that offers numerous benefits in pavement management. Unlike the models currently in use, a decision support model created by utilizing the DES technique would allow fractionalizing the pavement in smaller proportions and simulating the policies on these smaller segments. Thus, users would see how their decisions would affect these specific segments in the highway network over a period of time. Furthermore, DES technique would better model the multiple resource requirements and dynamic complexity of pavement maintenance processes. The purpose for this research is to create a decision support tool utilizing discrete event simulation technique where the highway maintenance managers can foresee the outcomes of their what-if scenarios on the specific segments and whole of the highway network evaluated. Thus, can be used for both project and network level decision support. The simulation can also be used as a guiding tool on when, where and why resources are needed on needs basis. This research relies on the budget allocation results from the linear optimization model (LOM). This model is a tool that creates the optimized budget allocation scheme for a network fitting to a determined scenario. Thus by integrating the LOM and the DES model, the maintenance managers can acquire an optimized budget allocation for their district and evaluate the results in both network and project selection level. Maintenance managers can obtain the best budget allocation plan without performing the repetitive trial and error approach like the previous decision support tools. There is a vast amount data in many varieties gathered as results from the simulation model. This fact alone demonstrates how powerful the discrete event simulation model is. By the nature of this simulation technique, the resources (highway segments, annual budget) can be traced throughout the simulation and this trait allows the design of the project selection level decision support system. By examining these reports, the maintenance managers can better observe how the scenarios evolve. Thus this tool helps the maintenance managers to have better decisions on the project selection level. The discrete event simulation model established in this research carries the project selection level pavement management from a position where maintenance managers should solely depend on their engineering judgment and experience to a position where maintenance managers can have more effective and justified plans since they can foresee the results of these decisions on the segments that are forming the network. This simulation engine is created with the discrete event simulation language called STROBOSCOPE. The model consists of two parts which work like a lock and key mechanism. The first part of the model is the data feeding mechanism where information from any network is loaded. The second part is the generic engine which can evaluate any road network data it is fed. The purpose of segregating these two components of the model is to allow the user to evaluate any network regardless of length, number of segments or the location. / Master of Science

The purpose of this study is to assist TxDOT engineers in the field of traffic control planning. This is to be done via the creation of a Geographic Information System (GIS) based tool. By bringing together information about TxDOT’s on-system roadways’ geographical locations, traffic demands, and capacities, one aggregate database has been established. Using the tools of GIS, Microsoft Excel, Microsoft Access, and VBA programming, a static clickable interface has been constructed. It enables users to access properties for any selected roadway link they desire. Expansion of the product to ArcIMS is ongoing to allow easy access for end users via the internet. / text

Este trabalho foi realizado com o objetivo de aplicar o Modelo de Tavakoli, que é um modelo de gerência de pavimentos para vias urbanas, para análise de priorização de vias urbanas em cidade de médio porte. Para isso se utilizou um estudo de campo previamente realizado pela Prefeitura Municipal de Suzano e pelo Laboratório de Mecânica de Pavimentos da Universidade de São Paulo no município de Suzano, no ano de 2007, com o qual foi criado um banco de dados das vias do município. Naquele estudo foi empregado o modelo HDM-4 do Banco Mundial para a priorização de intervenções de manutenção nas vias públicas. No presente trabalho buscou-se elaborar um estudo comparativo entre aquela solução e a solução atingida pelo modelo de Tavakoli para um mesmo conjunto de vias. Para este trabalho o Modelo de Tavakoli foi adaptado para planilhas eletrônicas e aplicado em um conjunto de seções de pavimentos, permitindo a determinação de uma lista de prioridades de intervenções. Posteriormente, essas intervenções foram simuladas para o mesmo conjunto de vias, buscando a priorização dos serviços, com o modelo HDM-4 versão 1.0. Através deste trabalho foi possível concluir que os dois critérios estudados podem ser úteis para gerenciar vias urbanas, pois priorizaram as intervenções necessárias nas vias urbanas analisadas. Foi possível verificar que o Modelo de Tavakoli se revelou mais conservador, por ser um critério fechado, com um índice de prioridades dependendo diretamente do índice da condição do pavimento e do volume diário médio de tráfego, afetando diretamente a classificação das seções. No Modelo HDM-4 a classificação das seções e os valores de irregularidade não tiveram uma sincronia, pois o HDM-4 é um modelo de critérios abertos, que permite ao usuário acrescentar vários parâmetros, e com estes foi possível reproduzir uma situação um pouco mais próxima da realidade. / This study was conceived in order to apply the Tavakoli Model, which is a pavement management system for urban roads, aiming the analysis of prioritization of urban streets in a mid-sized city. A field study previously conducted by Suzano City and the Pavements Mechanics Laboratory of the University of São Paulo in Suzano City in 2007 was used, from which was created a database of the towns streets. In that study, the Highway Design and Management (HDM-4) Model of the World Bank was employed for prioritizing maintenance work on public roads. In this study it was sought to develop a comparative study between the mentioned solution and the one reached by Tavakolis Model in the same set of roads. In this research the Tavakoli Model was adapted for the spreadsheets and applied to a set of pavement sections, allowing the determination of a priority list of interventions including the specific type of intervention for each segment. Subsequently, these same types of strategies or interventions were simulated for the same set of paths, seeking the prioritization, with HDM-4 Model version 1.0. Through this research it was possible to conclude that both criteria studied can be useful for managing urban roads, because they prioritized the necessary interventions in the urban roads analyzed. The Tavakoli Model proved to be more conservative, on account of being a closed criterion, with a priority index depending directly on the pavement condition index and average daily volume of traffic, affecting the classification of the sections directly as well. In the HDM-4 Model, the classification of the sections and values of the International Roughness Index did not match, due to HDM-4 being an open criteria model, which allows the user to add several parameters, and they can lead to more realistic report.

