吉林大学学报(工学版) ›› 2024, Vol. 54 ›› Issue (5): 1277-1284.doi: 10.13229/j.cnki.jdxbgxb.20220755

• 交通运输工程·土木工程 • 上一篇    

考虑驾驶员生理信息的城市交叉口风险评估方法

陈桂珍1(),程慧婷2,朱才华1,李昱燃1,李岩1()   

  1. 1.长安大学 运输工程学院,西安 710064
    2.重庆交通职业学院 轨道交通学院,重庆 402247
  • 收稿日期:2022-06-18 出版日期:2024-05-01 发布日期:2024-06-11
  • 通讯作者: 李岩 E-mail:chenguizhen@chd.edu.cn;lyan@chd.edu.cn
  • 作者简介:陈桂珍(1994-),女,博士研究生. 研究方向:交通安全.E-mail: chenguizhen@chd.edu.cn
  • 基金资助:
    国家自然科学基金项目(51408049);陕西省自然科学基础研究计划项目(2020JM-237)

A risk evaluation method for urban intersections considering drivers' physiological information

Gui-zhen CHEN1(),Hui-ting CHENG2,Cai-hua ZHU1,Yu-ran LI1,Yan LI1()   

  1. 1.College of Transportation Engineering,Chang'an University,Xi'an 710064,China
    2.School of Rail Transportation,Chongqing Vocational College of Transportation,Chongqing 402247,China
  • Received:2022-06-18 Online:2024-05-01 Published:2024-06-11
  • Contact: Yan LI E-mail:chenguizhen@chd.edu.cn;lyan@chd.edu.cn

摘要:

为解决交叉口风险评估未充分考虑驾驶员状态和风险损失的问题,提出了一种综合风险概率和风险损失的风险评估方法。利用熵值法得出基于驾驶员生理信息的风险概率,基于能量转换定理确定直接风险损失,提出环境脆弱度确定间接风险损失;利用聚类算法得到风险损失和风险概率的等级,进而基于风险矩阵得到交叉口风险等级。分析西安市19个交叉口试验数据得出:交叉口风险等级划分为比较安全、一般安全、比较风险和非常风险4个等级,风险等级主要集中在比较风险级别。所提出的基于驾驶员生理信息的交叉口风险评估方法与试验驾驶员的感知相符,准确度达到90%,为驾驶员风险管理提供了新方法。

关键词: 交通运输规划与管理, 生理指标, 城市交叉口, 风险评估, 熵值法, K-means聚类, 风险矩阵

Abstract:

A risk assessment method that combines risk probability and risk loss has been established to address the problem of insufficient consideration of driver status and risk loss in intersection risk assessment. The entropy weight method is utilized to determine the risk probability based on drivers' physiological information, while direct risk loss is calculated using the energy conversion theorem, and indirect risk loss is identified through the introduction of environmental vulnerability metrics. To prioritize intersection risk, a clustering algorithm is applied to rank both risk probability and risk loss. Subsequently, the intersection risk rank is determined through a risk matrix analysis. Empirical using data from 19 intersections in Xi'an city demonstrates that intersection risk levels can be categorized into four tiers: relatively safe, generally safe, relatively risky, and very risky, with a predominant concentration in the relatively risky category. The proposed intersection risk assessment method based on drivers' physiological information matches the perceptions of test drivers with 90% accuracy, providing a new method for driver risk management.

Key words: transportation planning and management, physiological indicators, urban intersections, risk assessment, entropy weight method, K-means clustering, risk matrix

中图分类号: 

  • U491

图1

试验设置"

表1

生理指标体系"

指标类型指标渐进显著性差异显著性说明指标类型指标说明
眼动指标平均注视持续时间(AFD)0.304差异不显著注视类指标心电指标LF低频段功率
注视比例(FR)0.017差异显著LF norm规一化低频段功率
平均扫视持续时间(ASD)0.377差异不显著扫视类指标HF高频段功率
扫视比例(SR)0.356差异不显著HF norm规一化高频段功率
平均扫视幅度(ASA)0.627差异不显著LF/HFLF与HF比值
平均扫视速度(ASV)0.000差异显著MRRRR间期均值
平均眨眼持续时间(ABD)0.003差异显著眨眼类指标SDNNRR间期均方差
眨眼比例(BR)0.001差异显著
眨眼频率(BF)0.001差异显著

图2

城市交叉口风险评估框架"

图3

城市交叉口风险指标体系"

表2

城市交叉口风险概率模型各指标权重 (%)"

权重AFDBFSRASALF变化率HF变化率MRRSDNN流量静态
左转5.732.824.442.952.121.755.742.7237.0934.64
直行3.792.035.971.793.321.957.652.8342.5728.08
右转3.752.930.972.862.211.883.492.2155.4424.24

图4

3种转向下交叉口风险概率对比图"

表3

3种转向下的城市交叉口风险概率值划分阈值"

风险概率

非常

安全

比较

安全

一般

安全

比较

风险

非常

风险

左转0.0~0.150.15~0.450.45~0.550.55~0.750.75~1.00
直行0.0~0.150.15~0.250.25~0.450.45~0.750.75~1.00
右转0.0~0.150.15~0.400.40~0.500.50~0.750.75~1.00

表4

指标权重"

指标权重/%指标权重/%
交叉口车辆类型11.80时段7.70
交叉口大小10.20交叉口土地性质23.30
交叉口类型9.10交叉口周围行人数量8.90
道路上汽车数量6.20安全防护设施9.70
天气13.00

表5

交叉口风险损失事件分级标准"

风险损失等级直接风险损失/J

间接风险损失

(环境脆弱度)

风险损失分级事故损失
轻微0~12250~20~2450仅仅是车辆间轻微剐蹭,不会造成人员伤亡及财产损失
一般1225~25002~42450~10000一次造成轻伤1~2人,或者财产损失机动车不足1000元的事故,对非机动车不足200元的事故
较大2500~36004~610000~21600一次造成重伤1~2人或者轻伤3人以上10人以下,或者财产损失不足3万元的事故
重大>3600>6>21600一次造成死亡1~2人,或者重伤3人以上10人以下,或者财产损失3万元以上不足6万元的事故

图5

城市交叉口风险等级"

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