Localization of Traffic Objects using Acoustic Data
Hearing is a crucial sense for our daily life. We are communicating by sound, classify situations and even locate objects by their sound emissions.
A typical scenario for sound source localization is traffic. Pedestrians may `hear´ the direction of an incoming vehicle, even though they are watching the other way. Locating vehicles by sound is pretty important, so the U.S. Department of Transportation National Highway Traffic Savety Administration proposed a rule for minimum sound requirements for electric vehicles. Therefore, information provided by sound may be also valuable for drivers assistance systems and autonomous vehicles.
In this thesis, a method, which utilizes acoustic data, for the determination of the directions of traffic objects is introduced and analysed. This method bases on the Multiple Signal Classification (MUSIC) algorithm and should determine the direction of all types of traffic sound.