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

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.<br>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.

随着电动汽车（EVs）相较于内燃机车辆运行更为静谧，其普及率的持续提升引发了关于其可探测性的担忧，尤其是针对视觉障碍道路使用者。相关法规强制要求电动汽车配备外部声音信号，以确保其在低速行驶时达到最低声压级要求。然而这类信号常被应用于本已嘈杂的城市环境中，由此带来一项研究挑战：在不加剧噪声污染的前提下提升电动汽车的可探测性。

本研究探索了兼具高辨识度与低烦扰性的合成外部声音方案。研究开展了一项视听实验，招募20名参与者，在15个虚拟现实场景中体验电动汽车从其前方驶过的过程。实验测试了多种声音信号，包括不同频率的纯音、间歇音与复合音，并设置了两个基线对照场景：仅柴油发动机噪声场景与仅轮胎噪声场景（即未添加合成声音）。参与者采用11点ICBEN量表对声音的烦扰度、辨识度与信息性进行评分。触发式测量则进一步探究了参与者横穿电动汽车前方道路的意愿。

研究结果明确了电动汽车外部声音的最优特性，为提升行人安全同时最大限度降低噪声污染提供了科学指导。通过优化电动汽车外部声音设计，本研究助力制定高效且用户友好的电动汽车声音标准，助力构建更安全、更具包容性的城市出行环境。

本研究的补充材料包含：
* `code/__init__.py`：导入项目日志配置函数与通用工具包。
* `code/analysis.py`：用于运行实验结果主数据分析流程的Python脚本。
* `code/common.py`：包含配置管理、字典检索与数据序列化相关功能的函数。
* `code/custom_logger.py`：实现自定义日志类，支持字符串格式化与多级别日志记录。
* `code/default.config`：配置文件，用于指定数据、Plotly模板与绘图目录的存储路径。
* `code/helper.py`：提供数据预处理与各类辅助任务功能的Python脚本。
* `code/logmod.py`：初始化并配置自定义日志器，支持可定制的显示与存储选项，可实现彩色日志、线程与多进程支持。
* `code/main.py`：用于生成全部实验图表并完成数据分析的Python脚本。
* `code/requirements.txt`：列出项目所需依赖包及其对应版本号的文件。
* `code/sound-unity`：用于运行实验的Unity项目文件。
* `code/utils/extra.py`：用于对参与者实验评分结果进行平均处理的Python脚本。
* `code/utils/HMD.py`：用于计算偏航角并管理头戴式显示器（Head-Mounted Display，HMD）姿态相关数据的Python脚本。
* `responses/`：匿名化的参与者实验数据。
* `sounds/`：实验所用声音刺激素材。