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Evaluating At-Grade Rail Crossing Safety along the Knowledge Corridor in MassachusettsHoran, Timothy P 01 January 2013 (has links) (PDF)
Highway-rail grade crossings are safer than ever, but collisions between motor vehicles and trains persist. Some collisions could be prevented by actively maintaining such grade crossings, yet many at-grade rail crossings are only evaluated following collisions. Those crossings that experience no collisions may go decades without being inspected. In recent years, the Congress has allocated funds for a national High-Speed Intercity Passenger Rail program, and it is in the public’s interest for state road/highway agencies to inspect all highway-rail crossings in high-speed rail corridors to ensure that the warning systems in place are commensurate with the crossings’ needs. The objectives of this research are to a) determine the adequacy of traffic control devices at highway-rail grade crossings along the restored Vermonter tracks in Massachusetts; and b) to recommend crossings for closure and/or grade separation if it is determined that the traffic control devices are inadequate at an intersection. The major findings of this paper are that a majority of the at-grade rail crossings need some improvements to be in compliance with MUTCD standards. Additionally, four at-grade crossings are identified for closure, grade-separation, and/or additional traffic control devices beyond MUTCD standards.
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Development of a Decision Support Tool for Planning Rail Systems: An Implementation in TSAMJoshi, Chetan 16 February 2006 (has links)
A Decision Support model for planning Intercity Railways is presented in this research. The main aim of the model is to generate inputs for the logit model existing in the Virginia Tech Transportation Systems Analysis Model (TSAM). The inputs required by the TSAM logit model are travel time, travel cost and schedule delay. Travel times and travel costs for different rail technologies are calculated using a rail network and actual or proposed rail schedules. The concept of relational databases is used in the development of the network topology. Further, an event graph approach is used for analysis of the generated network. Shortest travel times and their corresponding travel costs between origin-destination pairs are found using Floyd's algorithm. Complete itineraries including transfers (if involved) are intrinsically held in the precedence matrix generated after running the algorithm. A standard mapping technique is used to obtain the actual routes. The algorithms developed, have been implemented in MATLAB. Schedules from the North American Passenger rail system AMTRAK are used to generate the sample network for this study. The model developed allows the user to evaluate what-if scenarios for various route frequencies and rail technologies such as Accelerail, High Speed Rail and Maglev. The user also has the option of modifying route information. Comparison of travel time values for the mentioned technology types in different corridors revealed that frequency of service has a greater impact on the total travel time in shorter distance corridors, whereas technology/line-haul speed has a greater influence on the total travel time in the longer distance corridors. This tool could be useful to make preliminary assessments of future rail systems. The network topology generated by the algorithm can further be used for network flow assignment, especially time-dependent assignment if used with dynamic graph algorithms. / Master of Science
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Development of a High-Speed Rail Model to Study Current and Future High-Speed Rail Corridors in the United StatesVandyke, Alex J. 20 July 2011 (has links)
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
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Forecasting Model for High-Speed Rail in the United StatesRamesh Chirania, Saloni 08 November 2012 (has links)
A tool to model both current rail and future high-speed rail (HSR) corridors has been presented in this work. The model is designed as an addition to the existing TSAM (Transportation System Analysis Model) capabilities of modeling commercial airline and automobile demand. TSAM is a nationwide county to county multimodal demand forecasting tool based on the classical four step process. A variation of the Box-Cox logit model is proposed to best capture the characteristic behavior of rail demand in US. The utility equation uses travel time and travel cost as the decision variables for each model. Additionally, a mode specific geographic constant is applied to the rail mode to model the North-East Corridor (NEC). NEC is of peculiar interest in modeling, as it accounts for most of the rail ridership. The coefficients are computed using Genetic Algorithms. A one county to one station assignment is employed for the station choice model. Modifications are made to the station choice model to replicate choices affected by the ease of access via driving and mass transit. The functions for time and cost inputs for the rail system were developed from the AMTRAK website. These changes and calibration coefficients are incorporated in TSAM. The TSAM model is executed for the present and future years and the predictions are discussed. Sensitivity analysis for cost and speed of the predicted HSR is shown. The model shows the market shift for different modes with the introduction of HSR. Limited data presents the most critical hindrance in improving the model further. The current validation process incorporates essential assumptions and approximations for transfer rates, short trip percentages, and access and egress distances. The challenges for the model posed by limited data are discussed in the model. / Master of Science
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