Harmonizing Safety Regulations and Perception: A Simulation Methodology for AVAS System Design ESI Group

Format:

Book

Conference/Event

Author/Creator:

Calloni, Massimiliano, author.

Contributor:

Hadjit, Rabah

Musser, Chad

Salvekar, Pinak

Conference Name:

13th International Styrian Noise, Vibration & Harshness Congress: The European Automotive Noise Conference (2024-06-19 : Graz, Austria)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2024

Summary:

The development of an effective Acoustic Vehicle Alerting System (AVAS) is not solely about adhering to safety regulations; it also involves crafting an auditory experience that aligns with the expectations of vulnerable road users. To achieve this, a deep understanding of the acoustic transfer function is essential, as it defines the relationship between the sound emitter (the speaker inside the vehicle) and the receiver (the vulnerable road user). Maintaining the constancy of this acoustic transfer function is paramount, as it ensures that the sound emitted by the vehicle aligns with the intended safety cues and brand identity that is defined by the car manufacturer. In this research paper, three distinct methodologies for calculating the acoustic transfer function are presented: the classical Boundary Element method, the H-Matrix BEM accelerated method, and the Ray Tracing method. Furthermore, the paper encompasses an assessment of the correlation between these methods and their impact on the overall simulation time when balanced against accuracy. The study not only focuses on the accuracy of these methodologies but also assesses their computational efficiency, a crucial aspect in real-world AVAS implementation. Additionally, the paper provides an illustrative example of a binaural listening experience at various certification positions within a simulated environment

Notes:

Vendor supplied data

Publisher Number:

2024-01-2915

Access Restriction:

Restricted for use by site license