Xuerui Hou, Meiling Su, Chenhui Liu, Ying Li, Qinglu Ma
{"title":"Examination of the Factors Influencing the Electric Vehicle Accident Size in Norway (2020–2021)","authors":"Xuerui Hou, Meiling Su, Chenhui Liu, Ying Li, Qinglu Ma","doi":"10.3390/wevj15010003","DOIUrl":null,"url":null,"abstract":"With the great increase of electric vehicles (EVs) in the past decade, EV-involved traffic accidents have also been increasing quickly in many countries, bringing many new traffic safety challenges. Norway has the largest EV penetration rate in the world. Using the EV accident data from Norway in 2020 and 2021, this study aims to investigate the features of EV safety comprehensively. Firstly, a descriptive analysis is conducted. It has been found that rear-end collisions are the major collision type of EVs, and EVs are very likely to collide with pedestrians/cyclists. In addition, in terms of roadway type, EV accidents mainly occur on medium- and low-speed roads; in terms of environment, they mainly occur in good visibility conditions and dry road surface conditions. Then, a regression analysis is conducted to identify the key factors affecting the accident size, which is the number of traffic units involved in an accident and taken as the accident severity surrogate here. Since EV accidents are divided into four categories in order of accident size, the ordered logit model is adopted. It divides a multi-categorical dependent variable into multiple binary data points in order and calculates the probability of the dependent variable falling into each category with the logit model, respectively. The estimation results indicate that time of day, speed limit, and presence of medians have statistically significant impacts on the EV accident size. Finally, some countermeasures to prevent EV accidents are proposed based on the research results.","PeriodicalId":38979,"journal":{"name":"World Electric Vehicle Journal","volume":"72 10","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"World Electric Vehicle Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/wevj15010003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
With the great increase of electric vehicles (EVs) in the past decade, EV-involved traffic accidents have also been increasing quickly in many countries, bringing many new traffic safety challenges. Norway has the largest EV penetration rate in the world. Using the EV accident data from Norway in 2020 and 2021, this study aims to investigate the features of EV safety comprehensively. Firstly, a descriptive analysis is conducted. It has been found that rear-end collisions are the major collision type of EVs, and EVs are very likely to collide with pedestrians/cyclists. In addition, in terms of roadway type, EV accidents mainly occur on medium- and low-speed roads; in terms of environment, they mainly occur in good visibility conditions and dry road surface conditions. Then, a regression analysis is conducted to identify the key factors affecting the accident size, which is the number of traffic units involved in an accident and taken as the accident severity surrogate here. Since EV accidents are divided into four categories in order of accident size, the ordered logit model is adopted. It divides a multi-categorical dependent variable into multiple binary data points in order and calculates the probability of the dependent variable falling into each category with the logit model, respectively. The estimation results indicate that time of day, speed limit, and presence of medians have statistically significant impacts on the EV accident size. Finally, some countermeasures to prevent EV accidents are proposed based on the research results.