Thesis (Ph. D.)--University of California, Los Angeles, 1977. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 300-308).

Thesis (M.S.)--Ohio State University, 1986. / Includes bibliographical references (leaves 183-184). Available online via OhioLINK's ETD Center.

The management of large-scale transportation infrastructure is becoming a very complex task for the urban areas of this century which are covering bigger geographic spaces and facing the inclusion of connected and self-controlled vehicles. This new system paradigm can leverage many forms of sensing and interaction, including a high-scale mobile sensing approach. To obtain a high penetration sensing system on urban areas more practical and scalable platforms are needed, combined with estimation algorithms suitable to the computational capabilities of these platforms. The purpose of this work was to develop a transportation framework that is able to handle different kinds of sensing data (e.g., connected vehicles, loop detectors) and optimize the traffic state on a defined traffic network. The framework estimates the traffic on road networks modeled by a family of Lighthill-Whitham-Richards equations. Based on an equivalent formulation of the problem using a Hamilton-Jacobi equation and using a semi-analytic formula, I will show that the model constraints resulting from the Hamilton-Jacobi equation are linear, albeit with unknown integer variables. This general framework solve exactly a variety of problems arising in transportation networks: traffic estimation, traffic control (including robust control), cybersecurity and sensor fault detection, or privacy analysis of users in probe-based traffic monitoring systems. This framework is very flexible, fast, and yields exact results. The recent advances in sensors (GPS, inertial measurement units) and microprocessors enable the development low-cost dedicated devices for traffic sensing in cities, 5 which are highly scalable, providing a feasible solution to cover large urban areas. However, one of the main problems to address is the privacy of the users of the transportation system, the framework presented here is a viable option to guarantee the privacy of the users by design.

The main objective of this research is to develop a model to predict congestion. This model is developed using the techniques of simulation and as the model requires dynamic modeling, DYNAMO is used. This model incorporates the three-regime linear model for establishing a relationship between speed and density of the traffic stream. The input to this model is obtained from a presence type detector system. These measurements are then used to calculate various parameters and then the state of the traffic flow for the vehicular stream in the test zone is determined. This model also predicts the state of the traffic stream in any other section of the highway behind the test section. The model developed is flexible and easy to incorporate in any traffic control system. This research is also intended to simulate the various traffic stream models and evaluate their performance regarding their capability to represent highway traffic flow conditions. A thorough review of the fundamentals of traffic flow is required to achieve these objectives. The simulation models developed for these traffic stream formulae incorporate various measures of effectiveness to determine congestion. These measures of effectiveness are used to define congestion. The study of the various traffic stream models is necessary in order to develop a flexible and efficient model to predict congestion. The congestion prediction model developed incorporates all the parameters required to define congestion. / Master of Science

Macroscopic fundamental diagram is the concept of the highest importance in traffic flow theory used for development of network-wide control strategies. Previous studies showed that so called Arterial Fundamental Diagrams (AFDs) properly depict relationships between major macroscopic traffic variables on urban arterials. Most of these studies used detector’s occupancy as a surrogate measure to represent traffic density. Nevertheless, detector’s occupancy is not very often present in the field data. More frequently, field data from arterial streets provide performance metrics measured at the stop lines of traffic signals, which represent a hybrid of flow and occupancy. When such performance measures are used in lieu of density, the outcomes of the relationships between macroscopic fundamental variables can be confusing. This study investigates appropriateness of using degree of saturation, as a representative surrogate measure of traffic density, obtained from an adaptive traffic control system that utilizes stop-line detectors, for development of AFDs. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection

published_or_final_version / Economics and Finance / Master / Master of Economics

Transportation engineering has taken upon a new role; to empower the alternative modes of travel: walking, biking, and bus transit. In this new era, engineers are rethinking a network designed predominately for the automobile. The ultimate goal of this research is to create a process that can make a vehicle dominant corridor a desirable, livable thoroughfare by livability design and context sensitive performance measures. Balancing travel modes requires an account of vehicular traffic and the impact of reconfiguring existing conditions. The analysis herein is conducted by field data collection, transportation equations and microsimulation. Simulating traffic behavior will be the means to apply livable alternatives comparable to existing Southeast Florida conditions. The results herein have shown that micro-simulation can be utilized in transportation planning to reveal good livability alternatives. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2015 / FAU Electronic Theses and Dissertations Collection

Nowadays it is very hard to find available spots in public parking lots and even harder at facilities such as universities and sports venues. A system that provides drivers with parking availability and parking lot occupancy will allow users find a parking space much easier and faster. This thesis presents a system for automatic parking lot occupancy computation using motion tracking. The use of computer vision techniques and low cost video sensors makes it possible to have an accurate system that allows drivers to find a parking spot. Video bitrate and quality reduction and its impact on performance were studied. It was concluded that high quality video is not necessary for the proposed algorithm to obtain accurate results. The results show that relatively inexpensive and low bandwidth networks can be used to develop large scale parking occupancy applications. / by Francisco Alberto Justo Torres. / Thesis (M.S.C.S.)--Florida Atlantic University, 2013. / Includes bibliography. / Mode of access: World Wide Web. / System requirements: Adobe Reader.

Thesis. 1977. M.S.--Massachusetts Institute of Technology. Dept. of Civil Engineering. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Bibliography: leaf 121. / by Serge Tsygalnitzky. / M.S.

Thesis. 1978. M.S.--Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND AERONAUTICS. / Includes bibliographical references. / M.S.