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Application of Random-parameter Negative Binomial Model to Examine the Relationship between the Severity of Traffic Accident

机译:应用负参数负二项式模型检验交通事故严重程度之间的关系

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Traffic accident injury is the eighth leading cause of death in the world, which seriously affects economic development and life stability. In order to explore the influencing factors of the severity of major road traffic accidents in China, potential influencing factors were selected from the statistical data of 366 major accidents. Fixed-parameter and random-parameter negative binomial model were respectively used to build models for accidents data. The results show that geographical zone, time and date of accident, road administrative grade, season, accident type, road alignment and number of traffic violation behavior are significantly related to the accident severity. Strict management of drivers is an effective way to improve the degree of accident injury.
机译:交通事故伤害是世界第八大死亡原因,严重影响经济发展和生活稳定。为了探讨影响我国重大道路交通事故严重性的因素,从366起重大交通事故统计数据中选择了潜在的影响因素。分别使用固定参数和随机参数负二项式模型建立事故数据模型。结果表明,地理区域,事故发生的时间和日期,道路行政级别,季节,事故类型,道路路线和交通违规行为的数量与事故严重程度密切相关。严格管理驾驶员是提高事故伤害程度的有效途径。

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