吉林大学学报(工学版) ›› 2021, Vol. 51 ›› Issue (3): 875-885.doi: 10.13229/j.cnki.jdxbgxb20200055

• 交通运输工程·土木工程 • 上一篇    下一篇

基于乘员伤害分析的公路路侧事故风险评价

程国柱1,2(),程瑞1,徐亮3,张文会1()   

  1. 1.东北林业大学 交通学院,哈尔滨 150040
    2.重庆交通大学 重庆市交通运输工程重点试验室,重庆 404100
    3.长春工程学院 土木工程学院,长春 130012
  • 收稿日期:2020-01-23 出版日期:2021-05-01 发布日期:2021-05-07
  • 通讯作者: 张文会 E-mail:guozhucheng@126.com;rayear@163.com
  • 作者简介:程国柱(1977-),男,教授,博士生导师. 研究方向:道路交通安全,道路线形设计. E-mail:guozhucheng@126.com
  • 基金资助:
    国家自然科学基金面上项目(51778063);教育部人文社会科学研究规划基金项目(18YJAZH009);重庆市交通运输工程重点试验室开放基金项目(2018TE05)

Risk assessment of roadside accidents based on occupant injuries analysis

Guo-zhu CHENG1,2(),Rui CHENG1,Liang XU3,Wen-hui ZHANG1()   

  1. 1.School of Traffic and Transportation,Northeast Forestry University,Harbin 150040,China
    2.Chongqing Key Laboratory of Traffic&Transportation,Chongqing Jiaotong University,Chongqing 404100,China
    3.School of Civil Engineering,Changchun Institute of Technology,Changchun 130012,China
  • Received:2020-01-23 Online:2021-05-01 Published:2021-05-07
  • Contact: Wen-hui ZHANG E-mail:guozhucheng@126.com;rayear@163.com

摘要:

为了定量评估公路路侧事故风险,有针对性地提出安全改善策略,以减少事故损失,本文引入加速度严重性指数ASI作为乘员伤害指标。利用PC-crash仿真软件构建车辆模型、道路模型及路侧护栏优化模型,通过设置不同车辆驶出速度、圆曲线半径、边坡坡度和路基高度,分别开展载重货车、小型客车在有、无路侧护栏设置情况下的驶入路侧试验,共收集了1500组数据。针对公路直线段和曲线段,分别拟合了基于ASI的载重货车、小型客车乘员伤害评估模型。利用Fisher最优分割算法确定了路侧事故风险合理评价级数及各级对应的ASI阈值,给出了基于ASI的路侧事故风险评价方法,并予以案例验证。最后将载重货车比例引入ASI伤害评估模型中,进行模型改进。研究结果表明:ASI与驶出速度、路基高度呈正线性相关,与边坡坡度呈指数相关,与圆曲线半径呈幂相关;设置路侧护栏能够平均减少约24%~28%的小型客车路侧事故伤害,以及31%~36%的载重货车路侧事故伤害;与小型客车相比,载重货车更倾向于发生严重的路侧事故。

关键词: 交通运输安全工程, 风险评价, PC-crash, Fisher最优分割算法, 路侧事故, 乘员伤害

Abstract:

The aims of this study are to achieve a quantitative assessment of the risk of roadside accidents on highways and to propose corresponding safety measures to reduce accident losses. First, the acceleration severity index (ASI) is used as the indicator of occupant injuries, and the horizontal radii, vehicle departure speeds, side slope and subgrade height are taken as research variables in this research. Second, collision tests of trucks and cars were carried out in the presence or absence of roadside guardrails by constructing the vehicle, road and guardrail models in PC-crash simulation software, a total of 1500 data points were collected. For straight and curved segments of highways, the occupant injury evaluation models of trucks and cars were fitted based on the ASI. Third, according to the Fisher optimal segmentation method, reasonable classification standards of risks of roadside accidents and the corresponding ASI thresholds were determined, and the risk assessment methods for roadside accidents based on the ASI were provided and verified. Finally. a proportion of trucks was introduced to further improve the ASI evaluation model. The results show that the ASI has a positive linear correlation with the departure speed and subgrade height, an exponential correlation with the side slope, and a power correlation with horizontal radii. Setting the roadside guardrail can reduce the roadside accident injuries of cars by 24%~28% and that of trucks by 31%~36%. Compared with cars, trucks are more prone to serious roadside accidents.

