General Aviation (GA) accidents constitute the majority of aviation related accidents. In the United States, there have been over 7,000 GA accidents compared to 190 airline accidents in the last 8 years. Flight data analysis has helped reduce the accident rate in commercial aviation. Similarly, safety analysis based on flight data can help GA be safer. The FAA mandates flight data recorders for multi-engine and turbine powered aircraft, but nearly 80% of General Aviation consists of single engine, of which only a small portion contain any form of data recording device. GA aircraft flight data recorders are costly for operating pilots. Low-cost flight recorders are few and rarely used in GA safety analysis due to lack of accuracy compared to the certified on-board equipment. In this thesis, I investigate the feasibility of using a low-cost Attitude and Heading Reference System (AHRS) to detect hazardous states in GA aircraft. I considered the case of roll angles and found that the low-cost device has significant measurement errors. I developed models to correct the roll angle error as well as methods to improve the detection of hazardous roll angles. I devised a method to evaluate the time accuracy along with the angle accuracy and showed that despite the errors, the low-cost device can provide partial hazardous state detection information.

Roadway safety continues to be a priority for the Utah Department of Transportation (UDOT) Traffic and Safety Division. UDOT has participated in and managed several research projects in recent years to determine the roadway segments of highest safety concern in the state. This research has provided UDOT with more tools to assist in safety project prioritization. Researchers in Department of Civil and Environmental Engineering at Brigham Young University (BYU) have worked with UDOT and the Statistics Department at BYU to create two network screening statistical tools called the Utah Crash Prediction Model (UCPM) and the Utah Crash Severity Model (UCSM) to analyze roadway segment safety. The Roadway Safety Analysis Methodology (RSAM) was developed as a process to run these segment models. Because a significant portion of crashes occur at intersections, there is a need to analyze roadway safety specifically at intersections. This research focuses on the development of the Utah Intersection Crash Prediction Model (UICPM) and the Intersection Safety Analysis Methodology (ISAM). The UICPM is a Bayesian generalized linear model that determines crash distributions for each intersection based on roadway characteristics and historical crash data. The observed number of crashes at each intersection is compared with the crash distribution, and a percentile value is calculated as the probability that the number of crashes occurring at an intersection in a particular year is less than or equal to the average annual number of crashes. A high percentile value indicates that more crashes were observed than expected and the intersection is a hot spot and should be considered for safety improvements. All intersections are ranked at the state, UDOT Region, and county levels based on the percentile value, the higher ranks having higher percentile values. The ISAM is the three-step process that was developed to execute the UICPM. The first step is to prepare the model input by formatting and combining the roadway characteristics and crash data files. Crashes are assigned to intersections if they fall with the functional area of an intersection. Due to data limitations, the ISAM is currently being used only for intersections of at least two state routes. It is anticipated that, as more data are made available, the ISAM will function properly for intersections of non-state routes as well. The second step is to execute the UICPM using the R GUI tool and R software. The third step is to create a two-page Intersection Safety Analysis Report (ISAR) for intersections of interest and maps of the state, UDOT Regions, and counties with the model results. Parts of the ISARs are auto-generated and the rest is entered manually by an analyst. The two-page ISARs will be used by UDOT Regions to prioritize intersection safety projects in their respective areas.

The Utah Department of Transportation (UDOT) Traffic and Safety Division continues to advance the safety of the state roadway network through network screening and decision making tools. In an effort to aid UDOT in meeting this goal, the Department of Civil and Environmental Engineering at Brigham Young University (BYU) has worked with the Statistics Department in developing analysis tools for highway safety, specifically the Utah Crash Prediction Model (UCPM) and the Utah Crash Severity Model (UCSM). Additional tools and methodologies, such as the "Hot Spot Identification and Analysis," have been created to summarize the roadway characteristics, crash data, and possible countermeasures of roadway segments with safety problems.This research focuses on the creation of a three part "Roadway Safety Analysis" methodology, which applies and automates the cumulative work of recently completed highway safety research conducted for UDOT. The first part is to prepare the roadway data and crash data for the statistical analysis. The second part is to perform the network screening statistical analysis; rank the segments by state, UDOT Region, and county; and select segments of interest. The third part is to compile and publish the Roadway Safety Analysis reports for the selected segments of interest. These parts are accomplished using the automation tools and graphical user interfaces (GUIs), which are documented in three respective volumes of user manuals. The automation tools and GUIs were developed with checks and processes to allow the Roadway Safety Analysis methodology to be completed with new, updated roadway and crash datasets.The Roadway Safety Analysis methodology allows future iterations of the UCPM and UCSM analysis and compilation of the Roadway Safety Analysis reports to be conducted in a user friendly environment. A series of critical data columns were identified to communicate the need for data consistency for future iterations of this safety research. An example of the entire process of the Roadway Safety Analysis methodology is given to illustrate how the three parts tie together. The overall process has automated data processing tasks, which saves time and resources for the analyst to investigate possible safety measures for segments of interest. Recommendations for future highway safety research are given, including continued development of the Roadway Safety Analysis methodology, an analysis of intersections and horizontal curves, the implementation of the Roadway Safety Analysis methodology to other states, and the advancement of safety countermeasures and geospatial tools for highway safety research.

