<p> Transportation planning is a vital and necessary operation for a metropolitan area to grow. As such, and in order to receive Federal funding for transportation projects, metropolitan areas engage in transportation planning as regulated by MAP-21. One element of meeting MAP-21 requirements is addressing the safety of a region. With new requirements by MAP-21, MPOs must demonstrate some sort of performance measure showing changes in the various elements, making quantitative means of displaying these changes ever more important. </p><p> The goal of this project was to develop a model or set of models that could produce quantitative results as opposed to the traditional qualitative results gained from professional opinion. This allows for better decision-making for test project scoring in transportation plans and additionally in meeting MAP-21 requirements. Following a review of the current available methodologies and an inventory of other states&rsquo; efforts to develop crash prediction models, mathematical modeling for Louisiana statewide crash prediction formulae were attempted. These results and the methodology were deemed unsuitable for the desired outcomes and the use of SVR modeling was explored. </p><p> The use of the SVR models described in this report produce acceptable results, have been validated for use in forecasting, and allow for the comparison of conditions between base data, future years, and future years with MTP test projects included. The results of these models provide transportation planners increased means to determine project rankings based on safety as well as satisfy MAP-21 requirements.</p>

<p> Highway safely improvement is a critical issue for local and national transportation authorities. One of the most important tasks in highway safety analysis is the identification of appropriate countermeasures that might be useful in making signicant safety improvement. Targeting safety at roadway segments has been the key focus of safety related projects at all levels. Recognizing that resources are limited in Louisiana, an emphasis is provided on the identication of strategies that will yield impressive results that are easily implemented from both time and cost perspective. An extensive study on the selection of Louisiana specific inexpensive and effective countermeasures has not been performed yet. Safety countermeasures with high safety effects and low implementation costs are always preferable. This dissertation has developed a Six Sigma DMADV tool uniquely designed for determining effective, inexpensive countermeasures that can be used in both aggregate and disaggregate level. Using the framework of DMADV toolset, this dissertation has selected three inexpensive countermeasures suitable for Louisiana and has developed CMFs for the selected countermeasures. Moreover, a commercialization tool has been developed for transferring the research results to successful commercial product design. The results from this dissertation are practice-ready and has been used by the transportation authorities in Louisiana. </p>

<p> Fatigue cracking is one of the complex distresses that is dependent of pavement structure, asphalt mixture properties and environmental conditions. During the last decades, many asphalt agencies have conducted significant researches to investigate the fatigue cracking characterization. However, fatigue performance is still difficult to predict not only due to models and parameters but also because this phenomenon itself is not well understood. </p><p> The key point in fatigue performance prediction is which model to use and how to find the correct parameters for the selected model by using the simplest but the most reliable testing method. The modulus is one of the primary asphalt mixture properties used for the mechanistic performance prediction of asphalt pavements. Dynamic modulus testing is a common method of measuring mixture modulus as a function of loading frequencies and temperatures. Despite the numerous researches that have been carried out to evaluate mixture stiffness, it is still necessary to establish a practical dynamic modulus test method that is compatible with the field cores which are mostly less than a few inches. One of the objectives of this dissertation is to present the results of a ruggedness study of dynamic modulus testing in indirect tension mode to evaluate the factors that are most likely to affect the final results. Specimen thickness, air void content, gauge length, test temperature, and horizontal strain level, that are the critical factors that affect the dynamic modulus of asphalt concrete, were selected for the ruggedness analysis. According to the findings, air void content was found to be a major factor that affects the dynamic modulus values. </p><p> To investigate the fatigue life of the pavement, valid cyclic fatigue testing data which truly represents the mixture behavior seems necessary besides the mixture stiffness. With regard to direct tension fatigue testing, one of the common problems that substantially influence the mixture fatigue behavior is the failure at the ends of the asphalt specimens. During testing, it was observed that as more and more material was cut from the top and bottom of the gyratory-compacted specimens, the likelihood of failure in the middle of the specimen greatly increased. Therefore, fabricating shorter test specimens that are cored and cut from taller gyratory-compacted specimens can produce test specimens that have more uniformly distributed air voids such that middle failure occurs within the gauge length of the linear variable differential transformer (LVDT) in direct tension tests. As a part of study, the optimum specimen geometry of 100 mm diameter and 130 mm height was introduced through the experimental testing and numerical simulation. </p><p> The Simplified Viscoelastic Continuum Damage (S-VECD) model, a continuum damage mechanics-based model that is known as one of the effective models, has been applied to predict the performance of asphalt concrete mixtures under different loading conditions. Besides, energy-based fatigue failure criterion (<i>G^R</i>) has been proved to be able to predict the fatigue life of asphalt concrete mixtures across different modes of loading, temperatures, and strain amplitudes. This dissertation presents the application and calibration of the L&barbelow;ayered V&barbelow;iscoE&barbelow;lastic pavement analysis for C&barbelow;ritical D&barbelow;istresses (LVECD) program which is based on both S-VECD and G^R method to evaluate 33 pavement sections from different locations inside the United States, Canada, South Korea, and China. The capability of the LVECD program to capture crack initiation, crack propagation and, the damage in the pavement sections is investigated by comparing the simulation results with the field observations. In this regard, LVECD was found to effectively predict the fatigue cracking propagation in the pavement sections since reasonable agreement was obtained between the program simulations and field observations. Finally, predicted damage-to-field cracking transfer function was developed to correlate the predictive damage to the measured cracking.</p>

