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An environmentally adaptive warning sound system for electric vehicles

An environmentally adaptive warning sound system for electric vehicles
An environmentally adaptive warning sound system for electric vehicles
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.
Electric vehicle, noise pollution, Pedestrian safety
Kournoutos, Nikolaos
4caca7a8-e970-4875-a36d-bbb2d6155819
Cheer, Jordan
8e452f50-4c7d-4d4e-913a-34015e99b9dc
Kournoutos, Nikolaos
4caca7a8-e970-4875-a36d-bbb2d6155819
Cheer, Jordan
8e452f50-4c7d-4d4e-913a-34015e99b9dc

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.

Record type: Conference or Workshop Item (Paper)

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.

Full text not available from this repository.

More information

Accepted/In Press date: 25 February 2019
Published date: 16 June 2019
Keywords: Electric vehicle, noise pollution, Pedestrian safety

Identifiers

Local EPrints ID: 432014
URI: http://eprints.soton.ac.uk/id/eprint/432014
PURE UUID: 5530caa5-cb06-4266-a82e-932074d60070
ORCID for Jordan Cheer: ORCID iD orcid.org/0000-0002-0552-5506

Catalogue record

Date deposited: 26 Jun 2019 16:30
Last modified: 17 Jan 2020 17:34

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