The noise of motor vehicles is one of the most important problems as regards to pollution on main roads. However, this unpleasant characteristic could be used to determine vehicle speed by external observers. Building on this idea, the present study investigates the capabilities of a microphone array system to identify the position and velocity of a vehicle travelling on a previously established route. Such linear microphone array has been formed by a reduced number of microphones working at medium frequencies as compared to industrial microphone arrays built for location purposes, and operates with a processing algorithm that ultimately identifies the noise source location and reduces the error in velocity estimation.
Since motorcycles are one of the main sources of noise in urban environments, the use of electric powered two-wheelers may contribute to the improvement of soundscapes in Smart Cities. However, quiet vehicles can lead to an increased risk of accident for pedestrians and other drivers. In order to assess the noise generated by powered two-wheelers and their detectability, five different low capacity motorcycles were measured in a pass-by noise test. The measurements were performed at different speeds using a linear microphone array and a dummy head. The sound directivity radiated by the moving sources was studied with a microphone array. To establish the detectability of powered two-wheelers, thirty-seven subjects participated in an auditory test consisting on a virtual road-crossing scenario. The subjects had to detect the approaching of a vehicle at 20 km/h. The results showed a significant reduction in the sound pressure level emitted by electric motorcycles at low-speed, as well as a notable increase in sound directivity with velocity. The reaction time obtained for the detection of electric powered two-wheelers was higher compared to the traditional propulsion ones. The results highlighted the risk posed by this kind of electric vehicles for pedestrians.
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