The number of electric vehicles on the road is increasing rapidly every year. Due to the decreased sound produced by these vehicles at low speeds, there is significant concern that pedestrians and bicyclists will be at increased risk of vehicle collisions. This is particularly true for those with vision impairment who cannot rely on visual cues to alert them of an approaching vehicle. This thesis explores pedestrian aural detectability of six electric vehicle additive sounds produced by two additive sound systems: a modified version of the factory equipped system and a prototype exciter transducer-based system. All additive sounds and systems were first evaluated for regulatory compliance at stationary, 10 km/h, and 20 km/h conditions and then pedestrian detectability was assessed using 16 blind folded participants and on-road drive by tests. Participant drive by tests were then replicated using 3D sound field recordings played in a high-fidelity immersive reality lab. Results were used to verify the accuracy of lab environment and its potential applicability to future testing. The exciter transducer acoustic warning system was found to created more uniform sound levels on the passenger and drivers' sides of the vehicle than the factory system but produced lower sound levels on the front side of the vehicle. Additive sound modulation rate was not determined to be a key differentiator in pedestrian detectability and low frequency emphasis sounds were found to have the highest level of pedestrian detectability. As expected, vehicle speed played a critical role in participant detection with the 20 km/h speed condition producing higher average detection distances. The immersive reality lab was found to not replicate on-road environment however a perceived linear offset was observed between the two environments. / Master of Science / The number of electric vehicles on the road increases every year due to growing consumer demand for clean and sustainable transportation. Due to the decreased sound produced by these vehicles at low speeds there is significant concern that pedestrians and bicyclists will be at increased risk of vehicle collisions. This is particularly true for those with vision impairment who cannot rely on visual cues to alert them of an approaching vehicle. This thesis explores pedestrians' ability to detect six electric vehicle additive sounds produced by two sound systems: a modified version of the factory equipped system and a prototype system designed to produce uniform sound around the vehicle. All sounds and systems were evaluated see if they met current regulations at stationary, 10 km/h, and 20 km/h conditions. Pedestrians' ability to detect the vehicle was assessed using 16 blind folded participants and on-road tests where participants were asked to press a button when they heard an approaching vehicle. Participant drive by tests were then replicated using recordings taken on the same section of road and played in a lab environment. Results were used to see if the lab environment matched the results seen on the road. The prototype system created more uniform sound levels on the passenger and drivers' sides of the vehicle than the factory system but consistently produced lower sound levels on the front side of the vehicle. Sound modulation rate was not determined to be a key differentiator in pedestrian detectability and low frequency emphasis sounds were found to be the most easily detected by pedestrians. As expected, vehicle speed played a critical role in participant detection with the 20 km/h speed condition producing higher detection distances. The lab environment was found to not replicate on-road environment however similar offsets and sound ordering was observed between the two environments. Further work will be needed assess and correct this disagreement.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/111612 |
| Date | 23 August 2022 |
| Creators | Beard, Michael Hansen |
| Contributors | Mechanical Engineering, Roan, Michael J., Barry, Oumar, Tarazaga, Pablo Alberto |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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