Term of Award
Spring 2017
Degree Name
Master of Science in Applied Engineering (M.S.A.E.)
Document Type and Release Option
Thesis (restricted to Georgia Southern)
Copyright Statement / License for Reuse
This work is licensed under a Creative Commons Attribution 4.0 License.
Department
Department of Mechanical Engineering
Committee Chair
Valentin Soloiu
Committee Member 1
Biswanath Samanta
Committee Member 2
Rocio Alba-Flores
Abstract
Intelligent Vehicles (IVs) present an emerging sector of automotive technology development. This study explores a specific subset of IV control logic known as path following. Complex environments, such as roadway intersections, present a significant challenge to autonomous navigation, due to the many non-standard permutations. This research sought to quantify the accuracy with which an IV could follow a set path, through a complex environment, without the aid of environmental sensors. This required the vehicle to utilize only onboard telemetry sensors to determine its relative global location in free space, and subsequently execute a move through it. The results validated the hypothesis, that an IV could follow a path, as described, with reasonable accuracy, for short distances. The vehicle navigated a 1:4.5 scale version of a complex intersection in Statesboro, GA, while maintaining effective lane tracking through four permutations of turns from the main avenue. This was accomplished by using a reverse kinematic telemetry sensor fusion approach, which leveraged the relative strengths and weaknesses of real-time processing, inertial measurement, and individual wheel speed.
Recommended Citation
Beyerl, Thomas A., "Intelligent Vehicle Complex Environment Path Following Capabilities, Based on a Telemetry Sensor Fusion Approach, Utilizing Open Loop Navigation" (2017). Electronic Theses and Dissertations. 1556.
https://digitalcommons.georgiasouthern.edu/etd/1556
Research Data and Supplementary Material
No
