Nowadays, technologies of autonomous driving are very high-developed, but it is still not enough for fully safety usage on the public roads, almost in the cities. In this case it is very important to have more additional active and passive safety systems. And one of this systems is “car hearing”. An autonomous vehicle must have at least similar characteristics as a human driver, including perceptional skills like vision for object recognition and human control capabilities for driving. Most of the drivers can also hear, and it is a very important source of information for understanding the environment around the car.

First of all it is very important to recognize and localize different kinds of emergency sounds, such as ambulance or fireworks siren, hard breaking and human‘s shout in emergency cases. Second is passive dangers, such as overtaking car or motorcycle and car which is coming from behind.

Master Thesis: Sound localization system for autonomous driving

In this topic we are going to develop a sound localization system which must be able to localize and track the sound source using the data from 8 microphones installed on the top of the car. For example it is very important to localize ambulance siren, human‘s shout or hard braking sound in emergency cases.


  • The design, development and implementation of sound localization algorithms.


  • Strong programming skills (Python), ROS

Proseminar Topics

  • Sound filtering and separation for sound processing

  • TOA-based sound localization algorithms

  • Neural networks types for sound processing

  • Volume-based sound localization algorithms

Running projects

Camera to microphone calibration for sound processing

Master Thesis. May – November 2019

Sound Recognition for autonomous driving

Master Thesis. May – November 2019

zurück zur Übersicht der am Fachgebiet angebotenen Arbeiten