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The simulation tools that are used to model vehicle systems have not been advancing as quickly as the growth of research and technology surrounding the advancements of vehicle technology itself. A topological vehicle systems modelling package would use Modelica to take advantage of the flexibility and modularity of the language, the inherent multi-domain workspace and analytical accuracy of model equations. This package is defined through the use of SuperBlocks, a generalized model that allows the user to select and parameterize the appropriate sub-system directly within the workspace. This palette of SuperBlocks would be implemented within MapleSim6 to create MapleCar. This provides a customized balance between speed and accuracy after taking advantage of advanced graph-theoretic solutions methods used in MapleSim. MapleCar provides several advantages to a user over conventional tools. The SuperBlocks would ease the required steps to model a full vehicle system by providing clear, simple connections to quickly get a simulation assembled. Next, each SuperBlock is represented by a model that contains a replaceable model, a Modelica function which allows its internal model to be changed through a user-friendly parameter selection. The combination of sub-systems accessible directly through a parameter allows a variety of vehicle systems to be easily assembled, as well as provide a container for future models to be shared and published. A short demonstration of connecting these vehicle SuperBlocks from the MapleCar package is provided using MapleSim6. The generalized vehicle component palette provides a straight-forward, customizable drag-and-drop interface to assist in generating vehicle models for simulation. Conclusions and recommendations are provided at the end.

Thesis (M.S.)--Ohio University, June, 1985. / Title from PDF t.p.

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1992. / Vita. Abstract. Includes bibliographical references (leaves 137-140). Also available via the Internet.

Thesis (Ph. D.)--University of Hong Kong, 1999. / Includes bibliographical references.

Thesis (M.S.)--West Virginia University, 1999. / Title from document title page. Document formatted into pages; contains xiv, 429 p. : ill. (some col.). Vita. Includes abstract. Includes bibliographical references (p. 117-118).

Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2006. / Includes bibliographical references (leaves 78-80). Also available in electronic version.

M.Sc. (Mathematical Statistics) / This dissertation deals with the computation of nonlinear control strategies for an autonomous vehicle. The vehicle consists of two wheels attached to an axle. It is assumed that both wheels roll without slipping leading to nonholonomic constraints. A third order nonlinear kinematic model of the vehicle is derived from these constraints. It is further assumed that the vehicle has builtin feedback controllers independently regulating the rotational velocities of the wheels (using electric motors as actuators). Thus, the vehicle is maneuvered by applying a separate rotational velocity reference command to the feedback controller of each wheel. The closed loop system dynamics from the reference command to the wheel rotational velocity is approximately modelled by a first order system. This leads to a fifth order nonlinear state-space model for the vehicle. The above-mentioned reference commands constitute the control input variables of the vehicle model and are subject to amplitude constraints. Firstly, a methodology is developed for computing reference command strategies to drive the autonomous vehicle from a specified initial state to a desired final state in a given time and such that a circular obstacle is avoided. The vehicle performs the required maneuver whilst satisfying all the specifications and constraints. Secondly, feedback reference command laws are developed such that a specified point just ahead of the vehicle asymptotically tracks a given reference trajectory in the horizontal plane. The feedback control law steers the vehicle onto the reference path from any initial position and keeps it moving on the path. Thirdly, the stochastic system performance is evaluated when the above-mentioned tracking control strategy is applied and the initial state of the vehicle is a random vector.

Modern cell phone hardware, due to its integrated peripherals, provides a low cost intelligent controller for use in the navigation of an Automated Guided Vehicle (AGV). Most commercial AGV’s use proprietary hardware which is expensive to replace and also difficult to maintain. Using industrial hardware components combined with Android mobile platforms could provide a low-cost alternative. This would be easier to maintain, using existing in-house factory maintenance knowledge. A prototype AGV was designed and developed based on an integrated system between an industrial Programmable Logic Controller (PLC) and an Android operating system mobile platform. This system utilises the mobile platforms integrated Global Position System (GPS) or video camera as tools for navigation. Experimental tests were performed to determine whether the prototype can navigate a predefined course by making use of GPS and camera line following algorithms. The accuracy of the line following algorithm was influenced by the speed at which the research AGV moved. Mounting the Android camera higher above the ground improved the vision and therefore accuracy of the algorithm. The GPS algorithm successfully navigated to various waypoints. The accuracy of the implemented GPS unit on the Android device is its limitation. The research unit was only capable of reaching a waypoint consistently within a three-metre radius.