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Numerical Examinations of Traffic Accident Characteristics Using the Analytical Statistical Methods

机译:分析统计方法的交通事故特征的数值考试

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This study applied analytical statistical approaches to investigate some characteristics of traffic accidents. The regression analysis of the injury severities of accidents, and the discrete choice model of different time periods of day when accidents likely occur have been developed. The Poisson regression and Logit model were used by considering the occurrence mechanism of accidents on freeways. Using the observed accident data in Washington State, the accident injury severity model was successfully estimated using a Passion regression. Three variables were found significant in the model. The findings of this study were encouraging. In the studies of Logit model the probability of occurrence of an accident in the different time periods of day including day, dawn, evening and night was expressed by the four utility functions. Both traffic flow and freeway characteristics were included in the model. Compared with most existing models, the new findings were obtained to describe some accidents characteristics.
机译:本研究应用分析统计方法来调查交通事故的一些特征。事故伤害较严重程度的回归分析,以及发生事故发生的不同时间段的离散选择模型。考虑到高速公路事故发生机制,使用了泊松回归和Logit模型。使用华盛顿州的观察到的事故数据,使用激情回归成功估算了事故损伤严重性模型。模型中发现了三个变量。这项研究的结果令人鼓舞。在Logit模型的研究中,在包括日,黎明,晚上和夜间的不同时间段发生的事故发生的可能性是由四个实用功能表达的。模型中包含交通流量和高速公路特征。与大多数现有模型相比,获得了新发现来描述一些事故特征。

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