Exploration of Crash Features of Electric Vehicles with Traffic Crash Data in Changshu, China
The rapid development of electric vehicles (EVs) around the world has resulted in new challenges for road safety. Identifying the features of EV crashes is a precondition for developing effective countermeasures. However, due to the short history of EV development, existing studies on EV crashes are...
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MDPI AG
2025-03-01
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| Series: | World Electric Vehicle Journal |
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| Online Access: | https://www.mdpi.com/2032-6653/16/3/185 |
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| author | Rongxian Long Chenhui Liu Song Yan Xiaofeng Yang Guangcan Li |
| author_facet | Rongxian Long Chenhui Liu Song Yan Xiaofeng Yang Guangcan Li |
| author_sort | Rongxian Long |
| collection | DOAJ |
| description | The rapid development of electric vehicles (EVs) around the world has resulted in new challenges for road safety. Identifying the features of EV crashes is a precondition for developing effective countermeasures. However, due to the short history of EV development, existing studies on EV crashes are quite limited. China, which has the largest EV market in the world, has witnessed a substantial increase in EV crashes in recent years. Therefore, this study comprehensively investigated the characteristics of EV crashes by analyzing the 2023 traffic crash data from Changshu. This is a pioneering study that discusses EV safety by comparing real EV crashes and ICEV crashes from a city in China, the largest EV market in the world. It was found that EV crashes had a higher fatality rate compared to internal combustion engine vehicle (ICEV) crashes. Compared to ICEV crashes, EV crashes are more likely to hit pedestrians and occur during the starting phase. Among the vehicles involved in crashes, the proportion of EVs used for passenger and freight transport was higher than that of ICEVs. In addition, for EV crashes, the proportion of female drivers was much higher, but the proportion of elderly drivers was much lower. Thus, to identify the significant factors influencing crash severity, a logistic regression model was built. The results confirm that EV crashes are more likely to be more fatal than ICEV crashes. In addition, hitting pedestrians and light trucks and crashes occurring in rural areas, at intersections, during winter, and on weekdays could significantly increase the risk of fatalities. These findings are expected to provide new perspectives for improving EV safety within the wave of automotive electrification. |
| format | Article |
| id | doaj-art-b7dfef79c7dd47b5a42ab75a2cce372d |
| institution | OA Journals |
| issn | 2032-6653 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj-art-b7dfef79c7dd47b5a42ab75a2cce372d2025-08-20T01:50:07ZengMDPI AGWorld Electric Vehicle Journal2032-66532025-03-0116318510.3390/wevj16030185Exploration of Crash Features of Electric Vehicles with Traffic Crash Data in Changshu, ChinaRongxian Long0Chenhui Liu1Song Yan2Xiaofeng Yang3Guangcan Li4College of Civil Engineering, Hunan University, Changsha 410082, ChinaCollege of Civil Engineering, Hunan University, Changsha 410082, ChinaSchool of Traffic Management, People’s Public Security University of China, Beijing 100038, ChinaChangshu Traffic Police Brigade, Suzhou 215500, ChinaChangshu Traffic Police Brigade, Suzhou 215500, ChinaThe rapid development of electric vehicles (EVs) around the world has resulted in new challenges for road safety. Identifying the features of EV crashes is a precondition for developing effective countermeasures. However, due to the short history of EV development, existing studies on EV crashes are quite limited. China, which has the largest EV market in the world, has witnessed a substantial increase in EV crashes in recent years. Therefore, this study comprehensively investigated the characteristics of EV crashes by analyzing the 2023 traffic crash data from Changshu. This is a pioneering study that discusses EV safety by comparing real EV crashes and ICEV crashes from a city in China, the largest EV market in the world. It was found that EV crashes had a higher fatality rate compared to internal combustion engine vehicle (ICEV) crashes. Compared to ICEV crashes, EV crashes are more likely to hit pedestrians and occur during the starting phase. Among the vehicles involved in crashes, the proportion of EVs used for passenger and freight transport was higher than that of ICEVs. In addition, for EV crashes, the proportion of female drivers was much higher, but the proportion of elderly drivers was much lower. Thus, to identify the significant factors influencing crash severity, a logistic regression model was built. The results confirm that EV crashes are more likely to be more fatal than ICEV crashes. In addition, hitting pedestrians and light trucks and crashes occurring in rural areas, at intersections, during winter, and on weekdays could significantly increase the risk of fatalities. These findings are expected to provide new perspectives for improving EV safety within the wave of automotive electrification.https://www.mdpi.com/2032-6653/16/3/185road safetytraffic crasheselectric vehiclelogistic regression |
| spellingShingle | Rongxian Long Chenhui Liu Song Yan Xiaofeng Yang Guangcan Li Exploration of Crash Features of Electric Vehicles with Traffic Crash Data in Changshu, China World Electric Vehicle Journal road safety traffic crashes electric vehicle logistic regression |
| title | Exploration of Crash Features of Electric Vehicles with Traffic Crash Data in Changshu, China |
| title_full | Exploration of Crash Features of Electric Vehicles with Traffic Crash Data in Changshu, China |
| title_fullStr | Exploration of Crash Features of Electric Vehicles with Traffic Crash Data in Changshu, China |
| title_full_unstemmed | Exploration of Crash Features of Electric Vehicles with Traffic Crash Data in Changshu, China |
| title_short | Exploration of Crash Features of Electric Vehicles with Traffic Crash Data in Changshu, China |
| title_sort | exploration of crash features of electric vehicles with traffic crash data in changshu china |
| topic | road safety traffic crashes electric vehicle logistic regression |
| url | https://www.mdpi.com/2032-6653/16/3/185 |
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