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This study evaluates the dynamic interaction between rail vehicles and the track on which they travel. The measurements were analyzed in the time and frequency domain. The effects of external parameters such as the vehicle design, subgrade stiffness, and degree of curvature were analyzed and compared for both the vehicle response and the track geometry data. This study was conducted in close cooperation with the Transportation Technology Center, Inc. (TTCI) in Pueblo, Colorado. The track and vehicle response data was collected on the High Tonnage Loop at TTCI over a span of approximately ten years. For the purpose of this study, TTCI provided this data to the Advanced Vehicle Dynamics Laboratories (AVDL) at Virginia Tech. The analysis of the data was first completed for the vehicle response and track geometry measurements separately. In this manner, the effects of the subgrade stiffness, the degree of curvature, and the vehicle design could be evaluated for each of the measurements. The analysis of the track and rail vehicle response was successfully completed, and the results from this analysis are presented in the following chapters. The analysis showed that the subgrade stiffness had a significant effect on the vertical wheel loads, the track crosslevel, and the track gauge. For an increase in the degree of curvature, the variation of the crosslevel increased. The dynamic response of the vertical and lateral wheel loads showed a significant dependence on the alignment of the rails. Improvements for future studies of the interaction between the track and rail vehicles have been recommended. / Master of Science

Wavelet intensity based algorithm developed previously at VirginiaTech has been furthered and paired with an SVM based classifier. The wavelet intensity algorithm acts as a feature extraction algorithm. The wavelet transform is an effective tool as it allows one to narrow down upon the transient, high frequency events and is able to tell their exact location in time. According to prior work done in the field of signal processing, the local regularities of a signal can be estimated using a Lipchitz exponent at each time step of the signal. The local Lipchitz exponent can then be used to generate the wavelet intensity factor values. For each vertical acceleration value, corresponding to a specific location on the track, we now have a corresponding intensity factor. The intensity factor corresponds to break-no break information and can now be used as a feature to classify the vertical acceleration as a fault or no fault. Support Vector Machines (SVM) is used for this binary classification task. SVM is chosen as it is a well-studied topic with efficient implementations available. SVM instead of hard threshold of the data is expected to do a better job of classification without increasing the complexity of the system appreciably. / Master of Science

The ability of a Doppler LIDAR (Light Detection and Ranging) system to measure the speed of a moving rail vehicle in a non-contacting manner is extended to capture the lateral and vertical irregularities of the track itself and to evaluate the rail track quality. Using two pairs of lenses to capture speed signals from both rails individually, the track speed, curvature, and lateral and vertical geometry variations on each side are determined. LIDAR lenses are installed with a slight forward angle to generate velocity signals that contain two components: 1) the left and right track speeds, and 2) any lateral and/or vertical speed caused by track motion and/or spatial irregularities. The LIDAR system collects and outputs the track information in time domain. Separating each speed component (forward, vertical, and lateral) is possible due to the inherent separation of each phenomenon with respect to its spatial/temporal frequencies and related bandwidths. For the measurements to be beneficial in practice, the LIDAR data must be spatially located along the track. A data-mapping algorithm is then simultaneously developed to spatially match the LIDAR track geometry measurements with reference spatial data, accurately locating the measurements along the track and eliminating the need for a Global Positioning System (GPS). A laboratory-grade LIDAR system with four Doppler channels, developed at the Railway Technologies Laboratory (RTL) of Virginia Tech, is body-mounted and tested onboard a geometry measurement railcar. The test results indicate a close match between the LIDAR measurements and those made with existing sensors onboard the railcar. The field-testing conducted during this study indicates that LIDAR sensors could provide a reliable, non-contact track-monitoring instrument for field use, in various weather and track conditions, potentially in a semi-autonomous or autonomous manner. A length-based track quality index (TQI) is established to quantify the track geometry condition based on the geometry data collected by the LIDAR sensors. A phenomenological rail deterioration model is developed to predict the future degradation of geometry quality over the short track segments. The introduced LIDAR's TQI is considered as the condition-parameter, and an internal variable is assumed to govern the rail geometry degradation through a deterioration rule. The method includes the historical data, current track conditions collected by the LIDAR system, and traffic data to calculate the track deterioration condition and identify the geometry defects. In addition to rail geometry inspection, a LIDAR system can potentially be used to monitor the rail surface structure and integrity. This is possible due to the fact that the Doppler shift imposed on the laser radiation reflected from a moving surface has the Doppler bandwidth broadened in proportion to the height and width of the surface features. Two LIDAR-based rail surface measures are introduced based on LIDAR measurements to identify different rail surface conditions and materials. / Ph. D.

Rail vehicle dynamicists Frequently employ roller rigs to study the complex dynamic response of vehicles and trucks. This work presents the analytical and experimental investigation of a one-fifth scale model of a typical North American three-piece Freight truck running on a roller rig. The roller rig was built as part of this research For the Department of Mechanical Engineering at Virginia Polytechnic Institute and State University. Linear and nonlinear mathematical models were also developed to simulate the lateral dynamics of the truck running on the roller rig. The nonlinear model incorporates a lookup table For the wheel/rail geometric constraints, a heuristic creep force model to take into account creep force saturation, and it includes the effects of Coulomb friction in the truck bearings. The linear model predicts the truck's natural Frequency versus speed within 5% of the experimental values. lt also predicts the damping ratio decrease that occurs with increasing truck speed. The nonlinear model simulates the lateral instability known as hunting. The nonlinear model and the roller rig also exhibit small amplitude hunting, in which flange contact does not occur. The nonlinear model simulates the experimentally observed increase in oscillation Frequency that accompanies the onset of flange contact. / Master of Science

