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Thesis (Ph. D.)--Aerospace Engineering, Georgia Institute of Technology, 2005. / Amy R. Pritchett, Committee Member ; Moore, Mark D., Committee Member ; Wilhite, Alan, Committee Member ; Schrage, Daniel P., Committee Chair ; Mavris, Dimitri N., Committee Co-Chair ; DeLaurentis, Daniel A., Committee Member. Vita. Includes bibliographical references.

Thesis (Ph. D.)--Georgia Institute of Technology, 2005. / Also available online from the website Georgia Institute of Technology (http://etd.gatech.edu/). Vita. Includes bibliographical references (p. 271-280).

The transportation system is particularly vulnerable to disruptive events, while at the same time it is the primary sector for preparedness management and mitigation. The objective of this research is to quantify the changes in vehicle movement during non-recurrent events (Hurricane Irma 2017, Hurricane Michael 2018, and the COVID-19 pandemic in 2020) by comparing with recurrent period for different categories of vehicles, with an emphasis on freight vehicles. This research sought to identify where and when different classes of vehicles were traveling leading up to hurricane landfall and post-storm re-entry. Moreover, this study aims to understand the impact of the pandemic based on different decision made by government and how this decision was affected by the changes in the daily number of cases. The most significant findings showed that the transportation system is very exposed to disruptive events and needs considerable time to recover and adapt. In addition, it was found that freight vehicle transport experience significant changes after the evacuation and the last phases of the pandemic. The less impacted vehicles are those who belong to vehicle category 9 . This category did not have many days with significant changes. On the other hand, the most affected categories were vehicles in category 5 for evacuations and vehicles in categories 5 and 8 for the pandemic. These findings indicate the vehicle category is a parameter that should be taken into consideration in various emergency event management. The guidance of each vehicle group should have a unique design in order to increase management success by the competent authorities. / Includes bibliography. / Thesis (MS)--Florida Atlantic University, 2021. / FAU Electronic Theses and Dissertations Collection

Numerous local incidents occur on road networks daily many of which may lead to congestion and safety hazards. If vehicles can be provided with information about such incidents or traffic conditions in advance, the quality of driving in terms of time, distance, and safety can be improved significantly. Vehicular Ad Hoc Networks (VANETs) have recently emerged as an effective tool for improving road safety through the propagation of warning messages among the vehicles in the network about potential obstacles on the road ahead. This research has presented an effective warning data dissemination scheme which deploys relay strategy and concept of Region of Interest (RoI). A warning data message is characterized as spatio-temporal, implying that both the location and the time of an incident must be considered. Factors such as the type of warning message, the layout of the road network, the traffic density and the capacity of alternative roads are influential in determining the RoI in which the warning message needs to be propagated. In the developed scheme, the type of warning message is taken into account for the determination of the RoI so that the more severe the incident, the wider the RoI. In the selection of the relay point, the border relay area in which the relay point is placed, is adapted to the traffic density so that the higher the traffic density , the narrower the relay area. Traffic statistics are used to calculate the RoI, which is then enclosed in the warning message so that the message is not retransmitted beyond the RoI. Also, the responsibility for retransmitting the message is assigned to the relay node. The data is then disseminated effectively so that vehicles in areas unrelated to the incident are not informed. The primary objective of this research is to provide better understanding of the dissemination of warning data in the context of a vehicular network with the ultimate goal of increasing the possibility of using VANETs for safety applications.

Numerous local incidents occur on road networks daily many of which may lead to congestion and safety hazards. If vehicles can be provided with information about such incidents or traffic conditions in advance, the quality of driving in terms of time, distance, and safety can be improved significantly. Vehicular Ad Hoc Networks (VANETs) have recently emerged as an effective tool for improving road safety through the propagation of warning messages among the vehicles in the network about potential obstacles on the road ahead. This research has presented an effective warning data dissemination scheme which deploys relay strategy and concept of Region of Interest (RoI). A warning data message is characterized as spatio-temporal, implying that both the location and the time of an incident must be considered. Factors such as the type of warning message, the layout of the road network, the traffic density and the capacity of alternative roads are influential in determining the RoI in which the warning message needs to be propagated. In the developed scheme, the type of warning message is taken into account for the determination of the RoI so that the more severe the incident, the wider the RoI. In the selection of the relay point, the border relay area in which the relay point is placed, is adapted to the traffic density so that the higher the traffic density , the narrower the relay area. Traffic statistics are used to calculate the RoI, which is then enclosed in the warning message so that the message is not retransmitted beyond the RoI. Also, the responsibility for retransmitting the message is assigned to the relay node. The data is then disseminated effectively so that vehicles in areas unrelated to the incident are not informed. The primary objective of this research is to provide better understanding of the dissemination of warning data in the context of a vehicular network with the ultimate goal of increasing the possibility of using VANETs for safety applications.

