基于部分优势比模型的电动二轮车驾驶人头部损伤致因研究

为获取二轮车骑行者头部损伤程度与影响因素之间的定量关系,提取CIDAS数据库中1411例电动二轮车交通事故深度调查数据并进行筛选、分级处理,建立骑行者头部损伤程度与驾驶人、车辆结构、道路环境等30个变量之间的定量关系。为克服多项log"模型和有序log"模型的不足,选择部分优势比模型进行建模计算及模型弹性分析。结果表明,其中13个变量与骑行者头部损伤有显著的影响。驾驶人身材、驾车时间长度、制动行为、交通控制模式、黄昏或黎明时间等因素对于驾驶人头部损伤具有不同程度的影响。研究对于后续重点区域安全设施部署、安全防护措施的设置、安全教育培训的目标性具有重要的意义。

To obtain the quantitative relationship between the degree of head injury of electric two-wheeler drivers and influencing factors,the study extracted the in-depth investigation data of 1411 cases of electric two-wheeler traffic accidents in CIDAS database.By screening and grading these data,the quantitative relationship between the degree of the ridefs head injury and 30 variables such as the driver,the vehicle structure and the road environment was established.In order to overcome the shortcomings of multiple logit models and ordered logit models,the study selected the partial proportional odds model for modeling calculation and model elasticity analysis.The results showed that 13 of these variables have a significant impact on the rider's head injury.Factors such as the driver's body size,the length of driving time,the braking behavior,the traffic control mode,the time of the day(dusk or dawn)and others have different degrees of impact on the rider's head injury.The study is of great significance to the deployment of safely facilities in key areas,the setting of safety protection measures and the achievement of safety education and training goals.