The implementation of high-speed passenger trains (HST) within existing highway right-of-way (ROW) offers a solution for regions with a demand for the capacity and service offered by HST but lacking the support for sharing freight rail ROW or acquiring new ROW corridors. The states of Florida, Colorado, California and Nevada propose to use highway ROW for their HST projects to increase the capacity of the corridor, prevent or minimize impacts and prevent disruption of freight rail operations. Despite the constraints of using existing highway ROW, such as speed-limiting degrees of curvature and safety concerns, solutions and mitigation measures exist. The purpose of this thesis is to present the HST projects in the United States proposing use of highway ROW, the potential benefits and engineering issues to consider and the feasibility of using the existing I-35 ROW in Texas for HST. / text

Thesis (M.S.)--University of Michigan, 1960.

Thesis (M.S.)--University of Michigan, 1960.

This thesis describes high-speed railway system in Spain. At the first part it concerns on the history of high-speed rails in the world, its legislation and the contribution of EU. The second part concentrates on the evolution in Spain, high speed infrastructure and trains. Mainly it analyzes the price policy.

This thesis describes the position of rail transport in Spain and focuses mainly on the current development of high-speed rail transport. Attention is paid to the AVE system, which is operated by the newly built infrastructure, but also to the other high-speed trains to run on conventional lines with Iberian gauge. The aim is to highlight the progress achieved in this area, capture a network built and planned high-speed lines, the transition to neighboring states and the process of integration of Spain into the Trans-European transport networks. In analyzing the tariff policy, the paper deals with basic and preferential tariffs applied by Renfe Operadora in the sphere of high-speed long-distance passenger trains.

A model that can be used to analyze both current and future high-speed rail corridors is presented in this work. This model has been integrated into the Transportation Systems Analysis Model (TSAM). The TSAM is a model used to predict travel demand between any two locations in the United States, at the county level. The purpose of this work is to develop tools that will create the necessary input data for TSAM, and to update the model to incorporate passenger rail as a viable mode of transportation. This work develops a train dynamics model that can be used to calculate the travel time and energy consumption of multiple high-speed train types while traveling between stations. The work also explores multiple options to determine the best method of improving the calibration and implementation of the model in TSAM. For the mode choice model, a standard C logit model is used to calibrate the mode choice model. The utility equation for the logit model uses the decision variables of travel time and travel cost for each mode. A modified utility equation is explored; the travel time is broken into an in-vehicle and out-of-vehicle time in an attempt to improve the model, however the test determines that there is no benefit to the modification. In addition to the C-logit model, a Box-Cox transformation is applied to both variables in the utility equation. This transformation removes some of the linear assumptions of the logit model and thus improves the performance of the model. The calibration results are implemented in TSAM, where both existing and projected high-speed train corridors are modeled. The projected corridors use the planned alignment for modeling. The TSAM model is executed for the cases of existing train network and projected corridors. The model results show the sensitivity of travel demand by modeling the future corridors with varying travel speeds and travel costs. The TSAM model shows the mode shift that occurs because of the introduction of high-speed rail. / Master of Science

Changes in climate caused by changes in anthropogenic (i.e. "man-made") greenhouse gas (GHG) emissions have become a major public policy issue in countries all over the world. With an estimated 28.4% of these emissions attributed to the transportation sector, attention is being focused on strategies aimed at reducing transportation GHG emissions. Quantifying the change in GHG emissions due to such strategies is one of the most challenging aspects of integrating GHG emissions and climate change into transportation planning and policy analysis; the inventory techniques and methods for estimating the impact of different strategies and policies are still relatively unsophisticated. This research developed a method for estimating intercity passenger transportation energy and carbon footprints and applied this method to three US DOT-designated high speed rail (HSR) corridors in the U.S.-- San Francisco/Los Angeles/San Diego; Seattle/Portland/Eugene, and Philadelphia/Harrisburg/Pittsburg. The methodology consists of estimating the number of trips by mode, estimating the direct CO₂ emissions, and estimating indirect CO₂ emissions. For each study corridor the impacts of different strategies and policies on carbon dioxide emissions were estimated as an illustration of the policy application of the developed methodology. The largest gain in CO₂ savings can be achieved by strategies aiming at automobile emissions, due to its sizeable share as main mode and access/egress mode to and from airports and bus and train stations: an average fuel economy of 35.5 mpg would result in a 38-42% savings of total CO₂ emissions; replacing 25% of gasoline use with cellulosic ethanol can have a positive impact on CO₂ emissions of about 13.4-14.5%; and a 10% market share for electric vehicles would result in potential CO₂ savings of 3.4-7.8%. The impact of a 20% or 35% improvement in aircraft efficiency on CO₂ savings is much lower (0.88-3.65%) than the potential impacts of the policies targeting automobile emissions. Three HSR options were analyzed using Volpe's long-distance demand model: HSR125, HSR150, and HSR200. Only the HSR150 and HSR200 would result in CO₂ savings, and then just for two of the three corridors: the Pacific Northwest (1.5%) and California (0.8-0.9%). With increased frequency and load factors, a HSR150 system could result in CO₂ savings of 5.2% and 1.8% for the Pacific Northwest and California, respectively. This would require a mode shift from auto of 5-6%. This shift in auto mode share would mainly have to be a result of pricing strategies. From these results, HSR may not be such an obvious choice, however, with increased ridership and diversions from other modes, CO₂ savings increase significantly due to the lower emissions per passenger mile for HSR. The framework developed in this study has the ability to determine the GHG emissions for such HSR options and increased diversions.

published_or_final_version / Politics and Public Administration / Master / Master of Public Administration

The objective of this research is to develop and demonstrate low-complexity, robust, frequency-scalable, wide-band waveform acquisition techniques for testing high speed com- munication systems. High resolution waveform capture is a versatile testing tool that enables flexible test strategies. However, waveform capture at high data rates requires costly hardware because the increased bandwidth of the signal waveform leads to an increase in the sampling rate requirement, cost of front-end components, and sensitivity to phase errors in traditional (source) synchronous Nyquist-rate tester architectures. The hardware cost and complexity of wide-band waveform acquisition systems can, however, be significantly reduced by using (trigger-free) incoherent undersampling to achieve reduced sampling rates and robustness to phase errors in signal paths. Reducing the hardware cost of such a system using incoherent undersampling requires increased signal processing at the back end. This research proposes computationally-efficient, time-domain waveform reconstruction algorithms to improve both performance, and scope of existing incoherent undersampling- based test instrumentation. Supporting hardware architectures are developed to extend the application of incoherent undersampling-based waveform acquisition techniques to linearity testing of high-speed radio-frequency components without any synchronization between the signals involved, and to the acquisition of wide-band signals beyond the track-and-hold bandwidth barrier of the traditional incoherent undersampling architectures, using multi-channel bandwidth interleaving. The bandwidth is extended in a source-incoherent framework by using mixers to down convert high-frequency signal components to base band followed by digitization using undersampling, and back-end signal processing to reconstruct the original wide-band signal from multiple band-pass components.

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