Development of an intuitive sound manipulation tool for in-vehicle human-machine interaction design

Abstract

Intuitive sounds such as auditory icons are known to be more efficient than abstract sounds (earcons) in conveying driver relevant information. Further, different traffic situations may be of different urgency levels and also related to the driver’s performance. Hence auditory information may have to be changed or manipulated in order to convey the appropriate level of urgency. However, very few authors address the problem of appropriately designing auditory icons and how they should be manipulated to convey different urgency levels. This thesis work has been conducted in order to develop a signal processing tool which could be used for such design and evaluation. The tool is designed to take different sensory data (as distance to a leading vehicle) as the input and use that data to manipulate a catalogue of sound signals. The goal of the thesis is to let these sound signals inform the driver about the current traffic situation with the right level of urgency.