This project is part of the Global Formula Racing Team (GFR) which is a collaboration between students at OSU and students at DHBW-Ravensburg in Germany. GFR competes in Formula SAE competitions in the US and Europe. The GFR team has designed and is building 2 electric cars this year, both able to convert to autonomous form.

Mapping, localization, and boundary estimation is part of the autonomous sub-team of GFR. Our groups purpose is to help design and improve software that will win the driverless competitions this summer. To do this, the car must be able to navigate a course without any prior knowledge, identify the cones marking the track and estimate its own location. Then use these to create boundaries and plan a path between them.

Last year was the team's first year designing driverless software, unfortunately they were not ready to race in the driverless competitions by the end of the year. This year our team's job is to fix the bugs left from last year's implementation and update the algorithms to improve performance. We would have competed the car in California, Germany, and Spain this summer but these have been canceled due to COVID-19.

For any questions or access to the code base, contact any of us with the emails listed at the bottom of this page.

Autonomous driving has become an increasingly talked about topic in the world of technology in the past few years making this project especially relevant to the general public and the automotive industry. Since this specific implementation of a driverless car is scoped to a single car on a marked race course there are not as many ethical concerns present as a driverless car on the road with human drivers. Irregardless, safety was a primary concern when developing this driverless system, even for a race car on a closed course. Ensuring that the system produced accurate estimations of the environment and vehicle location is key to this in addition to correctly identifying track boundaries.

Although there was nothing groundbreaking about the driverless system developed we hope that in addition to helping the team succeed at competition our work can help to expose more people to how these systems work. Hopefully this will provide people a solid base of understanding when dealing with technology like this in the future whether it be an engineering career or as a consumer.