In order to achieve sustainable long-term transport infrastructure development, there is a growing need for fast, reliable and effective methods to evaluate and predict the impact of traffic safety measures. Recognising this need, and the need for an active traffic safety approach, this thesis focuses on traffic safety assessment and prediction based on the use of safety indicators that measure the spatial and/or temporal proximity of safety critical events. The main advantage of such measures is that they occur more frequently than accidents, and therefore require relatively short periods of study to establish values that can later be used for comparison, or for accident prediction purposes. There are a number of more generally accepted safety indicators including: Time-to-Accident, Time-to-Collision, and Post-Encroachment Time. These are based on different underlying principles and measurement techniques, including both on-site subjective estimation, and objective photometric measures. A major part of the work presented in this thesis, concerns identifying the potential and limitations of the different safety indicators with regard to their validity and reliability, and practical use for safety assessment and prediction purposes. This is done in conjunction with field studies in the urban and suburban environment, at both signalised and unsignalised intersections. Results from these studies indicate that on-site observation methods provide useful quantitative and qualitative information relatively quickly and efficiently, provided that they are used correctly. On the other hand, the methods based on photometric measurement (video-analysis) proved arduous and time-consuming. Furthermore, there are questions regarding the abilities of the Time-to-Collision and Post-Encroachment Time safety indicators to adequately represent interaction severity, suggesting possible flaws in fundamental concepts related to construct validity. Importantly, results showed that the relationship between safety indicators and traffic accidents is complex and equivocal, where many different factors and processes can impose a significant influence on safety. This makes generalised predictive modelling a particularly difficult task for safety analysts. The potential of micro-simulation for traffic safety and performance estimation based on the use of safety indicators was investigated in the second part of this thesis. Microscopic traffic simulation has become increasingly popular among transport planners, due to the fact that it serves as a safe and flexible off-line test environment for the estimation of dynamic and complex traffic system effects. It is useful and cost-effective in relation to the evaluation of issues concerning roadway design, and technological systems that influence road-user behaviour and vehicle performance. For reasons related to modelling fidelity and data quality, simulation has seldom been used for traffic safety estimation. Simulation model development is however, undergoing rapid development and the area of ‘safety-simulation’ and is recognised as having a high potential in the field of transport planning and traffic engineering. As part of the work in this thesis, practical simulation experiments were carried out to investigate this potential, and identify limitations. Based on the data from one of the earlier studies, and knowledge regarding important safety-influencing factors and behavioural processes, one of the simulation experiments showed evidence to suggest that realistic safety critical events could be generated and measured using safety indicators in a simulation environment, without making unnecessary and unrealistic behavioural assumptions. Furthermore, a second application of this methodology revealed the safety potential of a rear-end incident-reduction function used in standard vehicle actuated signalling. While both of these simulation studies highlighted the potential of this type of approach, the need for more flexible and realistic models of interactive behavioural processes could be identified in addition to the general need for greater active research into the field of safety simulation. / QC 20100830