Key words: engineering of communicaitions and transportation safety, risk assessment, PC-crash, Fisher optimal segmentation method, roadside accident, occupant injury

中图分类号: 

  • U491.31

表1

试验参数"

试验参数取值
车型“载重货车”=0、“小型客车”=1
驶出速度/(km·h-1)40、60、80、100、120
圆曲线半径/m+∞、600、500、400、300、200
边坡坡度1∶6.5、1∶5.5、1∶4.5、1∶3.5、1∶2.5、1∶1.5
路基高度/m0.5、2.5、4.5、6.5、8.5、10.5

表2

驶出角度"

变量取值
驶出速度/(km·h-1)406080100120
驶出角度/(°)129866

图1

试验场景"

图2

ASI与各个试验变量的关系"

图3事故概况"

图4

道路和车辆模型"

表3

路侧护栏尺寸"

参数数值
单跨护栏长度/m4.00
护栏横向宽度/m0.46
横梁上沿离地高度/m0.87
横梁下沿离地高度/m0.56
护栏重心高度/m0.00

图5

仿真结果"

表4

小型客车运动状态"

车速

/(km·h-1)

圆曲线半径/m
+∞600500400300200
40
60
80
100
120

表5

载重货车运动状态"

车速

/(km·h-1)

圆曲线半径/m
+∞600500400300200
40
60
80
100
120

图6

有、无路侧护栏防护作用下的ASI值分布"

表6

乘员伤害评估模型"

编号道路类型模型表达式相关系数R2
1直线段ASIc=0.01Vc+0.127H+0.008e0.121α+0.161-0.24X0.975
2ASIc=0.01Vc+0.566e0.99H+0.019α-1.7181-0.38X0.863
3ASIc=0.002e0.001Vc+0.603logH+8.851×10-14e0.877α+0.0391-0.41X0.622
4ASIt=0.341e1.713Vt+0.085H+0.001e0.208α-0.051-0.37X0.765
5ASIt=0.006Vt+0.12H+6.544×10-9e0.54α+0.461-0.31X0.943
6ASIt=0.05Vt+0.347e0.19H+2.602×10-11e0.735α-1.1841-0.26X0.872
7曲线段ASIc=0.01Vc+0.076H+0.029e0.087α+0.763R-0.247+0.351-0.28X0.982
8ASIc=0.01Vc-1.849e-0.058H+6.155×10-6e0.327α-0.148R+1.0351-0.23X0.783
9ASIc=0.013Vc+0.161logH+0.024α-0.176R-1.0151-0.14X0.833
10ASIt=0.953e0.006Vt+0.333logH+0.3590.038α+0.018R-1.8551-0.36X0.712
11ASIt=0.012Vt+0.33logH+0.034α+0.006e-0.34R-1.0721-0.38X0.879
12ASIt=0.009Vt+0.15H+0.568e0.025α+14.796R-0.013-13.011-0.36X0.971

图7

最小误差函数与分类数的关系"

表7

分类结果"

样本类别k最小误差函数分类情况β
ASIc有序样本2108.321{1~83}{84~126}-
350.012{1~31}{32~83}{84~126}1.64
430.467{1~31}{32~61}{62~83}{84~126}1.31
523.319{1~31}{32~61}{62~83}{84~102}{103~126}-
ASIt有序样本289.975{1~113}{114~166}-
333.721

