Journal of safety research · 2025
How do EV crashes differ from ICEV crashes: A comparative study of Pennsylvania.
СтатьяСравнительное исследованиеПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Xu Ningzhe, Xu Yiming, Liu Jun, Jiao Junfeng
Аннотация
INTRODUCTION: As electric vehicles (EVs) become more common due to adoption and policy incentives, understanding their safety aspects compared to internal combustion engine vehicles (ICEVs) is crucial for safety and acceptance.
METHOD: This study leveraged crash data from Pennsylvania during 2020 and 2022 to investigate the patterns and characteristics of crashes involving EVs (including battery electric vehicles, plug-in hybrid electric vehicles, and hybrid electric vehicles) and compare them with ICEV crashes through spatiotemporal patterns, statistical tests, and regression models.
RESULTS: The results indicated that EV-involved crashes predominantly occurred in urban areas and were more frequent during daylight hours, with a time-of-day distribution exhibiting more fluctuations. Moreover, EV crashes had a lower percentage of fatal and severe injury crashes compared to ICEV crashes. Aggressive driving and traffic sign/signal violations were more common among EV crashes, whereas driving under the influence (DUI) and speeding-related behaviors were more commonly associated with ICEV crashes. For multi-vehicle crashes, DUI, speeding, running red lights, head-on collisions, and angle collisions were positively associated with crash severity for both ICEV- and EV-involved crashes.
CONCLUSIONS: EV and ICEV crashes differ in spatiotemporal distribution, crash severity, and associated factors.
PRACTICAL APPLICATIONS: This study provides valuable insights into the distinctive patterns of EV crashes and crash severities, thus offering vital references for the development of road safety plans and strategies that accommodate the emergence of EVs.
METHOD: This study leveraged crash data from Pennsylvania during 2020 and 2022 to investigate the patterns and characteristics of crashes involving EVs (including battery electric vehicles, plug-in hybrid electric vehicles, and hybrid electric vehicles) and compare them with ICEV crashes through spatiotemporal patterns, statistical tests, and regression models.
RESULTS: The results indicated that EV-involved crashes predominantly occurred in urban areas and were more frequent during daylight hours, with a time-of-day distribution exhibiting more fluctuations. Moreover, EV crashes had a lower percentage of fatal and severe injury crashes compared to ICEV crashes. Aggressive driving and traffic sign/signal violations were more common among EV crashes, whereas driving under the influence (DUI) and speeding-related behaviors were more commonly associated with ICEV crashes. For multi-vehicle crashes, DUI, speeding, running red lights, head-on collisions, and angle collisions were positively associated with crash severity for both ICEV- and EV-involved crashes.
CONCLUSIONS: EV and ICEV crashes differ in spatiotemporal distribution, crash severity, and associated factors.
PRACTICAL APPLICATIONS: This study provides valuable insights into the distinctive patterns of EV crashes and crash severities, thus offering vital references for the development of road safety plans and strategies that accommodate the emergence of EVs.