At the moment the most significant risk that could jeopardize the success of the project is the accuracy of our object detection algorithms. We do not want to tell a blind person to cross the road when they are not supposed to. We are currently looking into options to mitigate this risk, one option may be to reduce the scope of the project to just doing crosswalk detection or cross sign detection to allow us to focus more time to one the algorithms and to hopefully make it better. We should also focus on the rate being less than 1%, a metric we were thinking of would probably be 0.5% for the detection of whichever application we pick, and if we pusue both as well. The design of the system has been unchanged, however we are looking into how to get the false positive rate as close to 0% as possible.
Carnegie Mellon ECE Capstone, Fall 2022: Colin Hackwelder, Zachary Zhao