What began as a newfound interest in Formula 1 this summer has turned into the inspiration for my latest independent research project. After spending the summer following races and becoming an enthusiastic Mercedes fan, I found myself increasingly fascinated not only by the competition, but also by the engineering that makes it possible. From split-second strategic decisions to the enormous amounts of data collected during a race, Formula 1 offered an interesting intersection of technology, performance, and human decision-making.
As an Electrical and Computer Engineering Junior, I began wondering how I could connect this interest with my academic background. In a sport where cars can exceed 200 miles per hour, even the smallest mistake can have serious consequences. While Formula 1 has made tremendous advances in safety, I was interested in exploring whether artificial intelligence could help identify dangerous situations before they occur.
That question became the foundation of my ECE 398 independent research project, which investigates whether machine learning can recognize warning signs in the moments leading up to an on-track incident. By examining information such as vehicle speed, braking, acceleration, and positioning, I hope to explore how technology might provide earlier warnings in situations where every second matters.