Working with data from self-driving cars

I spent the summer after sophomore year (2018) working for Optimus Ride, Inc in Boston, MA. I developed a graphical tool for analyzing LIDAR calibration data using Python, matplotlib, and PyQt. I also assisted in the refinement of their LIDAR calibration procedures.

Takeaways

While I was extremely excited going into the internship, it didn’t turn out to be a great experience for a number of reasons. Firstly, I didn’t provide enough time for self-care and rejuvenation away from the hubbub of the city (biking from through downtown Boston twice a day and then retreating to a small apartment with three other people doesn’t exactly recharge the soul). I also lost enthusiasm for the concept of self-driving cars in general. While I’d initially hoped they could enable more environmentally sustainable transportation modes, the more I learned, the more I realized the impacts of self-driving cars would more likely be negative than positive. The project I worked on was also a bit of a long shot. Nobody knew if my work would actually turn up something interesting (but if it did, it would have been immensely helpful).

Despite my lackluster experience, I still believe Optimus Ride as a company is a great place for many. I wish the company the best as it tries to make transportation more accessible. (And as far as self-driving car companies go, I think their application–first-to-last-mile transportation–is about as green as you can get.)