Abstract
My technical and STS research topics both address the general sociotechnical problem that technological innovation can have destabilizing economic effects, specifically transportation technology. Despite benefits to efficiency and quality of life, unneeded workers can face unemployment, labor protests can cause unrest in daily life, the supply chain can break down to limit availability of products, and industry leaders profit, leading to increased economic disparity. Engineers and companies have a responsibility to ensure that innovative technology is implemented responsibly, in a way that improves the welfare of society and mitigates negative consequences. My technical research relates to this problem by developing a technology which further enables vehicle automation. Specifically, torque vectoring lends itself to being controlled by AI, as humans don’t have the processing power to manage it. My STS paper directly addresses the problem of vehicle automation by trying to determine how the introduction of automation into the trucking industry can be least disruptive.
The problem for my technical paper was to design the motor to wheel transmission for the UVA Motorsports formula electric vehicle, to accommodate a single motor driving each wheel independently. The goal was to optimize weight, cost, and efficiency, while satisfying volume and interface constraints. This problem is important because torque vectoring, proactively sending different amounts of torque to each wheel, enables higher performance driving and aggressive turns and can make routine driving safer. The group researched what design choices others made for similar vehicles and also received advice from many UVA Mechanical Engineering experts. The team brainstormed and screened several design options using the scoring approach taught in ME Design. After deciding on a rough design, the team wrote software to optimize several gear design parameters based on stresses and assembly size. Some decisions, such as material, tolerances, bearing type, and lubricant, were made based on research and industry standards. Less deterministic features such as the form of the casing, planet gear carrier, and fasteners/connectors, were chosen using past transmission design experience of UVA motorsports members, and verified using ME equations or FEA analysis. Ultimately a compound planetary gearbox was chosen for the transmission design and was manufactured successfully within tolerances. Specific tests were performed for most specifications, and all of these were passed, verifying a satisfactory design.
The problem for my STS research paper was that the development of AI-driven trucks is threatening to disrupt the U.S. trucking industry through trucker unemployment and social unrest. This problem is particularly important because of how central trucking is to the U.S. economy. To determine whether the industry needs to prepare and how, multiple methods were employed. A review of current driving technology was conducted to show that the AI-driven trucking transition is likely enough to warrant preparation. Autonomous trucking research, trucking companies, and relevant infrastructure were analyzed to argue for the industry’s flexibility to change. Solutions were determined through analysis of past automation in the automotive and stevedoring industries. It was found that the trucking industry will likely experience many negative effects from automation, and there are several specific organizational/infrastructural/policy changes that can be made now to minimize negative effects.
Through the analysis in my technical and STS research papers I have been successful in contributing to the solution of the general sociotechnical problem: automation leading to destabilizing economic effects. My technical research developed a technology that enables further vehicle automation. This has helped to increase understanding of the processes that go into creation of such technologies, which is a key preliminary step for sociologists and engineers looking to safeguard from economic harm. My STS research has increased the understanding of negative consequences for vehicle automation as well as solutions to address them. By demonstrating the experience with designing an automating technology and findings for how automation in the trucking industry can be implemented smoothly, my research will help ensure that similar technology benefits society in the future. Future researchers should explore types of automation other than vehicles to expand our knowledge of destabilizing innovation, and our tools for managing it.
First, I would like to thank my capstone group members, Cooper Berggren, Ryley Butler, Tim Genz, Devin Power, Andrew Smith, and Riley Van Aken. Their experiences and insight into transmission design/manufacturing have ensured that our technical project was a success. I would also like to thank the ME professors who have advised us throughout the design process, Peter Griffiths and Michael Momot. Finally, I would like to thank my STS advisor, Caitlin Wylie, for her exceptional guidance on STS analysis and research.
