摘要
根据京珠高速公路韶关段4个隧道的交通事故资料,以事故严重程度为因变量,从时间、隧道环境和交通动态因素3个方面选择9个候选自变量,采用反向选择法分析候选自变量与因变量是否显著相关。研究发现:事故发生时段、碰撞类型、天气和日标准小客车交通量与年平均日交通量(AADT)之比与事故严重程度显著相关。采用logistic回归模型,分析了事故发生时段、碰撞类型、天气和日标准小客车交通量与AADT之比对交通事故严重程度的影响程度,并根据发生比率的概念,对模型的估计情况进行了解释。最后,从模型的拟合优度和预测准确度2个方面对模型进行检验。结果表明,建立的logistic回归模型在事故严重程度影响因素分析中具有较好的适应性和实用性。
Based on the traffic accident data collected from the 4 tunnels in Shaoguan section of Beijing-zhuhai freeway,taking the accident severity as dependent variable,selecting 9 candidate independent variables from 3 aspects：the time of the accident happened,the tunnel environment,and the traffic dynamic factors,the relevance between the candidate independent variables and the dependent variable was analyzed by the reverse selection method.It was found that the time of the accident happened,the collision type,the weather condition,and the ratio of daily PCU to AADT are the factors that most significantly related to the accident severity.The effects of these most related factors on the accident severity was analyzed using a logistic regression model.A statistical interpretation was given to the modeled estimates in terms of the odds ratio concept.The proposed logistic regression model was tested on the goodness-of-fit and predictive accuracy and the encouraging result was achieved.
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2010年第2期423-426,共4页
Journal of Jilin University:Engineering and Technology Edition
基金
国家科技支撑计划项目(2007BAK35B06)
国家自然科学基金项目(50878026)
关键词
交通运输安全工程
LOGISTIC回归模型
公路隧道
事故严重程度
engineering of communications and transportation safety
logistic regression model
highway tunnel
accident severity
