Date of Award

12-2023

Degree Name

Doctor of Philosophy

Department

Mechanical and Aerospace Engineering

First Advisor

Zachary D. Asher, Ph.D.

Second Advisor

Richard Meyer, Ph.D.

Third Advisor

Guan Yue Hong, Ph.D.

Fourth Advisor

Damon Miller, Ph.D.

Keywords

Autnomous vehicles, energy efficient, perception, sensor technology

Abstract

The majority of states have passed legislation or have signed an executive order enacting safe testing, development, and deployment of level 4 and level 5 autonomous vehicles (AVs) in accordance with SAE standard J3016, which has led to an increase in the frequency of AV testing. The major driving force behind the push for AVs on public roads appears to be the increases the number of AVs on the road to decrease the chances of fatalities from distracted drivers. There are reports of disengagement from companies, which are required to report them to operate within California. The continuance of disengagements from AV companies within California show that there is a need for further research and development to advance AV technology. This study focuses on development and evaluation of sensor technology for an AV perception subsystem. This was accomplished by addressing three separate research questions with various focuses to identify (1) instrumentation for AV applications focusing on development of a low-cost energy-efficient research platform (2) develop and evaluate high-accuracy, low-computational sensor fusion algorithms for a perception subsystem (3) and develop and evaluate the feasibility of passive infrastructure sensors for efficient AV operations. The first study provides a better understanding of how AV technology works and what is necessary for safe AV operation. The second study explores a novel algorithm for reducing the amount of detection from radar and LiDAR to improve computational efficiency in the perception subsystem. Finally, the third study purposes how a retroreflector can be used for a passive-infrastructure sensor which has the capability to detect lane lines using radar to detect lane markers. This collection of studies demonstrate AV sensor technology and perception subsystems can improve the AV operation and energy efficiency.

Access Setting

Dissertation-Open Access

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