中山大学学报(自然科学版) ›› 2020, Vol. 59 ›› Issue (4): 120-127.doi: 10.13471/j.cnki.acta.snus.2019.04.10.2019B035

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基于Logistic的城市公交事故严重程度影响因素分析以广东省为例 

林庆丰, 邓院昌   

  1. 中山大学智能工程学院//广东省智能交通系统重点实验室,广东 广州 510006
  • 收稿日期:2019-04-10 出版日期:2020-07-25 发布日期:2020-07-25
  • 通讯作者: 邓院昌(1972年生),男;研究方向:交通心理与行为、交通安全;E-mail:dengych@mail.sysu.edu.cn
  • 作者简介:林庆丰(1992年生),男;研究方向:交通心理与行为、交通安全;E-mail:linqfeng@mail2.sysu.edu.cn

Analysis of factors affecting city bus accident severity based on Logistic modela case in Guangdong Province 

LIN Qingfeng, DENG Yuanchang   

  1. School of Intelligent Systems EngineeringSun Yat-sen University//Guangdong Provincial Key Laboratory of Intelligent Transportation SystemGuangzhou 510006China
  • Received:2019-04-10 Online:2020-07-25 Published:2020-07-25

摘要: 2008~2017年间广东省发生的5 869起公交事故为基础,将其分为车辆间事故、车辆行人事故和单车事故等3类,以事故严重程度为因变量,选取年龄、行驶状态、道路线形、区域、照明条件和事故形态等因素为候选自变量,分别建立Logistic模型进行对比分析,以探究人、车、路和环境等因素对公交事故严重程度的影响。结果表明:除单车事故模型外,各模型拟合度良好。不同形态的公交事故严重程度影响因素之间存在异同性。行驶状态、道路类型、区域和时段等对除单车事故模型外的其余模型因变量均具有显著影响;而道路线形仅对整体事故严重程度具有显著影响,路口路段类型和节假日类型仅对车辆间事故严重程度具有显著影响。研究结果可为降低公交事故严重程度提供一定参考依据。

关键词: 交通安全, 公交客运, 事故严重程度, K-means聚类, Logistic回归模型

Abstract: In order to explore the impact of risk factors, i.e. human, vehicle, road and environment, on bus accident severity, 5 869 bus accidents happening in Guangdong Province during 2008 and 2017 were selected and then divided into 3 categories which were accidents between vehicles, vehicle-pedestrian accidents and single vehicle accidents. Taking accident severity as the dependent variable and selecting age, vehicle maneuver, road alignment, region, lighting condition and accident modalities etc as the independent variables, Logistic models were constructed for comparative analysis. The results show that: The models fit the data properly except the model of single vehicle accidents. The risk factors of bus accident severity had similarities and differences among accidents with different modalities. Vehicle maneuver, road type, region and time were significantly correlated with bus accident severity except in the model of single vehicle accidents. Road alignment only significantly influenced the overall bus accident severity, while type of crash location and holiday only had significant impact on severity of accidents between vehicles. The results can provide references for reducing bus accident severity.

Key words: traffic safety,  , bus transit,  , accident severity,  , K-means clustering,  , Logistic regression model

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