Generation and analysis of artificial warning sounds for electric scooters

Torija Martinez, AJ; Elliott, AS; Harris, LE; Podwinska, ZM; Welham, CJ; Nicholls, RK; Steer, B; Williams, DAH

Abstract

• emTransit B.V (Dott) is a European mobility operator currently operating over 30,000 electric scooters in Belgium, France, Germany, Italy, Poland and now the UK. The company aims to expand its UK operations and has recently won a tender for the Transport for London e-scooter trials.
• Dott scooters is looking to mitigate potential safety hazards to pedestrians with the use of an Acoustics Vehicle Alerting System (AVAS) for distinct e-scooter category.
• This report presents the work carried out by Salford’s Acoustics Research Centre (ARC) to create a stand-alone device to generate warning sounds for Dott’s e-scooters.
• This report includes:
o Sound generation process
o Analysis of the warning sounds
o Explanation of the implementation of a subjective experiment
o Conclusions and recommendations for next steps, including how to optimise the sound generation system on the scooter, and how to continue the research for designing optimal warning sounds to maximise vehicle noticeability without increasing noise annoyance.
• Key outputs are:
o A system (including hardware and software) has been developed to generate in real time a warning sound, according to the scooter’s operating conditions (e.g., vehicle speed).
o A laboratory study has been carried out to gauge pedestrian awareness of an approaching e-scooter with and without a warning sound added. Preliminary results suggest that a significant benefit, in terms of vehicle noticeability, is observed with the addition of a warning sound. Of the sounds tested, the addition of a broadband sound with modulated tones seems to be the most effective sound increasing vehicle noticeability.
• The development of technologies, innovations, goods and services within the Clean Growth sector, for instance sustainable and inclusive micro-mobility, is in strategic alignment with the University of Salford.

Citation

Torija Martinez, A., Elliott, A., Harris, L., Podwinska, Z., Welham, C., Nicholls, R., …Williams, D. Generation and analysis of artificial warning sounds for electric scooters

• Report Type: Project Report
• Deposit Date: Mar 25, 2022
• Publicly Available Date: Mar 25, 2022
• Additional Information: Funders : HEIF & Dott Scooters; Projects : Generation and Analysis of Artificial Warning Sounds for Electric Scooters; Grant Number: SEFA12