Output from OpenCV vision prcessing

Trials

Inspiration

We're part of a team that builds an electric race car, but have trouble finding people that know what they're doing when they're behind the wheel of a race car. Using this app, we can teach people how to better drive on the racetrack.

What it does

Trials analyzes the driver's performance as they race around the track at blistering speeds. By looking at the past data of the driver, we are able to analyze where they are fastest on the track and where they have room for improvement. The drivers are then able to compare a specific lap against their best times at the track to increase their performance to the maximum!

How we built it

Toy RC Car from CVS

Lots of Python classes to track the car's position and performance

Flask app that allowed us to remotely control an Amazon Fire Phone. We took control of the camera and sent a video back to our computer for processing. A small web portal allows a user to define the sections of the track they want to analyze, and are provided with feedback about that specific section of the track.

Challenges we ran into

Trying to figure out the location of the car (and to do so accurately) was probably the biggest challenge of this Hackathon. It also took a very long amount of time to get Flask set up correctly to interface with the phone and the browser.

What's next for Trials

We hope to actually use this with our full size car once it's fully built. To determine location and acceleration, we plan on using GPS and an accelerometer, so the core of the program will be easily transferred.