This thesis presents an inspection method based on RGB-D profiling for the rail industry. The proposed approach uses inexpensive RGB-D cameras to generate color and geometrical information of the observations, and stitches each consecutive scan from the sensor to form a map, provided that the two scans contain the information from the same observation. Using a technique known as pairwise registration, the errors between these consecutive scans are minimized using error minimization algorithms such as Iterative Closest Point and Normal Distributions Transform. Once the error between each consecutive scan is minimized, the scans are then converted into a global co-ordinate frame work to form a global map of all the added scans. The proposed approach could be used as a map-based identification technique by comparing the past global map to newly acquired scans while also reducing computation time effectively. The effectiveness of this approach is demonstrated by developing a system that uses multiple RGB-D cameras to detect railway defects such as spikes. The applicability of the proposed approach to other applications is then evaluated by profiling long lengths of road. / Master of Science

25 airports have a connection with the local rail transit system, but each is unique. Variables such as network size, train frequency, type of airport station, time, and cost vary by airport. Both airport passengers and planners should have a technical basis of selecting which system is the most useful, efficient, and reliable. To date, there have been no scoring procedures created to rank the airports in order of quality of connection. This thesis analyzes rail transit accessibility for all 25 airports (3 of which have 2 separate transit systems) by investigating 8 characteristics, 3 of which are market factors and 5 of which are system factors. The 5 system factors are travel time difference between car and train, transit cost difference between car and train, airport/transit connection type, network size, and train frequency. The 3 market factors are rail transit mode share, business traveler percentage, and low-cost carrier percentage. A scoring system was then developed and each airport's characteristics were inputted. The airports were scored using three different methods and were subsequently evaluated to understand why airports received the scores they did. This evaluation led to a better understanding of airport transit best practices. The scoring system was used again to evaluate an airport (Washington-Dulles) undergoing radical changes to understand by what factor a score can improve. A "top 10" list of airport transit connections was produced with JFK coming in first. This method is a starting point for developing a robust system to evaluate transit connections to airports. / Master of Science

The suburban landscape is a landscape of opportunity. Historically, the suburban landscape has been a desirable place for living. Because it demands the use of automobiles, it is also a landscape undesirable for pedestrians. Optimistically, through principles of New Urbanism, walkability, and mass transportation via light rail, there is an opportunity to transform the auto dominated suburban landscape into one that promotes walkability. Located in the suburbs of Alexandria, Virginia, an atypical intersection is analyzed for its characteristics of walkability. This intersection consists of several major roads converging to create a location overly dominated by busy roads and automobiles. Though there are accommodations that signify this intersection is also a place for pedestrians, a walkability checklist and a walkability study prove otherwise. The author investigates transforming this otherwise unwalkable landscape into one that promotes walkability by providing a safe, comfortable, and enjoyable experience for suburban pedestrians. Design intentions are focused on preserving much of the existing land use and not re-developing suburbia into a new urban center. Yet, through using new urbanist principles for walkability, there is the opportunity to create a new suburban center. / Master of Landscape Architecture

The accuracy of the results from a rail vehicle dynamic model is dependent on the realism of the track input to the model. An important part of the track input is the irregularities that exist on actual track. This study analyzes the irregularities inherent in railroad track geometry data, and provides an analytical method for creating track data with the irregularities for use as the input to a dynamic model. Track data, measured from various classes of track, was examined using statistical and frequency analysis techniques to identify any similarities in the characteristics of the irregularities. The results showed that each class of track had a distinctive value for the standard deviation of the alignment and profile data. It was also determined that the frequency content of all the tracks was contained within a common bandwidth. The track irregularities could then be generated with the same characteristics as an actual track. The method for creating the track irregularities was then programmed into TRAKVU. TRAKVU is a track preprocessor used in conjunction with NUCARS, a railcar dynamic modeling program¹. TRAKVU enables users to create track data and apply the appropriate irregularities so that the track will have the characteristics of the desired class of track. A validation was then performed to determine how well track created in TRAKVU simulated actual tracks. The statistical and frequency characteristics of created tracks were compared directly with actual tracks. Created track was also used as the input to a dynamic model. The predicted vehicle response was then compared to the actual vehicle response and the predicted vehicle response using measured track data as the input. The results from the validation showed that the created track performed as well as the measured track in providing the input to the model. Although the predicted response using the created track did not compare as well with the actual vehicle response, the differences could be attributed to inaccuracies in the model. ¹NUCARS and TRAKVU are copyrighted property of the Association of American Railroads. / Master of Science

No / Passenger rail overcrowding is fast becoming a problem in major cities worldwide. This problem therefore calls for efficient, cheap and prompt solutions and policies, which would in turn require accurate modelling tools to effectively forecast the impact of transit demand management policies. To do this, we developed an agent-based model of a particular passenger rail system using an activity based simulation approach to predict the impact of public transport demand management pricing strategies. Our agent population was created using a customer/passenger mobility survey dataset. We modelled the temporal flexibility of passengers, based on patterns observed in the departure and arrival behavior of real travelers. Our model was validated using real life passenger count data from the passenger rail transit company, after which we evaluated the use of peak demand management instruments such as ticketing fares strategies, to influence peak demand of a passenger rail transport system. Our results suggest that agent-based simulation is effective in predicting passenger behavior for a transportation system, and can be used in predicting the impact of demand management policies.