There’s a lot of data here in PAVE, ranging from image data for neural networks to CAN data about every electrical system in the vehicle (like throttle pedal position, steering torque, steering wheel position, engine RPM, etc.) 

So, we’ll be doing some experimental research to uncover as much information about the car as possible. For example, we can use cross-correlation to determine when to prioritize certain sensors, time-series analysis to uncover which CAN ids do what (since Ford won’t tell us), etc.

Additionally, we’ll be doing a ton of data visualization. So if that’s what you’re interested in, get pumped!No prior experience necessary!

Languages: Python or R or any language you’re comfortable with

Sub Team Leader: Chris Hay ’17