What do the findings mean for automotive sound quality? 7.4.1.
Currently, policy makers place emphasis on ensuring that the exterior (H)EV sounds are detectable and intuitively recognizable as a vehicle so that can effectively alert pedestrians and other road users of the vehicles’ approach to ensure their safety. However, vehicle companies are concerned about how (H)EV sounds would also influence pedestrians’ impressions of the vehicle brand. Pedestrians hearing (H)EV exterior sounds could evaluate the (H)EV as a brand, in terms of simply liking to hear the EV pass-by, or as a potential consumer who may want to purchase the vehicle. Thus, they would play an important role in reinforcing the brand image of the vehicle.
Traditionally, automotive sound quality is measured and described using well-established dimensions of emotional evaluations that can effectively discriminate and distinguish the different types of car sounds [26], [28], [57], such as, sounds of different characters like − ‘luxury’, ‘sporty’; and sounds from different manufacturers [26], [28], [57]. Most sound quality researchers use two underlying dimensions of emotional evaluation - where one dimension describes the strength or the power aspect of the vehicle and the other describes the aspects related to comfort and pleasantness of the vehicle [26]. These measures are used for the sounds of ICEVs. This research showed that similar measures can also be used to describe the impressions of the vehicle brand from listening to the (H)EV exterior sounds.
Therefore, it is suggested that the (H)EV exterior sound quality should be evaluated in terms of the following measures:
I. Detection rate of sounds
expressed in terms of detection distance or time-to-vehicle arrival
II. “Detectability” of sounds
expressed as ratings on semantic scales
III. “Recognisability of the sounds” as a vehicle
expressed as ratings on semantic scales
IV. Emotional characteristics of the sound
expressed in terms of standard dimensions of vehicle sound quality
Here, the first three measures are to ensure the (H)EV exterior sounds are effective in alerting the pedestrians of the vehicle approach, whereas the last measure is used to understand how these sounds influence perception of the vehicle brand. Among these measures, detection rate should take precedence as pedestrians’ safety is currently the most pressing issue for (H)EV sounds. This is followed by measuring emotional characteristics in standard dimensions of vehicle sound quality. This is because in the long run manufacturers are keen to distinguish themselves in the vehicle market. Although, measuring detectability and recognisability of (H)EV exterior sounds are not as important as other measures, they complement the detection rate measure for a more comprehensive evaluation of the (H)EV sounds for pedestrians’ safety.
Study 2 and study 3 show that these measures are not mutually exclusive. Particularly, detection rate of (H)EV exterior sounds does not correlate with the existing perceptual dimensions of automotive sound quality. Therefore, the vehicle sounds that are more detectable may not be more recognizable, or portray a positive
impression of the vehicle brand. Overall, in context of (H) EV, exterior sounds pedestrians’ safety is the primary requirement, but how these sounds influence the impression of the vehicle brand cannot be overlooked. A more holistic evaluation of the (H)EV exterior sound quality should assess these sounds in terms of all these contrasting measures.
In study 2, the sound quality measures namely, detection rate, powerfulness and pleasantness have significant strong correlation (p<.05) with metrics of SPL, loudness, roughness and sharpness of the (H)EV exterior sounds (see Table 5.5 and Table 6.5). Previous research shows that the same metrics are key in determining and influencing perception of automotive interior sound quality [26]. The results from study 2 indicate that, just like the vehicle interior sounds, these metrics influence (H)EV exterior sound quality. In particular, the (H)EV sounds’ detection rate had a positive linear relation with the SPL dB(A), which means as the SPL dB(A) increased the target car sounds were detected faster. Similar results have been found in other detection tests of vehicle sounds [9], [10]. This fact is also supported by the fundamental auditory signal detection theories that states SPL in dB(A) as a major determinant of the audibility of sounds [11]. However, one sound did not follow this relationship (see section 5.4.6) and was detected much faster than some sounds with similar or higher decibel levels. In this research detection rate was not correlated to other key metrics (loudness, roughness and sharpness). Therefore (H)EV sounds’ detectability may be affected by other metrics not commonly used in automotive sound quality research.
Additionally, the research provides more evidence that for sounds with wide acoustic variety in metrics, A-weighted SPL predicts the rate at which pedestrians detect a vehicle. However, sounds with low acoustic variety (within 2 dB difference)
may have significantly different detection rate and recognisability. Study 3 however used only three sounds that had very narrow variation in these metrics. Therefore, no significant correlation was found in study 3.
What do the findings mean for auditory detection and evaluation? 7.4.2.
Study 2 and 3 both show that rate of detecting the (H)EV sounds is dependent on arrival time of the target vehicle. Previous research in the field of auditory signal detection indicates that an uncertainty in the onset of a target signal in the presence of background noise leads to decrease in detectability [108]. An increase in the time of the onset of target signal within an experimental condition slows down or reduces the listener’s ability to detect the signal [108]. A reason proposed for this is that as uncertainty of the signal presence or onset time increases, the listeners become more fatigued resulting in the decrease in their performance in detection [108].
This research found that increase in the target vehicle’s arrival time within an experimental condition slows down a participants’ rate of detecting a target vehicle sound, i.e. it reduces participants’ ability to detect a target vehicle sound. This phenomenon is in agreement with the above observations in auditory signal detection [108]. Therefore, arguably an increase in the target vehicle’s arrival time, decreases the listener’s level of attention and increases the fatigue. This reduces their rate of detecting the vehicle.
Previous research suggests that the increase in the background sound, decreases the detection rate [108]. An increase in the randomness of the background sound can decrease the listener’s capability to detect the target sound [108]. This also applies to detecting vehicle sounds in presence of real-life ambient soundscape.
Study 2 provides evidence that participants make more detection errors due to fluctuations in the background sound. Similar detection errors have been found in previous studies involving vehicle detection in urban soundscape [31], [38], [48]. This research indicates that in the presence of real-life ambient soundscape participants’ find the vehicle detection difficult. In real world, pedestrians have to identify and detect the vehicle in the presence of other non-vehicle based ambient sounds. As such, pedestrians tend to detect and identify the vehicles more continuously and subjectively [10]. Study 2 indicates that if a listening experiment involves detecting vehicle sounds in presence of real-life ambient soundscape then the detection task will become more representative of the real-world vehicle
detection through a detection-time-measurement-method with following
characteristics:
I. An option to record many instances of detections to accommodate for and
monitor the participants’ self-reported detection errors if and whenever
they mistake a vehicle for the transient sounds in the ambience.
II. A scale to subjectively evaluate ‘detectability’ of the vehicle sounds.