Auditory Scene Understanding for Autonomous Driving
Auditory Scene Understanding for Autonomous Driving
- New search for: Furletov, Yury
- New search for: Willert, Volker
- New search for: Adamy, Jurgen
- New search for: Furletov, Yury
- New search for: Willert, Volker
- New search for: Adamy, Jurgen
One necessary condition for autonomous driving is an accurate and reliable representation of the environment around the vehicle. Current architectures rely on cameras, radars, and lidars to capture the visual environment and to localize and track other traffic participants. Human drivers can see but also hear and use a lot of auditory information for understanding the environment in addition to visual cues. In this paper, we present a pure sound localization and recognition system to extract an auditory representation of the environment. First, the environmental sound is classified into seven main categories of traffic objects followed by six specific kinds of sirens in an emergency case using a simple neural network layout. Second, each object is localized via a combined time-delay of arrival and amplitude-based localization algorithm. The system is evaluated on real-world data focusing on a robust detection and accurate localization of emergency vehicles.
Document information
Auditory Scene Understanding for Autonomous Driving
2021-07-11
1897000 byte
Conference paper
Electronic Resource
English
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