Safe and Sustainable Fleet Management with Data Analytics and Reinforcement Training / A Utilitarian Ethics Analysis of the 2016 Tesla Autopilot Crash

Ahmadiyar, Ryan, School of Engineering and Applied Science, University of Virginia
Park, B. Brian, EN-Eng Sys and Environment, University of Virginia
Laugelli, Benjamin, EN-Engineering and Society, University of Virginia

My technical work and my STS research are primarily connected through the idea of improvement to current road transportation systems and the ethical implications these improvements could pose. Both of my projects discuss current driving habits and limitations, and offer potential solutions and improvements. However, my works differ in their approaches to improving the consumer transportation system. My research project explores self-driving vehicles and a complete overhaul to the current understanding of driving. My technical work focuses on smaller scale, human driving habits and offers various techniques and training to improve the current ability of drivers to ensure safety and sustainability. Although these topics are rather different, both projects still operate with the theme of improved driving systems at their respective cores.
My technical work focuses on improving safety and sustainability measures in UVA’s Facilities Management (FM) fleet. My capstone team created different training materials to target specific driving safety and sustainability metrics, such as seat belt usage and idling time. By analyzing telematic tracking data, we were able to formulate a better understanding of how and why drivers commit safety infractions and created more positive ways of addressing the issues in order to correct them. The overall goal of the project was to improve the FM fleet’s safety scores and create a safer, more sustainable grounds. We hope this project can provide the groundwork to continue scaling the project to other university fleets and beyond.
My STS research centers around utilitarian ideals, specifically in relation to self-driving cars. The development process of autonomous vehicles is currently discombobulated and under heavy public scrutiny. My research discusses how the current process violates utilitarianism and how the competitive nature of the technology industry causes a lack of proper safety development. The goal of the research is to highlight issues with technological development through the lens of the autonomous vehicle industry. Engineering design should prioritize functionality and safety over speed to market.
Working on both of these projects simultaneously added great value to each of them. I believe understanding the nature of human drivers and their mistakes can provide great value to the development of autonomous vehicle algorithms. Creating a better understanding of current driving systems can help develop new driving systems, such as autonomous vehicles. Prioritizing safety and sustainability not only leads to an improved society, but will also improve the product itself. Working on both of these projects simultaneously allowed me to understand where we are now and the direction we are going in as the driving landscape evolves.

BS (Bachelor of Science)

School of Engineering and Applied Science
Bachelor of Science in Systems Engineering
Technical Advisor: B. Brain Park
STS Advisor: Benjamin Laugelli
Technical Team Members: Jenny Chun, Caroline Fuccella, Damir Hrnjez, Grace Parzych, Benjamin Weisel

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