PROCEEDINGS of the23rd International Congress on Acoustics
9 to 13 September 2019 in Aachen, Germany

Relationship between acoustic characteristics and impression forwarning sounds on electric vehicles
Nozomiko YASUI1
1Graduate School of Science and Engineering, Saitama University, JapanABSTRACT
The motor sound on electric vehicle is quiet at low speeds. Thus, pedestrians have difficulty detecting thosevehicles approaching them. Although those vehicles were designed to play an alert sound to solve thisproblem, it has not been solved yet. When the sound is designed, it should be concerned not only detectabilityof approaching quiet vehicles but also impression of the sound. For pedestrians, it’s important to make iteasier to recognize quiet vehicle. Also, warning sounds shouldn’t contribute to traffic noise annoyance. Our
previous studies found that acoustic characteristics of amplitude fluctuation are effective to make them detectapproaching vehicles. Here, this study evaluates impressions of those fluctuated sound, investigates
relationship between the impression and those characteristics. The impressions of synthesized warningsounds that have periodic and non-periodic amplitude fluctuations were measured by semantic differential
method. The obtained data were analyzed by factor analysis. The results revealed that characteristic ofamplitude fluctuation influences the factors of “alerting”, “clarity” and “familiarity”.
Keywords: warning sound, amplitude fluctuation, Impression

1. INTRODUCTION
Hybrid electric (HEV) or electric vehicles (EV) are becoming common globally. These vehicles arecomparatively quieter than gasoline powered vehicles, especially when those vehicles are driven at
low speeds. It has been a matter of concern that the quietness of quiet vehicles may create dangerous
situations for pedestrians, because sometimes, they have trouble recognizing their approach in anurban sound environment(1). This is not only particular problem for the visually impaired people but
also for any people who cannot see the approaching vehicle, for example in the situation that thevehicle comes from behind of them or an obstacle object. Thus, a warning sound should be played tosolve this problem. When the sound is designed, it should be concerned not only detectability ofapproaching quiet vehicles but also impression of the sound. For pedestrians, it’s important to make iteasier to recognize quiet vehicle. Also, warning sounds should not contribute to traffic noise
annoyance. The previous study(2) found that the amplitude fluctuated sound is effective to enablepeople to notice the approaching vehicles. Here, we evaluated impressions of those fluctuated sound,investigated relationship between impression and characteristics of amplitude fluctuation.

2. EXPERIMENT
2.1 Method
To evaluate impressions of those fluctuated sound, we conducted a semantic -differential-rating
experiment with 5 subjects in a soundproof room. All subjects reported to have normal hearing
abilities. A total of those subjects with an average of 26.0 years (21 to 34) took the experiment. 3
subjects were male and 2 subjects were female.
A total of 84 sounds were used as stimuli. The order of stimuli was determined randomly for eachsubject. After listening to each stimulus, the subjects were requested to rate the impressions. The
impressions of the stimuli were measured by 10 bipolar, 5-step, Semantic Differential(SD) scales. The
10 pairs of adjectives shown in Table 1 were used to create the SD scales. These scales were selectedfrom the previous study[*]. Numbers 1 to 5 were given for each of the five categories on the SD scales.
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nyasui@mail.saitama-u.ac.jp

The stimuli were presented to the subjects through a speakers (GX500Hd, ONKYO Inc.). Thosesubjects were allowed to adjust the acoustic sound level before the experiment to one that best enabled
them to listen to the stimulus. The average level was about LA = 54.4 dB.
Table 1 –Factor loadings of each factor on each adjective scale
Pair of adjectives

Factor 1(Alerting)

Factor 2(Clarity)

Factor 3(Familiarity)

