The focus of this research project is to develop the lane detection capabilities of Zeus, the self driving car at aUToronto. As a member of the Perception Team at aUToronto I work to meet the milestone goals set by my team leads and the advising professors including but not limited to Prof. Angela Schoellig and Prof. Tim Barfoot from the University Of Toronto.
My task was to improve upon the results of Zeus, whose current lane detection system runs on the GSCNN, a powerful network architecture created by the Toronto Nvidia AI Lab.
I am currently looking at whether PINet or the Ultra Fast Lane Detection networks can be integrated into the existing system with good results. Additionally, I am also exploring the potential for post processing pipelines, initializing sensor information and other methods which adjust/improve classifiers can be used to improve the performance of the car.
Code to be shared here once I get approval about what can and can't be made open source. Since we are currently still competing with our car in the SAE Autodrive Challenge, this may take some time. Thanks for understanding!