In 2014, 32,675 deaths were recorded in vehicle crashes within the United States. Out of these, 51% of the fatalities occurred in rural highways compared to 49% in urban highways. No specific crash data are available for the built-up areas along rural highways. Due to high fatalities in rural highways, it is important to identify the factors that cause the vehicle crashes. The main objective of this study is to determine the factors associated with severities of crashes that occurred in built-up areas along the rural highways of Nevada. Those factors could aid in making informed decisions while setting up speed zones in these built-up areas. Using descriptive statistics and binary logistic regression model, 337 crashes that occurred in 11 towns along the rural highways from 2002 to 2010 were analyzed. The results showed that more crashes occurred during favorable driving conditions, e.g., 87% crashes on dry roads and 70% crashes in clear weather. The binary logistic regression model showed that crashes occurred from midnight until 4 a.m. were 58.3% likely to be injury crashes rather than property damage only crashes, when other factors were kept at their mean values. Crashes on weekdays were three times more likely to be injury crashes than that occurred on weekends. When other factors were kept at their mean value, crashes involving motorcycles had an 80.2% probability of being injury crashes. Speeding was found to be 17 times more responsible for injury crashes than mechanical defects of the vehicle. As a result of this study, the Nevada Department of Transportation now can take various steps to improve public safety, including steps to reduce speeding and encourage the use of helmets for motorcycle riders.

Senior leaders in state government public sector agencies must manage employee performance to ensure quality services to the citizens they serve. Limited academic research exists to study the barriers that these leaders acknowledge as deterrents to managing employee performance. The purpose of this qualitative study was to understand the reasons that public sector leaders at the Ohio Department of Transportation (ODOT) were challenged to manage employee performance and explore the role of transformational leadership. The ODOT was selected for this research because two prior worker surveys conducted by the agency revealed that employee performance accountability was an issue of concern. Following the conceptual framework of transformational and full range leadership, the research question for this study examined the barriers that these leaders cited as deterrents to managing employee performance. Twelve leaders were interviewed using a 5-item, open-ended questionnaire. Data were analyzed using inductive coding techniques and examined against the full range leadership continuum. The results of the study revealed nine barriers that leaders cited as deterrents to managing employee performance. The most frequently occurring included subordinates' self-preservation interests, market pay disparity, employee low motivation levels, and ineffective leadership training. The study concluded the role of transformational leadership was minimal, as leaders identified mostly with transactional characteristics. These findings may assist public leaders to improve performance management outcomes and possibly increase the quality of services to citizens.

Fatigue and drowsy driving in the state of Utah has been a causal factor in thousands of crashes over the years and poses a serious threat to public safety. Consequently, the purpose of this research was to evaluate the impact of drowsy driving in the state, to identify locations where fatigue and drowsy driving may be contributing factors to current crashes, and to identify methods to help mitigate these crashes. A 3-year drowsy driving crash rate spanning the years 2002 – 2004 was used to determine which segments of Utah highway are most prone to drowsy driving crashes. Drowsy driving corridors were located on Interstates 15, 70, 80, and 84 as well as United States Routes 89 and 91. Furthermore, State Route 36 also had two drowsy driving corridors. In order to recommend appropriate drowsy driving countermeasures for the drowsy driving corridors, a review of the existing countermeasures was conducted. The existing countermeasures included cable median barrier, rumble strips, rest areas, and drowsy driving freeway signage. The freeway signage is used to alert drivers of the adverse effects of drowsy driving and was the basis for a before-after study as well as a public survey of drowsy driving along Interstate 80 west of Salt Lake City. The before-after study of the drowsy driving freeway signage concluded that the freeway signage has played a part in reducing the number of crashes by as much as 63 percent in the eastbound direction and by as much as 22 percent in the westbound direction. As indicated, a public survey was conducted at two rest areas to supplement the findings of the before-after analysis. Using the 405 completed surveys, 14 Chi-Square tests were conducted with five of the test yielding statistically significant results. Finally, recommendations were made for the 41 drowsy driving corridors resulting from the 3-year crash rate analysis. Drowsy driving countermeasures recommended include: additional shoulder and centerline rumble strips, cable median barrier, guardrail replacement, and drowsy driving highway signage. Drowsy driving countermeasures not yet implemented but which should be considered by the Utah Department of Transportation are transverse rumble strips, wider longitudinal pavement markings, in-lane pavement markings indicating “AVOID FATIGUE DRIVING,” minimizing edge drop off, flattening slopes in clear zones, and adding a modified rest area.

