Predicting Severity and Duration of Road Traffic Accident

Fang Zong, Huiyong Zhang, Hongguo Xu, Xiumei Zhu and Lu Wang

Mathematical Problems in Engineering, 2013, vol. 2013, 1-9

Abstract:

This paper presents a model system to predict severity and duration of traffic accidents by employing Ordered Probit model and Hazard model, respectively. The models are estimated using traffic accident data collected in Jilin province, China, in 2010. With the developed models, three severity indicators, namely, number of fatalities, number of injuries, and property damage, as well as accident duration, are predicted, and the important influences of related variables are identified. The results indicate that the goodness-of-fit of Ordered Probit model is higher than that of SVC model in severity modeling. In addition, accident severity is proven to be an important determinant of duration; that is, more fatalities and injuries in the accident lead to longer duration. Study results can be applied to predictions of accident severity and duration, which are two essential steps in accident management process. By recognizing those key influences, this study also provides suggestive results for government to take effective measures to reduce accident impacts and improve traffic safety.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:547904

DOI: 10.1155/2013/547904

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