{1~42}{43~113}

{114~166}

1.85
418.276

{1~42}{43~113}

{114~139}{140~166}

1.23
514.870{1~42}{43~87}{88~113}{114~139}{140~166}-

表8

路侧事故风险评价标准"

风险等级ASIc阈值ASIt阈值乘员损伤等级
I级≤1≤1轻度受伤或未受伤
II级(1,1.43](1,1.56]中度受伤
III级(1.43,1.98](1.56,2.17]重度受伤
IV级>1.98>2.17死亡

表9

案例验证"

事故

编号

事故时速度

/(km·h-1)

道路

类型

圆曲线半径/m路基高度/m边坡坡度

路侧

护栏

事故

车型

驾驶人损伤等级ASI

风险

等级

1108直线+∞21∶1设置小型客车死亡2.54IV
266直线+∞41∶2设置小型客车中度1.16II
370直线+∞3.51∶3.5未设置小型客车重度1.36II
458直线+∞5.81∶4未设置小型客车中度1.52III
5117直线+∞4.31∶2.5未设置小型客车死亡1.99IV
689直线+∞0.91∶4.5未设置小型客车中度1.20II
772直线+∞5.51∶1设置小型客车重度2.61IV
880直线+∞7.81∶2.5设置小型客车重度1.57III
967直线+∞0.51∶5.5未设置载重货车轻度受伤0.92I
1054直线+∞2.51∶3.5未设置载重货车中度1.08II
1162直线+∞3.81∶5.5未设置载重货车中度1.29II
1257曲线88021∶1设置小型客车轻度受伤0.90I
1389曲线108041∶2设置小型客车重度1.23II
1494曲线11703.51∶3.5未设置小型客车重度1.72III
15105曲线24605.81∶4未设置小型客车死亡1.99IV
1678曲线33303.71∶4未设置小型客车重度1.54III
1744曲线2401.81∶2.5未设置小型客车未受伤1.15II
1859曲线98021∶4.5未设置小型客车中度1.26II
1972曲线7703.21∶4未设置载重货车死亡2.26IV
2066曲线9404.41∶3.5未设置载重货车中度2.35IV

表10

改进的ASI阈值"

