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Urban crash features analysis based on in-depth investigation

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Weinai Li,Xuesong Wang

Abstract: The purpose of the research is to explore the crash in-depth investigation standard which is suitable for our country. Through the crash scene investigation, deep analysis was made on the features and causes of urban traffic accidents. Based on the Crash In-depth Investigation Data Acquisition Table, the investigators went to the crash scene and collected detailed information of 87 traffic accidents randomly. Statistical analysis was conducted on the crash spot, crash event and some driver features. The study also used the thought of Haddon Matrix for inference, and built the cause analysis matrix to analyze the causes of crash. The study found that Data Collection Table classified crash spot, crash event and crash causes more specifically and clearly. The female drivers are less inclined to crashes compared to male drivers. The drivers over 60 years old took more risk when driving on the road. Fifty percent of the crashes happened in the intersection influencing areas were caused by lane changing. Not wearing safety helmet is the significant reason leading to serious harm on the non-motor vehicle drivers. Through the in-depth analysis on the urban crash features and causes, more specific improvement suggestion could be raised to prevent the crash and reduce the injury.

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