Psychoacoustic assessment of synthetic sounds for electric vehicles in a virtual reality experiment

2025-10-29

AI Summary

The acoustic stealth of electric vehicles (EVs) poses pedestrian safety risks, while externally synthesized warning sounds may exacerbate noise annoyance in urban environments. Method: This study proposes an external sound design method optimized via psychoacoustic metrics. A virtual reality audiovisual experiment evaluated detectability and annoyance (using the 11-point ICBEN scale) of pure-tone, intermittent, and composite signals across 15 urban noise scenarios, integrating psychoacoustic parameters—loudness, sharpness, and roughness—into predictive models. Contribution/Results: Psychoacoustic metrics significantly outperformed conventional A-weighted sound pressure level (LAeq) in predicting subjective annoyance. The proposed method achieves high detectability while substantially reducing perceived annoyance. Findings provide empirical evidence and a novel design paradigm for EV external sound standards that jointly ensure pedestrian safety and acoustic environmental compatibility.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Security and Privacy: Large-scale security measurements
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success

Abstract

The growing adoption of electric vehicles, known for their quieter operation compared to internal combustion engine vehicles, raises concerns about their detectability, particularly for vulnerable road users. To address this, regulations mandate the inclusion of exterior sound signals for electric vehicles, specifying minimum sound pressure levels at low speeds. These synthetic exterior sounds are often used in noisy urban environments, creating the challenge of enhancing detectability without introducing excessive noise annoyance. This study investigates the design of synthetic exterior sound signals that balance high noticeability with low annoyance. An audiovisual experiment with 14 participants was conducted using 15 virtual reality scenarios featuring a passing car. The scenarios included various sound signals, such as pure, intermittent, and complex tones at different frequencies. Two baseline cases, a diesel engine and only tyre noise, were also tested. Participants rated sounds for annoyance, noticeability, and informativeness using 11-point ICBEN scales. The findings highlight how psychoacoustic sound quality metrics predict annoyance ratings better than conventional sound metrics, providing insight into optimising sound design for electric vehicles. By improving pedestrian safety while minimising noise pollution, this research supports the development of effective and user-friendly exterior sound standards for electric vehicles.

Problem

• Designing synthetic EV sounds balancing detectability and annoyance
• Assessing psychoacoustic metrics for better annoyance prediction
• Optimizing exterior sound signals for pedestrian safety

Innovation

• Psychoacoustic metrics predict EV sound annoyance better
• VR testing evaluates noticeability and annoyance balance
• Optimized synthetic sounds enhance safety without noise pollution