Evaluation of electric vehicle exterior sounds in virtual and real-world environments – a comparative study

An Exterior Sound Simulator (ESS) is a new technique for evaluating automotive exterior sounds in a virtual environment. These virtual environments can be made to replicate real-world environments where a pedestrian is likely to interact with a vehicle. Thus, they can provide a more realistic context than conventional laboratory listening methods, whilst providing more experimental control than in conventional on-road evaluations. Therefore, ESS combines the advantages of the traditional laboratory listening test and on-road evaluation methods, but has very few of their limitations.
However, to be a successful evaluation tool this simulator needs testing for its external validity, i.e. if the results obtained using simulation also hold true for a comparable real-world situation. This paper describes a comparative study of evaluations performed in a real-world environment and in a replicated virtual environment using ESS. Fourteen participants evaluated an electric car in both the real-world environment and the virtual environment. The visual scenario represented a pedestrian standing at the junction of a residential road crossing while the car, starting each time from one of two different locations situated behind the pedestrian on the adjacent parallel road, and travelling at 12 mph, arrived at the junction at one of the two different times.
Three potential sounds from a vehicle manufacturer were compared by measuring the vehicle’s detection distance, by evaluation of the vehicle sounds as recognisable and detectable, and through evaluation of the car as being powerful and pleasant.
Analysis of variance at an alpha level of 0.05 showed no significant differences between the results obtained from the virtual and real-world experiments for the subjective evaluations of detectability, powerfulness and pleasantness. Thus, subjective evaluations of the vehicle exterior sounds using the ESS are representative of similar real-world evaluations.