Our nation is faced with a shortfall in funding desired transportation improvement programs. Texas is one of many states currently at crisis level as it is faced with an estimated annual funding shortfall of about $7 billion dollars between projected needs and transportation fund availability. This is a result of increased vehicle miles traveled and significant population growth that has outpaced the state’s transportation fund availability. Not only is the Texas transportation system declining in quality, but it is rapidly falling behind in the quantity needed to maintain current quality of life. As the Texas Mobility Fund balance approaches zero, the state needs to look toward non-traditional financing mechanisms to address its revenue shortfall. This report examines the problems associated with increased transportation demands in Texas and financing the expansion and maintenance of the state’s transportation system. / text

As important components of intelligent transportation system, lane detection and tracking (LDT) and lane departure warning (LDW) systems have attracted great interest from the computer vision community over the past few years. Conversely, lane markings recognition (LMR) systems received surprisingly little attention. This thesis proposed a real-time lane assisting framework for intelligent vehicles, which consists of a comprehensive module and simplified module. To the best of our knowledge, this is the first parallel architecture that considers not only lane detection and tracking, but also lane marking recognition and departure warning. A lightweight version of the Hough transform, PPHT is used for both modules to detect lines. After detection stage, for the comprehensive module, a novel refinement scheme consisting of angle threshold and segment linking (ATSL) and trapezoidal refinement method (TRM) takes shape and texture information into account, which significantly improves the LDT performance. Also based on TRM, colour and edge informations are used to recognize lane marking colors (white and yellow) and shapes (solid and dashed). In the simplified module, refined MSER blobs dramatically simplifies the preprocessing and refinement stage, and enables the simplified module performs well on lane detection and tracking. Several experiments are conducted in highway and urban roads in Ottawa. The detection rate of the LDT system in comprehensive module average 95.9% and exceed 89.3% in poor conditions, while the recognition rate depends on the quality of lane paint and achieves an average accuracy of 93.1%. The simplified module has an average detection rate of 92.7% and exceeds 84.9% in poor conditions. Except the conventional experimental methods, a novel point cluster evaluation and pdf analysis method have been proposed to evaluate the performance of LDT systems, in terms of the stability, accuracy and similarity to Gaussian distribution.

The problem of this study was to evaluate the quality of service and the adequacy of financial support by the State of the Texas public school transportation system and to indicate what improvements, if any, are needed in order to met ideal standards.

The emergence of Vehicular Ad-hoc Networks (VANETs) in the past decade has added a level of complexity to the modelling of Intelligent Transportation System (ITS) applications. In this paper, the Vehicular Network Integrated Simulator (VNetIntSim) is introduced as a new transportation network and VANET simulation tool by integrating transportation and VANET modelling. Specifically, it integrates the OPNET software, a communication network simulator, and the INTEGRATION software, a microscopic traffic simulation software. The INTEGRATION software simulates the movement of travellers and vehicles, while the OPNET software models the data exchange through the communication system. Information is exchanged between the two simulators as needed. The paper describes the implementation and the operation details of the VNetIntSim as well as the features it supports such as multiclass support and vehicle reuse. Subsequently, VNetIntSim is used to quantify the impact of mobility parameters (vehicular traffic stream speed and density) on the communication system performance considering Transmission Control Protocol (TCP) and User Datagram Protocol (UDP) applications. Specifically, the routing performance (packet drops and route discovery time), IP processing delay in case of a file transfer protocol (FTP) application, and jitter in case of a Voice over Internet Protocol (VoIP) application and evaluated.