风险等级ASI阈值
I级≤1
II级(1,1.43+0.13w]
III级(1.43+0.13w,1.98+0.19w]
IV级>1.98+0.19w
1 Zeeger C V, Hummer J, Reinfurt D, et al. Safety effects of cross-section design for two-lane roads[R]. United States:Federal Highway Administration,1987.
2 Shankar V, Mannering F. An exploratory multinomial logit analysis of single-vehicle motorcycle accident severity[J]. Journal of Safety Research, 1996, 27(3): 183-194.
3 Ayati E, Asghar S A, Moghaddam A M, et al. Introducing roadside hazard severity indicator based on evidential reasoning approach[J]. Safety Science, 2012, 50(7): 1618-1626.
4 Roque C, Cardoso J A O L. Safeside: a computer-aided procedure for integrating benefits and costs in roadside safety intervention decision making[J]. Safety Science, 2015, 74(1): 195-205.
5 Roque C, Moura F, Cardoso J A O L. Detecting unforgiving roadside contributors through the severity analysis of ran-off-road crashes[J]. Accident Analysis & Prevention, 2015, 80(4): 262-273.
6 Lee C, Li X. Predicting driver injury severity in single-vehicle and two-vehicle crashes with boosted regression trees[J]. Transportation Research Record, 2015, 2514(1): 138-148.
7 Park J, Abdel-Aty M, Lee J. Use of empirical and full Bayes before-after approaches to estimate the safety effects of roadside barriers with different crash conditions[J]. Journal of Safety Research, 2016, 58(6): 31-40.
8 Hou Qin-zhong, Huo Xiao-yan, Leng Jun-qiang, et al. Examination of driver injury severity in freeway single-vehicle crashes using a mixed logit model with heterogeneity-in-means[J]. Physica A: Statistical Mechanics and its Applications, 2019,531: 121760.
9 Li Zhen-ning, Yu-sheng Ci, Chen Cong, et al. Investigation of driver injury severities in rural single-vehicle crashes under rain conditions using mixed logit and latent class models[J]. Accident Analysis & Prevention, 2019, 124(3): 219-229.
10 高海龙, 李长城. 路侧安全设计指南[M]. 北京: 人民交通出版社, 2008.
11 方勇, 郭忠印, 李志勇. 双车道公路路侧环境客观安全性评估模型[J]. 同济大学学报:自然科学版, 2013, 41(7): 1025-1030.
Fang Yong, Guo Zhong-yin, Li Zhi-yong. Assessment model for roadside environment objective safety on two-lane highway[J]. Journal of Tongji University (Natural Science), 2013, 41(7): 1025-1030.
12 龙科军, 李寅, 雷正保, 等. 基于加速度严重指数的公路路侧危险度评估[J]. 中国公路学报, 2013, 26(3): 143-149.
Long Ke-jun, Li Yin, Lei Zheng-bao, et al. Evaluating roadside hazard rating based on acceleration severity index[J]. China Journal of Highway and Transport, 2013, 26(3): 143-149.
13 陈慧, 张绍理, 刘志刚, 等. 基于AHP方法的山区等级公路路侧防护措施设置研究[J]. 中外公路, 2014, 34(6): 285-288.
Chen Hui, Zhang Shao-li, Liu Zhi-gang, et al. Setting of roadside protection measures of mountain grade highway based on AHP method[J]. Journal of China and Foreign Highway, 2014, 34(6): 285-288.
14 . 公路交通安全设施设计规范[S].
15 . 公路路线设计规范[S].
16 Riser. European best practice for roadside design: guidelines for roadside infrastructure on new and existing roads[R]. Gothenburg:Chalmers University of Technology,2005.
17 EN 1317-2: 1998. Road restraint systems—part 2: performance classes, impact test acceptance criteria and test methods for safety barriers[S].
