Introduction: When you walk on the road, do you often notice the absence of sound from electric vehicles? Today, we bring you a paper by Belenguer et al., titled “The Effectiveness of Alert Sounds for Electric Vehicles Based on Pedestrians’ Perception.” To enhance your reading experience, we have extracted key points and summarized this paper. Follow along as we explore!

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Research Background:

With the popularity of electric vehicles, their silent nature makes them often unnoticed by pedestrians, potentially leading to traffic accidents and collisions. This situation highlights the low noise characteristics of electric vehicles, which, while positively contributing to noise pollution reduction, simultaneously poses road safety issues. Especially with the promotion of new environmental policies and the increase in personal transportation tools, the usage of electric vehicles will further rise, exacerbating this problem.

Research Objective:

To assess the acoustic characteristics of sounds that can be easily perceived by pedestrians in electric vehicles.

Research Process:

This study designed and implemented a system to monitor background noise and emit alert sounds, aiming to evaluate the effectiveness of different sound types in various urban environments to determine the most suitable alert sounds for pedestrian safety.

Research Results:

The results indicate that a new adaptive alert system can adjust noise emissions based on environmental conditions to ensure pedestrians can easily hear them without causing unnecessary noise pollution. Furthermore, the EU’s sound emission limits may be too high in certain cases and require further adjustment.

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PART 01 Research Introduction

One of the main benefits of electric and hybrid vehicles compared to internal combustion engine vehicles is that they do not generate noise, which helps reduce urban noise pollution. However, their greatest advantage poses a risk to the safety of other road users. Research shows that these electric and hybrid vehicles have become part of urban traffic, traveling daily alongside pedestrians and various vehicles, leading to many accidents. Figure 1 shows the number of drivers and pedestrians who died in traffic accidents in Spain in recent years. It is evident that after 2014, the number of driver fatalities sharply decreased, while the number of pedestrian fatalities in traffic accidents did not follow the same trend. In recent years, due to the increase in the number of electric vehicles and their quiet operation, pedestrians are less likely to notice them, resulting in an increase in pedestrian fatalities. Comparing data from the past two years, it can be observed that the number of drivers dying in traffic accidents decreased by 2.25%, but the number of pedestrian deaths increased by 11%.

Figure 1: Number of (a) drivers and (b) pedestrians killed in traffic accidents

PART 02 Research Methodology

1. Define the requirements for the alert system: As of July 1, 2019, EU regulations require vehicles, especially electric and hybrid vehicles, to comply with minimum sound emission requirements. New hybrid and electric vehicles must be equipped with an Acoustic Vehicle Alerting System (AVAS) to enhance pedestrian safety.

2. Conduct background noise analysis: Urban areas in large cities face issues of noise and environmental pollution. Despite sustainable mobility policies, city centers are often affected by acoustic saturation due to high traffic volumes.

3. Define research objectives: Analyze the best alert sounds suitable for pedestrian safety, assess the applicability of EU sound emission limits in different urban environments. Design and implement a system to monitor background noise, emit alert sounds, and compare noise levels. The goal is to achieve an adaptive alert system that can adjust noise emissions based on environmental conditions.

4. Sound level meter specifications: Use DFRobot’s SEN0232 Gravity sound level meter, compatible with Arduino. Precisely measure environmental signal levels using a low-noise microphone. Integrate with an application using plug-and-play technology.

5. Study alert signal parameters: Experiment with different alert signals to determine their effectiveness and user preferences. Replicate three different types of signals with varying durations and spectral content. Select speakers suitable for system practicality and scenarios.

6. Sound simulation: Utilize DFRobot’s DFPlayer Mini external module to play MP3 or WAV sounds in conjunction with Arduino. This module has a micro SD card slot and can be controlled by a microcontroller.

7. Practical operation: Develop Arduino functions to continuously monitor background noise, emit signals through speakers, and calculate level differences. Display monitoring results of level differences.

PART 03 Experiments and Results

Experimental Process: Tests were conducted on a sample of 50 individuals aged 18 to 26 on “Avenida de los Naranjos” (a typical congested street near Valencia Polytechnic University) using the above system and signals. The decision to test these individuals in this context rather than in a laboratory was made to replicate the conditions encountered on the road years later as closely as possible. The main focus of the experiment was:

1. The detectability of these warning sounds.

2. The satisfaction level of participants regarding each warning sound.

3. The preferences of participants for the warning sounds.

Experimental Results:

Figure 2: Detectability of alert sounds

Figure 3: Participant satisfaction

Figure 4: Participant preferences

PART 04 Research Conclusions

According to recommendations from the United Nations’ Quiet Road Transport Vehicles (QRTV) informal working group, alert sounds should meet certain road safety and environmental requirements, including being easily heard and located, socially acceptable, and not increasing urban noise pollution. The study found through psychoacoustic testing that the optimal signal should primarily mimic the noise of internal combustion engine vehicles (artificially generated by music software). While louder sounds are easier to hear, pedestrians or drivers may find them very harsh, leading to discomfort.

The research also mentioned that the sound emission standards proposed by the European Commission (56-75 dB) may not be very suitable for the improved alert sound design. The volume of the alert sound should be moderately reduced and adaptively adjusted based on background noise levels, especially in quiet environments. Additionally, further research should include older populations (who may have hearing impairments) and hearing-impaired individuals to better understand their interactions in real-world scenarios.

Finally, the paper emphasizes that the goal of this research is not to set new sound alert limits but to find an appropriate balance point for alert sound levels that can be detected without introducing excessive noise pollution. Preliminary results indicate that these sound levels can be safely reduced compared to the limits set by the European Union. However, in very quiet or very noisy conditions, these levels may not be optimal. In other words, the level of sound alerts should be determined based on environmental noise levels to maintain safety and effectiveness in various situations.

Note

This article is a paper published in IEEE titled “The Effectiveness of Alert Sounds for Electric Vehicles Based on Pedestrians’ Perception.”

Original link: https://ieeexplore.ieee.org/abstract/document/9226134

The editor has written this in the form of reading notes, and the intellectual property of the original paper belongs to the journal or the original authors. If there are any infringements, please contact us for removal.

Cover image source: Free Photo | Free photo young man crossing the street (freepik.com) (If there are any infringements, please contact us for removal).

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Editor: Zhong Shan, Fu Xi

Editor-in-charge: Yu Xuechen, Zhang Ziyue

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