Comparison of Crash Characteristics Among Electric Vehicles and Internal Combustion Engine Vehicles
DOI:
https://doi.org/10.31224/3693Keywords:
Crash Analysis, Battery-Electric Locomotives, electirc vehicles, Multinomial Logistic Regression, Negative Binomial, Crash Data, Vehicle crashes, CrashAbstract
With an increasing market penetration of electric vehicles (EVs) in the traffic mix, it become necessary to examine crashes involving EVs. In addition, there is a need to identify differences compared with traditional internal combustion engine vehicles (ICEVs), as EVs are heavier and have different performance characteristics than ICEVs. To date, there is limited research comparing crash characteristics among EVs and ICEVs and further, differentiating among different types of EVs: battery electric vehicles (BEVs), plug-in hybrid electric vehicles (PHEVs), and hybrid electric vehicles (HEVs). To fill this research gap, this paper estimates crash injury frequency and crash severity outcomes through statistical regression analyses. The statistical models and hypothesis testing results suggest both similarities and differences in crash characteristics among BEVs, PHEVs, HEVs, and ICEVs. The similarity lies in human-related factors and traffic-related factors, and the differences come from four types of factors including vehicle, roadway, crash, and environment. The potential reasons (in terms of vehicles’ engine type, software, and hardware) that could contribute to the differences in crash characteristics among four types of vehicles are discussed. The findings of this paper can provide insights into devising safety regulations for EVs. For example, EVs equipped with advanced driving assistant technologies can help relieve crash injury counts. However, the high acceleration rate of electric motors could positively contribute to the crash severity, and the front of BEVs needs more protection since head-on crashes of BEVs cause more severe crashes.
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Copyright (c) 2024 Jiahe Ling, Xiaodong Qian, Konstantina Gkritza
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