Hybrid and electric vehicles (HVs and EVs) have demonstrated low noise levels relative to their Internal Combustion Engine (ICE) counterparts, particularly at low speeds. As the number of HVs/EVs on the road increases, so does the need for data quantifying auditory detectability by pedestrians; in particular, those who are vision impaired. Manufacturers have started implementing additive noise solutions designed to increase vehicle detectability while in electric mode and/or when traveling below a certain speed. A detailed description of the real-time acoustic measurement system, the corresponding vehicular data, development of an immersive noise field, and experimental methods pertaining to a recent evaluation of candidate vehicles is provided herein. Listener testing was completed by 24 legally blind test subjects for four vehicle types: an EV and HV with different additive noise approaches, an EV with no additive noise, and a traditional ICE vehicle. The primary results examined the distances at which subjects detected each oncoming vehicle and the corresponding acoustical measurements upon detection. Vehicle approach scenarios included two levels of steady-state speed: 10 kph and 20kph. Participants were seated on a closed-test track, and asked to identify auditory detection of each oncoming vehicle within the presence of continuous, spatially distributed, spectrally shaped noise at 55dBA and 60dBA. The spectrum of the noise matched that of typical average urban background noise. . The acoustic data was collected using measurement grade microphones positioned directly above each participant’s head. Findings suggest that although mean detection distances trend higher for vehicles with an additive noise component, they aren’t significantly different from the traditional EV at speeds of 10kph. Moreover, all EV/HVs were detected at significantly shorter distances relative to the ICE vehicle when traveling at 10kph. At 20kph these differences become nearly indistinguishable.


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    Titel :

    Electric Vehicle Detectability: a Methods-Based Approach to Assess Artificial Noise Impact on the Ability of Pedestrians to Safely Detect Approaching Electric Vehicles


    Weitere Titelangaben:

    Sae Int. J. Veh. Dyn., Stab., and Nvh


    Beteiligte:
    Glaser, Dan (Autor:in) / Moore, Douglas (Autor:in) / Neurauter, M. Lucas (Autor:in) / Roan, Michael (Autor:in)

    Kongress:

    Noise and Vibration Conference and Exhibition ; 2017



    Erscheinungsdatum :

    05.06.2017


    Format / Umfang :

    10 pages




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch


    Schlagwörter :



    Electric Vehicle Detectability:Impact of Artificial Noise on Ability of Pedestrians to Safely Detect Approaching Electric Vehicles

    Roan, Michael / Glaser, Dan / Neurauter, Michael | British Library Conference Proceedings | 2017



    Auditory Detectability of Hybrid Electric Vehicles by Blind Pedestrians

    Garay-Vega, Lisandra / Pollard, John K. / Guthy, Catherine et al. | Transportation Research Record | 2011


    Development of Approaching Vehicle Sound for Pedestrians (VSP) for Quiet Electric Vehicles

    Konet, H. / Sato, M. / Schiller, T. et al. | British Library Conference Proceedings | 2011