Perceived Annoyance in Multi-source Electric Vehicle AVAS Environments

Abstract

The increasing usage of electric vehicles in urban environments has resulted in a widespread presence of AVAS sounds. While individual vehicle sound design and testing is a common approach, real-world traffic scenarios often involve the simultaneous presence of multiple vehicles. Their combined presence may lead to changes in perception, compared to when they are presented individually, specifically regarding annoyance. The work addresses annoyance perception in scenarios involving multiple electric vehicle AVAS sounds. It changes the traditional isolated source-based view into a scene-based one by investigating the combined presence of multiple vehicle sounds as they are experienced in realistic traffic environments. Binaural listening tests were conducted using recorded electric vehicle pass-by sounds. The stimuli presented different traffic scenarios, including single and multiple-vehicles. Selected stimuli were spatially arranged to simulate vehicles approaching from opposite directions. After each stimulus, participants rated their perceived annoyance, enabling a comparison of annoyance responses between isolated and multiple AVAS sound scenarios. The test investigated how different levels of overlapping AVAS sounds affect perceived annoyance when multiple electric vehicles are passing by.