Detection of sound from AVAS in urban environments
Typ
Examensarbete för masterexamen
Master's Thesis
Master's Thesis
Program
Sound and vibration (MPSOV), MSc
Publicerad
2024
Författare
Demirci, Bircan
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
Functionality of AVAS (Acoustic Vehicle Alert System) faces challenges in urban
environments, where background noises may mask AVAS sounds. From a safety
perspective, designing AVAS sounds that effectively warn vulnerable road users
(without causing extensive environmental noise) is even more crucial in heavy vehicles
since they have longer braking distances, greater momentum, and more blind spots
than light vehicles. This study aims to contribute to the safety aspects of battery
electric trucks (BEV trucks) by exploring their detectability in urban areas and their
classification rate, which shows whether they can be distinguishable from cars.
In this regard, listening tests were conducted with 51 participants: eight distinct
vehicle sounds, five of which belong to a BEV heavy truck, one to an ICE (Internal
combustion engine) truck, one to a BEV passenger car, and one to an ICE passenger
car. Each vehicle sound was presented both at 10 and 20 km/h. In the first session
of the test, participants were tasked with classifying approaching vehicles as either
trucks or cars, without additional urban background noise (the equivalent levels
are about 45 dB(A)). During the second session, they were tasked with detecting
approaching vehicles amidst continuous urban background noise (the equivalent
levels are in the range between 57 and 62 dB(A)) and then classifying the detected ones.
The results revealed that in the first session of the test, where there was no additional
background noise, 50% of the vehicles were correctly classified within the safe zone.
The vast majority of the vehicles approaching at 10 km/h were classified within the
safe zone, while those approaching at 20 km/h were classified within the unsafe zone.
In the second session, with continuous urban background noise, 30% of the vehicles
were detected and then correctly classified within safe distances. Unlike the first
session, a large portion of the vehicles approaching at 20 km/h were detected and
then correctly classified within the safe zone, while those approaching at 10 km/h
were detected and then classified within the unsafe zone. While the ICE truck
outperformed at both speeds and in both sessions, the accuracy of the BEV truck
results varied depending on the session and vehicle speed. Moreover, the accuracy
rates of the tasks’ results were mainly affected by whether the AVAS sound was
in active mode or not, the modulation of the AVAS sound, and whether the tonal
components of the BEV truck were dominant or not. These findings may provide
insights into the current and future needs of designing AVAS sounds for electrified
trucks.
Beskrivning
Ämne/nyckelord
Acoustic Vehicle Alerting Systems, Electric Heavy Vehicles, BEV Trucks, Exterior Vehicle Sound, Pedestrian Safety, Detectability, Listening Experiments