Os modelos de previsão de desempenho de pavimentos são importantes ferramentas utilizadas pelos sistemas de gerência, essenciais para o planejamento das atividades de manutenção e reabilitação, assim como para a estimativa dos recursos necessários para a preservação das rodovias. Este trabalho tem por objetivo comparar modelos de desempenho de pavimentos, desenvolvidos por análises empíricas e empírico-mecanísticas, que predizem a evolução da condição de pavimentos flexíveis, ao longo do tempo e/ou tráfego acumulado. Os modelos de desempenho analisados foram desenvolvidos por pesquisadores e órgãos rodoviários brasileiros e internacionais, inclusive os modelos de deterioração utilizados pelo programa computacional de gerência de pavimentos desenvolvido pelo Banco Mundial, o HDM–4 (Highway Development and Management). A pesquisa está baseada na comparação do desempenho real de seções de pavimentos rodoviários, obtido a partir da base de dados dos experimentos LTPP (Long-Term Pavement Performance) do FHWA (Federal Highway Administration), com o comportamento previsto pelos modelos de desempenho desenvolvidos por Queiroz (1981), Paterson (1987), Marcon (1996) e Yshiba (2003). Neste trabalho, a análise do comportamento das seções de teste LTPP-FHWA é feita utilizando-se uma programação fatorial que, através da análise de variância (ANOVA), permite a determinação do nível de significância de fatores pré- selecionados (variáveis independentes: tráfego, idade e número estrutural corrigido) bem como a modelagem do desempenho dos pavimentos dessas seções (variáveis dependentes: irregularidade longitudinal e deformação permanente). / The pavement performance prediction models are important tools used for pavement management, essential for the planning of maintenance and rehabilitation activities, as well as for budgeting. The aim of this work is to compare performance prediction models developed through empirical and empirical-mechanistic analyses, which predict the evolution of the condition of flexible pavements, throughout the time and/or accumulated traffic. The performance prediction models analyzed were developed by researchers and Brazilian and international road agencies, including the deterioration models used by the pavement management comuputer program HDM-4 (Highway Development and Management), developed by the World Bank. The research is based on the comparison of the real performance of pavement of sections, obtained from the data base of the LTPP Program (Long-Term Pavement Performance) of FHWA (Federal Highway Administration), with the behavior predicted by deterioration models developed by Queiroz (1981), Paterson (1987), Marcon (1996) and Yshiba (2003). In this work, the analysis of the behavior of the LTPP-FHWA test sections is made through a factorial programming. Analysis of Variance (ANOVA) allows the determination of the level of significance of pre-selected factors (independent variables: traffic, age and pavement structure) and the development of performance prediction models (dependent variables: roughness and rutting).