Optimization of the Sound of Electric Vehicles According to Unpleasantness and Detectability

Abstract

Electric Vehicles (EVs) are very quite at low speed, which can be hazardous for pedestrians. It is necessary to add warning sounds but this can represent an annoyance if they are poorly designed. On the other hand, they can be not enough detectable because of the masking effect due to the background noise. In this paper, we propose a method for the design of EV sounds that takes into account in the same time detectability and unpleasantness. It is based on user tests and implements Interactive Genetic Algorithms (IGA) for the optimization of the sounds. Synthesized EV sounds, based on additive synthesis and filtering, are proposed to a set of participants during a hearing test. An experimental protocol is proposed for the assessment of the detectability and the unpleasantness of the EV sounds. After the convergence of the method, sounds obtained with the IGA are compared to different sound design proposals. Results show that the quality of the sounds designed by the IGA method is significantly higher than the design proposals, validating the relevance of the approach.

An interactive bi-objective optimisation process to guide the design of electric vehicle warning sounds

“…In Petiot, Legeay & Lagrange (2019), a study using an IGA for the design of QV sounds was presented. After a definition of the experimental protocol for the listening tests and the sound synthesis technique, a mono-objective optimisation using IGA was implemented, to explore the trade-off between detectability and unpleasantness, which were aggregated as a weighted sum.…”

A genetic approach for the interactive design of sounds: Application to electric vehicles

“…Subtle perceptual phenomenon can then be taken into account for the optimization of products involving sensory constraints (Wakefield et al, 2005). A study using IGA for the design of sounds for Electric Vehicles can be found in (Petiot, Legeay & Lagrange, 2019), where an exploration of the tradeoff between detectability and unpleasantness of the sounds is proposed, showing the efficiency of the approach. The present chapter is in the continuity of this work.…”

Extracting Design Recommendations From Interactive Genetic Algorithm Experiments: Application to the Design of Sounds for Electric Vehicles

“…All these studies are based on hearing tests of a predefined set of sound stimuli. In a previous paper (Petiot et al, 2019), we proposed a method based on an Interactive Genetic Algorithm (IGA) for the design of EV sounds that takes into account in the same time detectability and unpleasantness. Based on listening tests and a parametric synthesis of EV sounds, it provided efficient solutions, validating the relevance of the approach.…”

“…The objective of this section is to make a summary of the EV sounds synthesis method, the scenario for the assessment of the detectability and the unpleasantness, and the IGA implementation. For more information, the reader is invited to read the initial paper (Petiot et al, 2019).…”