Abstract

Prediction models have been extensively used in the field of road safety. However, none of these models have yet been particularly applied to injuries related to zero-emission electric vehicles (EVs), which may lead to different outcomes due to their inaudible engines. Using an optimisable classification tree, the aim of this first-ever study was to predict the likelihood of personal injury severities stemming from EV-related crashes on Britain's roads. The prediction model was found to be capable of detecting significant and insignificant factors. These factors provide important insights into how the severity of injuries could be reduced in the future deployment of EVs. Although there was an increased risk for injuries classified as ‘slight severity’, particularly at lower urban speed limits, several predictors are suggesting that EVs do not pose more of a risk to a certain group. Contrary to popular belief, no convincing evidence was found to suggest that eco-friendly EVs are ‘silent killers’ for vulnerable road users.

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