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The construction of state highway projects is bid out each year at approximately three billion dollars. Claims from contractors for additional compensation are common. This paper investigates the policies and procedures for handling claims and explores the False Claims Act case law and its implications for the Department of Transportation's contract administration.

There has been an increased push away from the traditional combustion-engine powered vehicle due to environmental, health, and political concerns. As a result, alternative methods of transportation such as electric vehicles (EVs) have gaining popularity in the market. However, the EVs are not penetrating the market as quickly as expected, due in part to a combination of range, charge anxiety, and their financial costs. EVs cannot travel far due to limited driving range and require longer charge times than combustion-engine powered vehicles to recharge. Coupled with a lacking infrastructure for charging, the feasibility of an all-electric transportation market is still not possible. We propose a novel system in which we study and characterize the feasibility of increasing the effective driving range of a battery electric vehicle by utilizing inductive charge transfer to create an ad-hoc charging network where vehicles can “share” charge with one another. The application of wireless charge transfer from vehicle-to-vehicle (V2V) is the first of its kind and does not require any changes to current metropolitan infrastructures. Through the use of computer networking and communications algorithms, we analyze real-world commuter and taxi data to determine the potential effectiveness of such a system. We propose a participation and incentive mechanism to encourage participation in this network that enables the system to be functional.To illustrate proof of principle for V2V charging at traffic lights, we simulate a simplified model in which vehicles only exchange charge at traffic lights without coordination with other vehicles. Using a greedy heuristic, vehicles only exchange charge if they happen to meet another vehicle that has charge to share. The heuristic is greedy since decisions are made at each iteration with longer optimality not being considered. We are able to demonstrate an increase in effective driving range of EVs using these simplistic assumptions. In this thesis, we develop and quantify a complete simulation framework, which allows EVs to operate using charge sharing. We analyze data from the United States Department of Transportation, New York City Taxi and Limousine Commission, and Regional New York City data sources to understand the cumulative driving distance distributions for passenger/commuter vehicles and taxicabs in large metropolitan areas such as New York City. We show that the driving distributions can best be represented as heavy-tail distribution functions with most commuter vehicles not requiring additional charge during a typical day’s usage of their vehicle as compared to taxicabs, which regularly travel more than 100 miles during a 12-hour shift. We develop and parameterize several variables for input into our simulation framework including driving distance, charge exchange heuristics, models for determining pricing of charge units, traffic density, and geographic location. The inclusion of these parameters helps to build a framework that can be utilized for any metropolitan area to determine the feasibility of EVs. We have performed extensive evaluation of our model using real data. Our current simulations indicate that we can increase the effective distance that an electric vehicle travels by a factor of at least 2.5. This increased driving range makes EVs a more feasible mode of transportation for fleet vehicles such as taxicabs that rely heavily on commuting long cumulative distances. We have identified areas for future improvement to add further parameters to make the model even more sensitive. Finally, we focus on the application of our charge sharing framework in a real-world application for utilizing this methodology for the New York City bus system. In partnership with the New York City MTA, we launched a feasibility study of converting the currently majority hybrid bus fleet into a complete electric bus fleet with charging available at bus stops during scheduled bus stops. Unlike the earlier charge sharing framework, this simulation focuses on discrete distances that are traveled by the bus before having an opportunity to charge at the next bus stop. In this scenario, a large source of variability is the amount of time that the bus is able to stop at a bus stop for charging since this is determined by the amount of time needed to successfully embark and disembark the passengers at the given bus stop. This particular variability impacts how much charge the bus is able to gain during any given stop. We conclude with a list of opportunities for future work in expanding the model with additional parameters and conclusions of our work. Further, we identify areas of further research that outline the potential positive and negative outcomes from a charge sharing system that can be extended to various other applications including micro-mobility applications such as electric scooters and bicycles.

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The VCOST budgeting tool uses a drive cycle simulator to improve fuel economy predictions for vehicle fleets. This drive cycle simulator needs to predict the efficiency of various components of the vehicle's powertrain including any differentials. Existing differential efficiency models either lack accuracy over the operating conditions considered or require too great an investment. A fundamental model for differential efficiency is a cost-effective solution for predicting the odd behaviors unique to a differential. The differential efficiency model itself combines the torque balance equation and the Navier-Stokes equations with models for gear pair, bearing, and seal efficiencies under a set of appropriate assumptions. Comparison of the model with existing data has shown that observable trends in differential efficiency are reproducible in some cases to within 10% of the accepted efficiency value over a range of torques and speeds that represents the operating conditions of the differential. Though the model is generally an improvement over existing curve fits, the potential exists for further improvement to the accuracy of the model. When the model performs correctly, it represents an immense savings over collecting data with comparable accuracy. / text