<p> This project presents the design, implementation and experimental demonstration of an intensity control system for highway lighting. High Intensity Discharge lights (HID) are replaced by the White Light Emitting diodes (LED) in highway lighting systems in order to incorporate the dimming feature and conserve energy. The intensity is controlled by utilizing a micro controller that belongs to the 8051 family by generating pulse width modulated signals that energize a metal-oxide-semiconductor field effect transistor (MOSFET) to switch the LEDs to accomplish the desired operation. </p><p> A working model using ATMEL has been developed in which an array of LEDs are connected in series and parallel to control the light intensity applicable to the highway lights, which makes it a real time system. The micro controller is programmed to keep light intensity high during peak traffic hours, and gradually reduce it as traffic decreases, until dawn when lights are turned off to save energy.</p>

<p> The increasing trend in crashes and consequent fatalities due to distracted driving is a growing safety concern in our road network. With rapid advancement in cellphone and in-vehicle technologies along with driver&rsquo;s inclination to multitasking, the number of crashes due to distracted driving are further on the rise. Some previous studies attempted to detect distracted driving behavior in real-time to mitigate this issue. However, these studies mainly focused on detecting either visual or cognitive distractions, while most of the real-life distracting tasks involve driver&rsquo;s visual, cognitive, and physical workload, simultaneously. Additionally, previous studies frequently used eye, head, or face tracking data, although current vehicles are not equipped with technologies to acquire such data. To address above issues, this driving simulator study focused on developing algorithms for detecting specific distraction tasks using only vehicle control and driving performance measures. Specifically, algorithms were developed to detect two distracting tasks &ndash; texting and eating/drinking. Three data mining techniques were explored &ndash; Linear Discriminant Analysis (LDA), Logistic Regression (LR), and Support Vector Machine (SVM). SVM algorithms found to outperform LDA and LR, which detected texting and eating/drinking distraction with an accuracy of 84.33% and 79.53%, respectively. This study may provide useful guidance to successful implementation of distracted driver detection algorithm in Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communication, as well as to auto manufacturers interested in integrating distraction detection systems in their vehicles. </p>

<p> This paper proposes an in-node microprocessor-based vehicle classification approach to analyze and determine the types of vehicles passing over a 3-axis magnetometer sensor. The approach for vehicle classification utilizes J48 classification algorithm implemented in Weka (a machine learning software suite). J48 is Quinlan's C4.5 algorithm, an extension of decision tree machine learning based on an ID3 algorithm. The decision tree model is generated from a set of features extracted from vehicles passing over the 3-axis sensor. The features are attributes provided with correct classifications to the J48 training algorithm to generate a decision tree model with varying degrees of classification rates based on cross-validation. Ideally, using fewer attributes to generate the model allows for the highest computational efficiency due to fewer features needed to be calculated while minimalizing the tree with fewer branches. The generated tree model can then be easily implemented using nested if-loops in any language on a multitude of microprocessors. Also, setting an adaptive baseline to negate the effects of the background magnetic field allows reuse of the same tree model in multiple environments. The result of the experiment shows that the vehicle classification system is effective and efficient.</p>

