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Project Highlights

A Data-Driven Approach to the Development and Evaluation of Acoustic Electric Vehicle Alerting Systems for Vision-Impaired Pedestrians

The increase of electric vehicles (EVs) on the road has led to safety reservations for vulnerable populations. EVs make significantly less noise in comparison to internal combustion engine vehicles, particularly at low speeds. Although pedestrians are at risk across all demographics, visually impaired pedestrians can be exposed to greater disadvantages in settings where ambient noise levels are louder than the noise emitted from EVs.

This is an important consideration because pedestrians rely on auditory signals when making important safety decisions, such as walking through complex intersections or crossing city streets. As a result of this safety concern, the National Highway Traffic Safety Administration has created regulations (FMVSS-141) that mandate EVs to release sounds that adhere to specific frequency content and sound pressure levels. Previous studies have shown a gap in the research with respect to the current standards of EV warning sounds and their effect on pedestrian safety, and especially the vision impaired. These gaps include a lack of universal sound radiation with the vehicle, implementing “dead” zones where sound may not even reach the pedestrians.

In addition, there has been a lack of communication in understanding the signal characteristics that have the most notable effect on vehicle detectability by vision-impaired and/or distracted pedestrians. Based on previous data collection and new experiments, this study continues the creation of EV acoustics-based safety performance actions, such as the likelihood of vehicle detection with regard to scientifically determined additive sounds that meet current standards in addition to measures for universal sound transmission around the vehicle.