Thesis (M.Eng.Sc.) - University of Queensland, 2003. / Includes bibliography.

Thesis (M.S.)--University of Missouri-Columbia, 2004. / Typescript. Includes bibliographical references (leaves 128-130). Also available on the Internet.

Thesis (M.S.)--University of Florida, 2001. / Title from title page of source document. Document formatted into pages; contains x, 85 p.; also contains graphics. Includes vita. Includes bibliographical references.

Thesis (M.S.)--University of Missouri-Columbia, 2004. / Typescript. Includes bibliographical references (leaves 128-130). Also available on the Internet.

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1994. / Vita. Abstract. Includes bibliographical references (leaves 107-112). Also available via the Internet.

In this work we reproduce driving techniques to mimic expert race drivers and obtain the open-loop control signals that may be used by auto-pilot agents driving autonomous ground wheeled vehicles. Race drivers operate their vehicles at the limits of the acceleration envelope. An accurate characterization of the acceleration capacity of the vehicle is required. Understanding and reproduction of such complex maneuvers also require a physics-based mathematical description of the vehicle dynamics. While most of the modeling issues of ground-vehicles/automobiles are already well established in the literature, lack of understanding of the physics associated with friction generation results in ad-hoc approaches to tire friction modeling. In this work we revisit this aspect of the overall vehicle modeling and develop a tire friction model that provides physical interpretation of the tire forces. The new model is free of those singularities at low vehicle speed and wheel angular rate that are inherent in the widely used empirical static models. In addition, the dynamic nature of the tire model proposed herein allows the study of dynamic effects such as transients and hysteresis. The trajectory-planning problem for an autonomous ground wheeled vehicle is formulated in an optimal control framework aiming to minimize the time of travel and maximize the use of the available acceleration capacity. The first approach to solve the optimal control problem is using numerical techniques. Numerical optimization allows incorporation of a vehicle model of high fidelity and generates realistic solutions. Such an optimization scheme provides an ideal platform to study the limit operation of the vehicle, which would not be possible via straightforward simulation. In this work we emphasize the importance of online applicability of the proposed methodologies. This underlines the need for optimal solutions that require little computational cost and are able to incorporate real, unpredictable environments. A semi-analytic methodology is developed to generate the optimal velocity profile for minimum time travel along a prescribed path. The semi-analytic nature ensures minimal computational cost while a receding horizon implementation allows application of the methodology in uncertain environments. Extensions to increase fidelity of the vehicle model are finally provided.

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references. Available also from Dissertation Abstracts.

Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 189-197). Available also in a digital version from Dissertation Abstracts.

Thesis (M.A.)--University of Hong Kong, 2001. / Includes bibliographical references (leaf 62).

No description available.