Date of Award:
5-2017
Document Type:
Thesis
Degree Name:
Master of Science (MS)
Department:
Electrical and Computer Engineering
Committee
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
b0fe0e8a4b2b480e56678002fb6bfe15
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
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