Accurate Identification of Traffic Signs Using Radar and Camera Fusion

Abstract

Self-driving cars are no doubt the future of commuting for the world and it is paramount to make them as safe as possible on the road. The paper will cover a start to end process of making a system to easily collect data from the radar and camera and then using algorithms on the data collected to reduce anomalies and detect objects with better accuracy. Radar and camera both act as a data input for self-driving cars and are extremely important for the safety of both passengers and pedestrians, however, both of these sensors can be easily fooled. The advantage here is that what deceives one of the sensors doesn’t always mislead the other one, hence, using the suitable traits of each to overcome the deficiencies of the other will make them more robust and less susceptible to be fooled by such anomalies. By the end of this paper, the reader will have an in-depth understanding of how data is taken in, manipulated, and converted into results that power a self-driving car.