Supplementary material for "Pedestrian crossing behaviour in front of electric vehicles emitting synthetic sounds: A virtual reality experiment"

DOI:10.4121/629cae37-76e7-4b14-8693-25c96a263b4b.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/629cae37-76e7-4b14-8693-25c96a263b4b

Datacite citation style

Bazilinskyy, Pavlo; Alam, Md Shadab; Merino-Martínez, Roberto (2025): Supplementary material for "Pedestrian crossing behaviour in front of electric vehicles emitting synthetic sounds: A virtual reality experiment". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/629cae37-76e7-4b14-8693-25c96a263b4b.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

The increasing adoption of electric vehicles (EVs), which operate more quietly than internal combustion engine vehicles, raises concerns about their detectability, particularly for visually impaired road users. Regulations mandate exterior sound signals for EVs, ensuring minimum sound pressure levels at low speeds. However, these signals are often used in already noisy urban environments, creating a challenge: enhancing detectability without adding excessive noise pollution. This study explores the use of synthetic exterior sounds that balance high noticeability with low annoyance. An audiovisual experiment was conducted with 20 participants in 15 virtual reality scenarios featuring an EV passing in front of them. Different sound signals, including pure, intermittent, and complex tones at varying frequencies, were tested alongside two baseline cases (a diesel engine and tyre noise alone, i.e., no synthetic sound added). Participants rated sounds for annoyance, noticeability, and informativeness using 11-point ICBEN scales. Trigger measurements provided additional insights into their willingness to cross in front of the EV. The results highlight optimal sound characteristics for EVs, offering guidance on improving pedestrian safety while minimising noise pollution. By refining exterior sound design, this research contributes to the development of effective and user-friendly EV sound standards, ensuring safer and more inclusive urban environments.


The supplementary material contains:

* code/

*. code/__init__.py: Imports the logging setup function and common utilities for the package.

* code/analysis.py: Python script for running the main data analysis routines for experimental results.

* code/common.py: Contains functions for configuration management, dictionary search, and data serialisation.

* code/custom_logger.py: Implements a custom logger class for handling string formatting and logging at various levels.

* code/default.config: Configuration file specifying paths for data, plotly template, and plots directory.

* code/helper.py: Python script that offers helper functions for data preprocessing and assorted tasks.

* code/logmod.py: Initialises and configures the logger with customisable display and storage options, supporting colored logs, threading, and multiprocessing.

* code/main.py: Python script that produces all figures and analyses.

* code/requirements.txt: Lists the dependencies and their versions required for the project.

* code/sound-unity: Contains Unity project for running the experiment.

* code/utils/

* code/utils/extra.py: Python script for averaging participants' responses.

* code/utils/HMD.py: Python script for calculating yaw and managing data related to Head-Mounted Display (HMD) orientation.

* responses/: anonymised data.

* sounds/: sound stimuli.

History

  • 2025-06-05 first online, published, posted

Publisher

4TU.ResearchData

Format

csv, py, txt, pdf, wav, Unity project

Organizations

TU Eindhoven, Department of Industrial Design, Computational Design Systems
TU Delft, Faculty of Aerospace Engineering, Department of Control and Operations