山区高速公路隧道交通事故特征分析:以G65包茂高速6条隧道为例

王芳菲; 彭立飞; 张诗; 黄杰; 徐进

doi:10.3973/j.issn.2096-4498.2023.05.009

隧道建设 >

2023 , Vol. 43 >Issue 5: 816 - 825

DOI: https://doi.org/10.3973/j.issn.2096-4498.2023.05.009

研究与探索

山区高速公路隧道交通事故特征分析:以G65包茂高速6条隧道为例

王芳菲 ,
彭立飞 ,
张诗 ,
黄杰 ,
徐进

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（1. 重庆交通大学交通运输学院, 重庆 400041； 2. 重庆高速巫云开建筑有限公司, 重庆 404546；3. 重庆高速公路集团有限公司南方营运分公司, 重庆 401300； 4. 山区复杂道路环境“人-车-路”协同与安全重庆市重点实验室, 重庆 400074）

王芳菲(1998—)，女，河南商丘人，〖JP2〗重庆交通大学交通运输专业在读硕士，研究方向为交通运输工程及道路交通安全。Email: ciawff@163.com。〖JP〗*通信作者：徐进， Email： yhnl_996699@163.com。

网络出版日期: 2023-06-20

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Characteristics Analysis of Traffic Accidents in Six Tunnels of G65 BaotouMaoming Highway in Mountainous Regions

WANG Fangfei ,
PENG Lifei ,
ZHANG Shi ,
HUANG Jie ,
XU Jin

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(1.School of Transportation,Chongqing Jiaotong University,Chongqing 400041,China;2.Chongqing High Speed Wuyunkai Construction Co.,Ltd.,Chongqing 404546,China;3.Southern Operation Branch of Chongqing Expressway Group Co.,Ltd., Chongqing 401300,China;4.Chongqing Key Laboratory for Human-Vehicle-Road Coordination and Safety of Complex Road Environment in Mountainous Areas,Chongqing 400074,China)

Online published: 2023-06-20

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摘要

为掌握山区高速公路隧道交通事故的规律和特征，提升其交通安全性，对G65包茂高速6条隧道进行分析。从年、月、周和时段4个维度进行时间特征分析，根据隧道类型提出区间划分原则，其中长隧道和特长隧道划分紧急停车带段，通过隧道区段交通事故率进行空间特征分析，分析隧道区段事故形态、车型和涉及车辆数分布特征；以事故严重程度为因变量，从车、路、环境3个要素中选取11个潜在自变量作为影响因素，采用SMOTE过采样法克服非均衡数据问题，通过单因素分析、共线性检验、二元logistic回归分析模型，对比均衡数据和非均衡数据的预测结果，识别事故严重程度的关键影响因素。结果表明：紧急停车带及其影响段事故率较高，严重影响隧道安全；非节假日、阴雨天、入口交织段、大型车辆和圆曲线段是严重事故的显著影响因素。

关键词： 山区公路隧道; 交通事故; 紧急停车带; 二元logistic; 事故严重程度

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王芳菲 , 彭立飞 , 张诗 , 黄杰 , 徐进 .

山区高速公路隧道交通事故特征分析:以G65包茂高速6条隧道为例

[J]. 隧道建设, 2023 , 43(5) : 816 -825 . DOI: 10.3973/j.issn.2096-4498.2023.05.009

Abstract

To further elucidate the rules and characteristics of traffic accidents that occur in highway tunnels in mountainous regions and improve traffic safety, a case study is conducted on six tunnels of the G65 BaotouMaoming expressway. The time characteristics are examined in four dimensions of year, month, week, and hour. Furthermore, according to the tunnel type, the interval division principles are proposed; moreover, the long-and extraong tunnels are classified as emergency parking belts. The spatial distribution characteristics of the traffic accident rate in the tunnel section are also discussed. The distribution characteristics of accident morphology, vehicle type, and vehicle quantities are analyzed. With 11 potential independent variables, such as the vehicle, the road, and the environment, as the influencing factors and the accident severity as the dependent variable, SMOTE sampling methods are used to overcome unbalanced data. Based on univariate analysis, collinearity test, and binary logistic regression analysis model, the predicted results of balanced and unbalanced data are compared to identify the key factors that affect accident seve rity. The results show that the accident rate of emergency parking belts and their influencing sections is high, which seriously affects the safety of the tunnel. Furthermore, regular days (nonholidays), cloudy and rainy days, entrance/exit sections, oversized vehicle, and curved sections are significant influencing factors involved in serious accidents.

Key words： mountain highway tunnels; traffic accident; emergency parking belt; binary logistic; accidental severity

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