Data to Improve Automotive Transportation

My project took a case-study approach towards employing data from past accidents and vehicle traffic volume and external entities to improve safety, reliability, sustainability, and the overall consumer experience and safety during travel. It focused on data from Southeast Michigan to use logistic regression to predict harmful accidents. This identified which accident factors caused injuries or fatalities instead of just property damage. It then gave multiple recommendations to improve safety, both from research done on future smart vehicles and more imminent needs based on recent trends before vehicles with more automation are available at scale.