考虑驾驶员生理信息的城市交叉口风险评估方法
A risk evaluation method for urban intersections considering drivers' physiological information
陈桂珍 1程慧婷 2朱才华 1李昱燃 1李岩1
作者信息
- 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
- 折叠
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.
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.
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Key words
transportation planning and management/physiological indicators/urban intersections/risk assessment/entropy weight method/K-means clustering/risk matrix引用本文复制引用
基金项目
国家自然科学基金(51408049)
陕西省自然科学基础研究计划(2020JM-237)
出版年
2024
NETL
NSTL
万方数据