Successful dam design endeavor involves generating technical solutions that can meet intended functional objectives and choosing the best one among the alternative technical solutions. The process of choosing the best among the alternative technical solutions depends on evaluation of design conformance with technical specifications and reliability standards (such as capacity, environmental, safety, social, political etc pecifications). The process also involves evaluation on whether an optimal balance is set between safety and economy. The process of evaluating alternative design solutions requires generating a quantitative expression for lifetime performance and safety. An objective and numerical evaluation of lifetime performance and safety of dams is an essential but complex undertaking. Its domain involves much uncertainty (uncertainty in loads, hazards, strength parameters, boundary conditions, models and dam failure consequences) all of which should be characterized. Arguably uncertainty models and risk analysis provide the most complete characterization of dam performance and safety issues. Risk is a combined measure of the probability and severity of an adverse effect (functional and/or structural failure), and is often estimated by the product of the probability of the adverse event occurring and the expected consequences. Thus, risk analysis requires (1) determination of failure probabilities. (2) probabilistic estimation of consequences. Nonetheless, there is no adequately demonstrated, satisfactorily comprehensive and precise method for explicit treatment and integration of all uncertainties in variables of dam design and risk analysis. Therefore, there is a need for evaluating existing uncertainty models for their applicability, to see knowledge and realization gaps, to drive or adopt new approaches and tools and to adequately demonstrate their practicability by using real life case studies. This is required not only for hopefully improving the performance and safety evaluation process accuracy but also for getting better acceptance of the probabilistic approaches by those who took deterministic design based research and engineering practices as their life time career. These problems have motivated the initiation of this research. In this research the following have been accomplished: (1) Identified various ways of analyzing and representing uncertainty in dam design parameters pertinent to three dominant dam failure causes (sliding, overtopping and seepage), and tested a suite of stochastic models capable of capturing design parameters uncertainty to better facilitate evaluation of failure probabilities; (2) Studied three classical stochastic models: Monte Carlo Simulation Method (MCSM), First Order Second Moment (FOSM) and Second Order Second Moment (SOSM), and applied them for modeling dam performance and for evaluating failure probabilities in line with the above mentioned dominant dam failure causes; (3) Presented an exact new for the purpose analytical method of transforming design parameters distributions to a distribution representing dam performance (Analytical Solution for finding Derived Distributions (ASDD) method). Laid out proves of its basic principles, prepared a generic implementation architecture and demonstrated its applicability for the three failure modes using a real life case study data; (4) Presented a multitude of tailor-made reliability equations and solution procedures that will enable the implementations of the above stochastic and analytical methods for failure probability evaluation; (5) Implemented the stochastic and analytical methods using real life data pertinent to the three failure mechanisms from Tendaho Dam, Ethiopia. Compared the performance of the various stochastic and analytical methods with each other and with the classical deterministic design approach; and (6) Provided solution procedures, implementation architectures, and Mathematica 5.2, Crystal Ball 7 and spreadsheet based tools for doing the above mentioned analysis. The results indicate that: (1) The proposed approaches provide a valid set of procedures, internally consistent logic and produce more realistic solutions. Using the approaches engineers could design dams to meet a quantified level of performance (volume of failure) and could set a balance between safety and economy; (2) The research is assumed to bridge the gap between the available probability theories in one hand and the suffering distribution problems in dam safety evaluation on the other; (3) Out of the suite of stochastic approaches studied the ASDD method out perform the classical methods (MCSM, FOSM and SOSM methods) by its theoretical foundation, accuracy and reproducibility. However, when compared with deterministic approach, each of the stochastic approaches provides valid set of procedures, consistent logic and they gave more realistic solution. Nonetheless, it is good practice to compare results from the proposed probabilistic approaches; (4) The different tailor-made reliability equations and solution approaches followed are proved to work for stochastic safety evaluation of dams; and (5) The research drawn from some important conclusions and lessons, in relation to stochastic safety analysis of dams against the three dominant failure mechanisms, are. The end result of the study should provide dam engineers and decision makers with perspectives, methodologies, techniques and tools that help them better understand dam safety related issues and enable them to conduct quantitative safety analysis and thus make intelligent dam design, upgrading and rehabilitation decisions.

When project sites consist of substandard design elements according to standards set by the Federal Highway Administration (FHWA), design exceptions are implemented. The goal of this thesis is to analyze a sample set of 18 design exceptions taken from a total of 467 design exceptions approved in Georgia from 1995 – 2012. Crash data were obtained at the locations of each of these design exceptions three years before the let date and three years after the construction end date. To compensate for causal factors other than the design exception on the roadway, similar information from a range of control sites were also obtained. These control sites consisted of projects without design exceptions that occurred within the same time constraints as the design exception projects, were of the same work type, and were either located on the same route or within the same district. The potential safety impacts of the design exceptions were evaluated by comparing the before and after crash rates of projects before and after crash rates at these control sites Based on these data, no statistically significant relationship between the existence of a design exception and crash rates was identified. The sample set in this study was too small and the number of crashes found at both projects with design exceptions and control sites without design exceptions was too low to perform a significant Empirical Bayesian (EB) analysis. When additional data is available, an EB before and after analysis is recommended to compensate for any potential regression to the mean bias.

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