Characteristic Analysis of Vehicle-VRUs Crashes Based on Real Accident Data in China
- Delivery
- Available on this site
- Format
- Price
- Non-members (tax incl.)：￥1,100 Members (tax incl.)：￥880
- Publication code
- 20266193
- Paper/Info type
- Proceedings (Autumn)
No.133-26
- Pages
- 1-8(Total 8 p)
- Date of publication
- Oct 2026
- Publisher
- JSAE
- Language
- English
- Event
- 2026 JSAE Annual Congress (Autumn)
Detailed Information
| Author(J) | 1) Zeyao Li, 2) Zhuo Li, 3) Di Pan, 4) Koji Mizuno, 5) Yong Han |
|---|---|
| Author(E) | 1) Zeyao Li, 2) Zhuo Li, 3) Di Pan, 4) Koji Mizuno, 5) Yong Han |
| Affiliation(J) | 1) Huaqiao University, 2) Xiamen University of Technology, 3) Xiamen University of Technology, 4) Nagoya University, 5) Xiamen University of Technology |
| Affiliation(E) | 1) Huaqiao University, 2) Xiamen University of Technology, 3) Xiamen University of Technology, 4) Nagoya University, 5) Xiamen University of Technology |
| Abstract(E) | Vulnerable Road Users (VRUs) suffer high casualty rates in traffic crashes and are a major focus of road safety research. Based on 4,060 real vehicle-VRU crash videos from the VRU-TRAVi database in China, this study conducts statistical and characteristic analysis across pre-crash, in-crash, and post-crash stages. K-modes clustering is used to identify typical accident scenarios. The findings reveal spatiotemporal, kinematic, and injury patterns of pedestrians, cyclists, and powered two-wheelers, and clarify key risk factors including visual obstructions, speed, and impact locations. Results provide reliable data support for vehicle safety design, road management, and VRU crash prevention. |
