電気自動車の警告音が歩行者に聞こえにくいことを示す研究（Electric cars and their warning signals difficult to locate at low speed）

2025-06-19

2025-06-18 チャルマース工科大学

As electric cars become more common, vulnerable road users are encountering more and more warning signals from them. Now, new research from Chalmers University of Technology in Sweden, shows that one of the most common signal types is very difficult for humans to locate, especially when multiple similar vehicles are in motion simultaneously.

チャルマース工科大学の研究で、電気自動車（EV）の低速時の警告音は、歩行者にとって音の方向を特定しにくいことが明らかになった。被験者が警告音の発信源を特定する実験では、多くが誤った方向を示した。特にEV特有の静音性と警告音の周波数特性が要因とされる。この問題は視覚障がい者などにとって深刻なリスクとなり、安全な音響設計の必要性が示された。研究成果は『Journal of the Acoustical Society of America』に掲載。

＜関連情報＞

複数の定置型電気自動車の聴覚的定位
Auditory localization of multiple stationary electric vehicles

Leon Müller;Jens Forssén;Wolfgang Kropp
The Journal of the Acoustical Society of America Published:March 24 2025
DOI:https://doi.org/10.1121/10.0036248

Current regulations require electric vehicles to be equipped with acoustic vehicle alerting systems (AVAS), radiating artificial warning sounds at low driving speeds. The requirements for these sounds are based on human subject studies, primarily estimating detection time for single vehicles. This paper presents a listening experiment assessing the accuracy and time of localization using a concealed array of 24 loudspeakers. Static single- and multiple-vehicle scenarios were compared using combustion engine noise, a two-tone AVAS, a multi-tone AVAS, and a narrowband noise AVAS. The results of 52 participants show a significant effect of the sound type on localization accuracy and time for all evaluated scenarios (⁠ <?XML:NAMESPACE PREFIX = “[default] http://www.w3.org/1998/Math/MathML” NS = “http://www.w3.org/1998/Math/MathML” />p<0.001⁠). Post-hoc tests revealed that the two-tone AVAS is localized significantly worse than the other signals, especially when simultaneously presenting two or three vehicles with the same type of sound. The multi-tone and noise AVAS are generally on par but localized worse than combustion noise for multi-vehicle scenarios. For multiple vehicles, the percentage of failed localizations drastically increased for all three AVAS signals, with the two-tone AVAS performing worst. These results indicate that signals typically performing well in a single-vehicle detection task are not necessarily easy to localize, especially not in multi-vehicle scenarios.