Familiar-

Unfamiliar

0.040

0.040

0.843

Safe-

Dangerous

0.538

0.296

-0.549

Comfortable-

Uncomfortable-0.004-0.162-0.680Calm-

Restless

0.927-0.4520.018

Approaching-

Receding-0.0090.693-0.029

Alerting-

Non alerting

0.770

0.328

0.010

Vehicle-like-

Non vehicle-like-0.064

0.354

0.167

Distinct-

Vague

0.005

0.710

-0.018Informing-Non informing

0.663

0.387

0.221

Advancing-Backing

0.179

0.193

0.044

2.2 Stimuli
A total of 84 sounds were used as stimuli. 3 of those stimuli were non -fluctuated complex sounds,
81 of those stimuli were amplitude-fluctuated complex sounds. The levels of acoustic power of thosestimuli were equalized.
Those fluctuated sounds were synthesized using the procedure proposed in previous study(*),
created in the under condition.
 Frequency characteristics of complex sound: 630 and 2000 or 3150 or 4000 Hz
 Fluctuation frequency: 8, 14 20 Hz Deviation patterns: No deviations, only DA, and DT&DA
 Envelopes on amplitude fluctuation: sine wave, square wave, sawtooth wave
Three kind of complex sounds were used. One is complex sound composed of a 630 Hz tone and2000 Hz (CS 1 ), another is one composed of a 630Hz tone and 3150 Hz (CS 2 ), the other is one
composed of a 630 Hz tone and 4000 Hz (CS 3 ). Those frequencies were decided based on UN
regulation No. 1382 and previous study(*). In case of “No deviation”, the stimulus doesn’t have bothDT and DA. In case of “DA”, the one has only DA. In case of “DT & DA”, the one has both DT andDA.
2.3 Result
The rating values were averaged for each scale and foreach sound. Next, a factor analysis wasperformed for the averaged values with maximum likelihood method and promax rotation. The resultsof the analysis showed that these impressions were accounted for by the orthogonal three-factor
solution. Table 1 shows the resulting factor loading. The first factor is interpreted as the alarm factor
because adjective pairs such as ‘‘alerting/non alerting’’, “calm/ restless” and ‘‘informing/noninforming’’ have high loadings for the first factor. The second factor is interpreted as the clarity factor
because adjective pairs such as ‘‘distinct/vague’’ and ‘‘approaching/receding’’ have high factor
loadings. The third factor is interpreted as the familiarity factor because the adjective pairs‘‘familiar/unfamiliar’’ and ‘‘comfortable/uncomfortable’’ have high factor loadings. Then, those threefactors were labeled “alerting”, “clarity” and “familiarity”, respectively, from the scales showing highloading on the dimensions.
In order to investigate the features of the stimuli with regard to the factors, factor scores for eachstimulus for each factor were also calculated. As a result, it’s found that there are little difference
among each frequency characteristics and deviation patterns.

3. DISCUSSION
The factor scores of stimuli for each factors are given in Fig. 1 and 2. In Fig. 1 and 2, each stimulus

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are described on each two-dimensional space spanned by the “alerting”, “clarity” and “familiarity”. InFig. 1, each stimulus are plotted for each fluctuation frequency. In Fig. 2, each ones are plotted for eachenvelopes. “non” in fig. 1 and 2 means non-fluctuated complex sound.
As can be seen from Fig. 1, it’s found that fluctuation frequency contribute to both factors of“clarity” and “familiarity”. Fluctuating sounds with high frequency are relatively high “familiarity”
while those with low frequency are relatively low “familiarity”. This implies that the impression offamiliarity increased, as fluctuation frequency increased. Moreover, it’s observed that non-fluctuatedcomplex sounds have strong alerting and high familiarity. The reason is thought that those sounds areoften used as alert or warning sound in many places.
As seen in Fig. 2, it’s that observed that that fluctuation frequency contribute to factor of“alerting”. Fluctuating sounds with sine wave are relatively high “alerting” while those with squareand sawtooth wave are relatively low “alerting”.
Those results showed that fluctuating sound for detecting approaching quiet vehicles should bedesigned by considering fluctuation frequency or envelope not to contribute to traffic noise
annoyance.

4. CONCLUSIONSThis study evaluated impressions of amplitude fluctuated sound, investigated relationship between
4ClearFamiliar

42

3rdfactor
Factor3

2ndfactor
Factor2

2Type08
81420
non0

Muddy

Unfamiliar-2-4Type0881420
non0-2-4-4-2

Non alerting

02

Factor1
1stfactor

4-4-2

0

Factor1
1stfactor

Non alerting

Alerting(a) The 1st factor (‘‘Alerting’’ factor) andthe 3rd factor (‘‘Familiarity’ factor)

Familiar

4

Unfamiliar

3rdfactor
Factor3

2Type

808
1420
non0-2-4-2

Muddy

0

Factor2
2ndfactor

24Clear(c) The 2nd factor and the 3rd factor
Figure 1 – Factor scores of sound for each fluctuation frequency

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4Alerting(b) The 1st factor andthe 2ns factor (‘‘Clarity’’ factor)-42

4ClearFamiliar

42

Type

nonRect
SquareSaw
Sawtooth

0Sin

Muddy

Unfamiliar-2

3rdfactor
Factor3

2ndfactor
Factor2

2-4

Type

nonRect
SquareSaw
Sawtooth0Sin-2-4-4-2

Non alerting

02

Factor1
1stfactor

4-4Alerting-20

Factor1
1stfactor

Non alerting(a) The 1st factor and the 2ns factor

24Alerting(b) The 1st factor and the 3rd factor

Familiar

4Unfamiliar

3rdfactor
Factor32Type

nonRect
SquareSaw
Sawtooth

0Sin-2-4-4-2

Muddy

0Factor2
2ndfactor

24Clear(c) The 2nd factor and the 3rd factor
Figure 2 – Factor scores of sound for each envelope
the impression and characteristics of amplitude fluctuation. As a result of factor analysis, the factors of“alerting”, “clarity” and “familiarity” are obtained. Our results revealed that characteristic offluctuation frequency influences the factors of “clarity” and “familiarity”. Moreover, our results foundthat shapes of envelope contribute to factor of “alerting”.
In future work, this study plan to investigate the combined effect of characteristics of amplitude
fluctuation, to conduct the evaluation experiment increased the number of subjects and to examine
relationship between impression of fluctuating motor sound and detectability of approaching quietvehicle.

ACKNOWLEDGEMENTS
This study was partly supported by the Grants-in-Aid for Scientific Research from the Japan
Society for the Promotion of Science (16H03021, 19K20613).

REFERENCES
1. 1. Kerber S and Fastl H. Perceptibility of approaching vehicles in urban background noise. Proc.
Inter-noise 2007, 2007. pp. 981– 988.
2. Yasui N. Effect of amplitude fluctuation on detectability of alert sound for electric and hybrid vehicle inan actual environment. Proc. of Inter-noise 2018, 2018. in18_1619.

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