Date of Award

1-2022

Document Type

Thesis

Degree Name

Master of Science (MS)

College/School

College of Science and Mathematics

Department/Program

Computer Science

Thesis Sponsor/Dissertation Chair/Project Chair

Weitian Wang

Committee Member

Michelle Zhu

Committee Member

Jiayin Wang

Abstract

Autonomous vehicles (AVs) are a key component in the creation of the new transportation infrastructure. Over the last several decades, nations across the world have experienced an increase in traffic congestion, environmental deprecation due to greenhouse gas emissions and an increase in time loss and productivity. A key factor in these components is the increase in numbers of vehicles on the road, a number that continues to increase gradually every year. In addition, the continued increase in vehicles on the road poses a threat to human and environmental safety. There is strong evidence to support that accidental vehicular deaths and injuries are highly correlated to driver impairment, further supporting the need to address human errors and the "human problem" in the existing transportation model.

Autonomous vehicles provide opportunities to mitigate the inefficiencies of the current transportation model by aiding, and in future cases, removing human agents as well as possibly reducing the number of vehicles on the road. Both enterprises and governmental entities have begun the process of exploring the various ways that they can benefit from adapting autonomous vehicles. As of today, several companies have autonomous driving fleets in US cities making promising strides towards a driverless future. The Victoria Transport Policy Institute estimates that the integration of AVs should occur within the next three decades, with a peak in public acceptance in the 2040s to 2060s.

This thesis explores the current state of development of AVs integration in a political, technological, and social context. It explores the potential benefits and challenges of self-driving vehicles, the typical construction of autonomous vehicles, and the typical safety features integrated in every AV. This thesis also provides an informative approach to developing an educational 1/10th-scale autonomous vehicle with three of the most important features: PID-based collision avoidance features, a lane-tracking system, and a stop sign recognition feature. The quantitative and qualitative results of the implementation of the 1/10th-scale AV are verified and analyzed, and a plan of future improvements is presented.

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