An Evaluation of Laboratory and Test Road Environments and Electric Vehicle Warning Sounds and Systems

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.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Mechanical Engineering

Department dc:contributor.department

Mechanical Engineering

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2022

Author dc:creator

• Beard, Michael Hansen

Chair dc:contributor.committeechair

• Roan, Michael J.

Committee members dc:contributor.committeemember

• Barry, Oumar
• Tarazaga, Pablo Alberto

• Electric Vehicles
• Warning Sounds
• Detection
• Listener tests

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:35387

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/111612