Do experiments in the virtual world effectively predict how pedestrians evaluate electric vehicle sounds in the real world?

Sneha Singh, Sarah R Payne, James B. Mackrill, Paul A. Jennings

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)
64 Downloads (Pure)

Abstract

New laws stipulate that electric vehicles must emit additional sounds to alert pedestrians of the vehicles' approach to prevent potential collisions. These new sounds will also influence pedestrians' impression of the vehicle brand. A methodology has been developed to evaluate electric vehicle (EV) sounds in a virtual-world environment by assessing; (a) detectability and recognisability to ensure pedestrians' safety, and (b) emotional evaluation of the sound quality to determine its impact on the perception of the vehicle brand. This experimental study examines external validity of the methodology. Fourteen participants evaluated an EV, emitting three sounds, in a traffic scenario in a real-world and a virtual-world environment. The traffic scenario involved a pedestrian 'standing' at a residential road junction while the EV travelled at 12 mph from behind the pedestrian, arriving at the junction at one of two pre-set times. Results show that the presented virtual-world methodology accurately predicts pedestrians' evaluation of detectability of EV sounds and powerfulness and pleasantness of the vehicle brand in the corresponding real-world scenario. It also predicts the ranked order of sounds in the real-world for detection distance and recognisability. Arguably, for similar methods and setups, virtual-worlds would effectively predict pedestrians' evaluation in the real-world. Interestingly, varying a vehicle's arrival time, just like a real-world scenario, is found to affect pedestrians' detection rate. Unlike experiments in the real-world, the presented methodology for experiments in virtual-world benefits from being reliable, quick, easy to implement, with more experimental control and options to easily manipulate any experiment variables.

Original languageEnglish
Pages (from-to)119-131
Number of pages13
JournalTransportation Research Part F: Traffic Psychology and Behaviour
Volume35
DOIs
Publication statusPublished - Nov 2015

Keywords

  • Detection
  • Electric vehicle sounds
  • Evaluation
  • Quiet vehicle
  • Recognition
  • Virtual world

ASJC Scopus subject areas

  • Applied Psychology
  • Transportation
  • Automotive Engineering

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