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Characteristics and Casualty Analysis of Two- Wheeler Accidents in China, Data Source: The China In-Depth Accident Study (CIDAS)
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 3, 2018 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
The two-wheeler is a vehicle that runs on two wheels, which is classified as motorcycle, electric-bicycle, and bicycle in this research. China has the largest number of two-wheelers and relevant accidents in the world. The two-wheeler riders have a high level of vulnerability, creating a significant necessity to better understand the characteristics according to the road-user group. The objective of this paper is to study the characteristics and analyze the causes of two-wheeler accidents in China using the CIDAS (China In-Depth Accident Study) Database. 2012 cases of two-wheeler accidents with riders injured or dead were collected from the CIDAS Database from 5 cities (Changchun, Beijing, Weihai, Ningbo and Foshan) in China over a period of 5 years (2011.07-2016.06). Several key parameters such as accident characteristics, accident scenarios (containing collision point distribution, accident type, clock direction distribution and head WAD distribution) were analyzed using measurement and mathematical statistical methods. Results show that the motorcycle accident was the most frequent two-wheeler accident type in China, which accounted for 52.7% of the total two-wheeler accidents. The two-wheeler riders’ injury information were also queried from the CIDAS Database for detailed study regarding injuries and their sources. The results of the analysis allow for an overall assessment of the two-wheeler riders safety level in China, thus providing a useful support to decision makers working to improve the protection of two-wheeler riders from fatal accidents by a series of countermeasures.
CitationChen, Q. and Dai, B., "Characteristics and Casualty Analysis of Two- Wheeler Accidents in China, Data Source: The China In-Depth Accident Study (CIDAS)," SAE Technical Paper 2018-01-1052, 2018, https://doi.org/10.4271/2018-01-1052.
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