<p>Owners face challenges in setting priorities between potential projects to maintain, rehabilitate, and improve their infrastructure. The estimated cost of each potential project is a factor that owners use in setting priorities between projects and in developing their long-term maintenance and construction project portfolio. Owners face a dilemma: considerable effort is needed to develop accurate estimates of the cost of each project, but this effort will be wasted if the particular project is not selected for the long-term plan. They therefore need estimating methods that will enable them to develop reasonably accurate early stage cost estimates without an excessive amount of effort. These early stage estimates are ?conceptual cost estimates? and ?feasibility cost estimates.? This research examines the tools that are available to owners for performing early stage cost estimates for infrastructure projects. It then compares alternative parametric functions that could be used for that purpose, using data from public agencies in California. These functions are the linear parametric, common exponential parametric, and modified Cobb-Douglas exponential parametric models. This research tests the models on 1 common type of project, pedestrian access facility projects on highways. In the United States (US) these projects result, directly and indirectly, from the Americans with Disabilities Act (ADA) that Congress passed in 1990. On highways, they produce three types of improvement: 1. wheelchair ramps at street corners to allow people in wheelchairs to cross streets at designated pedestrian crossings, 2. wheelchair-accessible sidewalks, and 3. audible signals at signalized intersections to inform visually impaired people when a pedestrian signal is in their favor. The author developed a data set of 39 pedestrian access facility projects on state highways in California, used multiple regression analysis to find 4 best-fit versions of each of the 3 functions (i.e., 12 alternatives in all), and evaluated them using the Choosing By Advantages (CBA) method. The author then benchmarks the preferred state highway cost estimating model identified in the CBA against 10 city-street pedestrian access facility projects that had been completed by 4 cities in the San Francisco Bay Area. He finds a significant difference between the state highway project cost data and the city street project cost data, and further rationalizes that these differences have their roots in both the contracting methods used by the agencies and the fact that Caltrans prepares detailed designs while cities do only minimal design. The data suggests that there is an opportunity to increase output and lower the costs of pedestrian access projects (and perhaps other types of highway projects as well) by decreasing the Caltrans design effort and transferring more of the design effort and consequent risk to contractors. This could be tested through experimentation on selected pedestrian access facility installations. This dissertation contributes to knowledge by providing a review of the place of conceptual and feasibility estimating both with respect to the overall project timeline and with respect to the methods used. It provides specific examples of the use of the various classes of estimates in the development of highway projects, and it provides a synthesis of the research on conceptual and feasibility estimating methods, most notably of parametric estimating. It then provides specific examples of parametric estimates on pedestrian access projects on California State Highways and in San Francisco Bay Area cities. Finally, it unveils the successful use by Bay Area cities of a minimal amount of design when developing design-bid-build contracts for pedestrian access facilities. The dissertation aims to provide an approach that could be used both for project-by-project conceptual estimating prior to the start of work on highway projects and for evaluating the overall credibility of the estimates on large portfolios of highway projects.

<p> Intelligent transportation systems use in-pavement inductive loop sensors to collect real time traffic data. This method is very expensive in terms of installation and maintenance. Our research is focused on developing advanced algorithms capable of generating high amounts of energy that can charge a battery. This electromechanical energy conversion is an optimal way of energy scavenging that makes use of piezoelectric sensors. The power generated is sufficient to run the vehicle detection module that has several sensors embedded together. To achieve these goals, we have developed a simulation module using software&rsquo;s like LabVIEW and Multisim. The simulation module recreates a practical scenario that takes into consideration vehicle weight, speed, wheel width and frequency of the traffic.</p>

Report (M.S.)--Virginia Polytechnic Institute and State University, 1994. / Abstract. Includes bibliographical references (leaves 30-33). Also available via the Internet.

Thesis (M.Eng.(Industrial Engineering))--University of Pretoria, 2009. / Includes bibliographical references.