An environmentally adaptive warning sound system for electric vehicles

Kournoutos, Nikolaos and Cheer, Jordan (2019) An environmentally adaptive warning sound system for electric vehicles. In INTER-NOISE 2019: 48th International Congress and Exhibition on Noise Control Engineering.

Abstract

Electric vehicles are quiet at low speeds compared to their internal combustion engine counterparts, leading to regulations on the mandatory use of artificial warning sounds for their detection, as a safety measure for other road users. Arguments against the concept have been voiced focusing on the resulting environmental noise pollution, while at the same time some of the practical implementations have been shown to be somewhat ineffective when tested in an urban environment. To satisfy the need to both minimise noise pollution and ensure that the warning sound is sufficiently audible within any noise environment, an environmentally adaptive warning sound system is conceptualised and investigated. The system employs an adaptation algorithm that estimates the auditory masking thresholds due to a potentially changing sonic environment, and uses this information to adapt the warning sound not only in level, but also in spectral content. The system aims to render the vehicle detectable in both quiet and noisy environments without unnecessarily increasing its overall sound output level, therefore limiting noise pollution. The effectiveness of the adaptation algorithm is tested and evaluated for different auditory filter models and equalisation strategies in a variety of environmental noise scenarios.

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Contributors

Author: Jordan Cheer

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