18 江亮, 贺宜. 电动两轮车风险驾驶行为及事故影响因素分析[J]. 吉林大学学报:工学版, 2019, 49(4): 1107-1113.
Jiang Liang, He Yi. Risky driving behavior and influencing factors analysis for electric two-wheeler[J]. Journal of Jilin University (Engineering and Technology Edition), 2019, 49(4): 1107-1113.
19 高继东, 曾必强, 彭伟. 电动自行车与轿车碰撞中骑车人的伤害特征[J]. 吉林大学学报:工学版, 2016, 46(6): 1786-1791.
Gao Ji-dong, Zeng Bi-qiang, Peng Wei. Cyclist injury collision between car and electric bicycle[J]. Journal of Jilin University (Engineering and Technology Edition), 2016, 46(6): 1786-1791.
20 Jr Ross H E, Sicking D L, Zimmer R A, et al. Recommended Procedures for the Safety Performance Evaluation of Highway Features[M]. Washington DC: Transportation Research Board National Research Council, 1993.
21 . 道路交通事故车辆速度鉴定[S].
22 王辰. 基于PC-CRASH的汽车-护栏事故再现研究[D]. 长春: 吉林大学交通学院, 2014.
Wang Chen. A study on PC-CRASH reconstructing vehicle-guardrail accident[D]. Changchun: College of Traffic and Transportation, Jilin University, 2014.
23 张维刚, 胡高贤. 土基中波形梁护栏立柱的有限元模型研究[J]. 公路交通科技, 2007(7): 143-146.
Zhang Wei-gang, Hu Gao-xian. Finite element model of a w-beam guardrail post mounted in soil[J]. Journal of Highway and Transportation Research and Development, 2007(7): 143-146.
24 . 公路波形梁钢护栏[S].
25 . 碳素结构钢技术条件[S].
26 高峰, 刘江, 杨新刚, 等. 基于Fisher最优分割法的机床热关键点优化研究[J]. 仪器仪表学报, 2013, 34(5): 1070-1075.
Gao Feng, Liu Jiang, Yang Xin-gang, et al. Study on optimization of thermal key points for machine tools based on fisher optimal segmentation method[J]. Chinese Journal of Scientific Instrument, 2013, 34(5): 1070-1075.
27 周源, 杜俊飞, 王子鸿, 等. 基于多种函数拟合的自适应最优分割法[J]. 统计与决策, 2019, 35(13): 65-68.
Zhou Yuan, Du Jun-fei, Wang Zi-hong, et al. Adaptive optimal partition method based on multi-function fitting[J]. Statistics & Decision, 2019, 35(13): 65-68.
[1] 王露,刘玉雯,陈红. 侧风下峡谷桥隧连接段汽车的行驶特性[J]. 吉林大学学报(工学版), 2019, 49(3): 736-748.
[2] 代存杰,李引珍,马昌喜,柴获,牟海波. 不确定条件下危险品配送路线多准则优化[J]. 吉林大学学报(工学版), 2018, 48(6): 1694-1702.
[3] 王芳荣, 郭柏苍, 金立生, 高琳琳, 岳欣羽. 次任务驾驶安全评价指标筛选及其权值计算[J]. 吉林大学学报(工学版), 2017, 47(6): 1710-1715.
[4] 谭立东, 刘丹, 李文军. 基于蝇复眼的交通事故现场全景图像阵列仿生设计[J]. 吉林大学学报(工学版), 2017, 47(6): 1738-1744.
[5] 李显生, 孟祥雨, 郑雪莲, 程竹青, 任圆圆. 非满载罐体内液体冲击动力学特性[J]. 吉林大学学报(工学版), 2017, 47(3): 737-743.
[6] 王占中, 赵利英, 曹宁博. 基于多层编码遗传算法的危险品运输调度模型[J]. 吉林大学学报(工学版), 2017, 47(3): 751-755.
[7] 徐进, 陈薇, 周佳, 罗骁, 邵毅明. 汽车转向盘操作与驾驶负荷的相关性[J]. 吉林大学学报(工学版), 2017, 47(2): 438-445.
[8] 郭应时, 付锐, 赵凯, 马勇, 袁伟. 驾驶人换道意图实时识别模型评价及测试[J]. 吉林大学学报(工学版), 2016, 46(6): 1836-1844.
[9] 孙璐, 徐建, 崔相民. 面板数据模型分析及交通事故预测[J]. 吉林大学学报(工学版), 2015, 45(6): 1771-1778.
[10] 王喆, 杨柏婷, 刘昕, 刘群, 宋现敏. 基于模糊聚类的驾驶决策判别[J]. 吉林大学学报(工学版), 2015, 45(5): 1414-1419.
[11] 马勇, 石涌泉, 付锐, 郭应时. 驾驶人分心时长对车道偏离影响的实车试验[J]. 吉林大学学报(工学版), 2015, 45(4): 1095-1101.
[12] 徐建, 孙璐. 解决交通事故数据分析中零值问题的模型[J]. 吉林大学学报(工学版), 2015, 45(3): 769-775.
[13] 金立生, 王岩, 刘景华, 王亚丽, 郑义. 基于Adaboost算法的日间前方车辆检测[J]. 吉林大学学报(工学版), 2014, 44(6): 1604-1608.
[14] 金立生,牛清宁,刘景华,秦彦光,吕欢欢. 不同道路线形下驾驶人认知分散状态监测[J]. 吉林大学学报(工学版), 2014, 44(3): 642-647.
[15] 詹伟, 吕庆, 尚岳全. 高速公路隧道群交通事故灰色马尔可夫预测[J]. 吉林大学学报(工学版), 2014, 44(01): 62-67.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!