Auditory Perception in Open-Source Driving Simulator CARLA

This paper presents a proof of concept for integrating real-time audio classification into autonomous vehicle systems using the open-source autonomous driving simulator, CARLA. With the increasing need for autonomous vehicles to operate safely in their environment, the addition of auditory signal perception (e.g., emergency sirens) can improve navigation in urban settings. Using support vector machines, we developed a binary classification model capable of identifying sirens within the simulated environment, allowing simulated autonomous vehicles to detect and respond to emergency signals. Using CARLA, our open source framework, we can synthesize realistic urban driving scenarios, collecting and processing audio data. Results demonstrate the potential of auditory perception systems in autonomous vehicle development, improving the vehicle's situational awareness and paving the way for further developments in audio-responsive autonomous driving technology. This research showcases the flexibility of CARLA for auditory simulation and highlights the potential of audio detection to improve autonomous vehicle safety and environmental awareness. To facilitate further research and development in this area, we have made our implementation open-source.