Date of Award:
2017
Document Type:
Thesis
Degree Name:
Master of Science (MS)
Department:
Electrical and Computer Engineering
Advisor/Chair:
Rajnikant Sharma
Abstract
Autonomous driving is an area of increasing investment for researchers and auto manufacturers. Integration has already begun for self-driving cars in urban environments. An essential aspect of navigation in these areas is the ability to sense and follow lane markers. This thesis focuses on the development of a vision-based control platform using lane detection to control a full-sized electric vehicle with only a monocular camera. An open-source, integrated solution is presented for automation of a stock vehicle. Aspects of reverse engineering, system identification, and low-level control of the vehicle are discussed. This work also details methods for lane detection and the design of a non-linear vision-based control strategy.
Checksum
e80d205860d6347599eebdb3052d88e9
Recommended Citation
Kunz, N. Chase, "Vision-Based Control of a Full-Size Car by Lane Detection" (2017). All Graduate Theses and Dissertations. 6534.
https://digitalcommons.usu.edu/etd/6534
Included in
Copyright for this work is retained by the student. If you have any questions regarding the inclusion of this work in the Digital Commons, please email us at .