基于组合赋权法的山区高速公路驾驶负荷模型  

Driving Workload Model of Mountain Expressway Based onCombinatorial Weighting Method

作　　者：尚婷[1] 易爱强 黄龙显 刘建 黄安 游宝 SHANG Ting;YI Ai-qiang;HUANG Long-xian;LIU Jian;HUANG An;YOU Bao(School of Traffic&Transportation,Chongqing Jiaotong University,Chongqing 400074,China;Chongqing High Speed Engineering Consulting Co.,Chongqing 404100,China)

机构地区：[1]重庆交通大学交通运输学院,重庆400074 [2]重庆高速工程顾问有限公司,重庆404100

出　　处：《科学技术与工程》2025年第11期4769-4775,共7页Science Technology and Engineering

基　　金：教育部人文社会科学研究青年基金(22YJCZH143);重庆市自然科学基金(CSTB2023NSCQ-MSX0742);重庆市研究生科研创新项目(CYS240477)。

摘　　要：为研究山区高速公路驾驶负荷,组织驾驶人自然驾驶试验,使用眼动仪获取驾驶人自然驾驶状态下的眼动数据。以瞳孔面积变化率、平均扫视时间、眨眼频率和注视时间占比为关键变量,使用组合赋权法建立驾驶负荷量化模型,揭示桥隧群、隧道群、隧道至互通小间距等山区高速公路典型场景驾驶负荷演变化规律。运用K-means聚类算法,确定基于欧式距离度量的不同等级驾驶负荷阈值,界定高驾驶负荷危险场景。结果表明:桥隧群桥梁类型、隧道群连接段长度、隧道至互通间距均显著影响驾驶负荷;驾驶负荷与桥梁大小呈正相关,与隧道群连接段长度、隧道至互通间距呈负相关;山区高速公路驾驶负荷高、中、低强度等级的阈值为0.54和0.26;大桥或特大桥组成的桥隧群、间距小于300 m的隧道群以及间距小于400 m的隧道至互通路段为高驾驶负荷危险场景;建议在隧道内应用公路隧道智能照明系统、隧道洞口设置减光构筑物,隧道至互通小间距场景可考虑在隧道内适宜区段设置允许换道区域。To investigate driving workload on mountainous expressways,a naturalistic driving study was conducted utilizing an eye tracker to capture drivers'eye movement data in a realistic driving environment.Employing the change rate of pupil area,average saccade time,blink frequency,and fixation time ratio as primary indicators,a quantitative driving workload model was formulated through a combined weighting approach.This model aimed to reveal the driving workload evolution mechanism in typical scenarios of mountain expressways such as bridge and tunnel clusters,tunnel clusters,and short distances between tunnels and intersections.A clustering algorithm was applied to determine the classification thresholds for driving workload,thereby identifying high-risk scenarios characterized by heightened workload.The results show that the types of bridges within bridge-tunnel groups,the length of connection sections between tunnel groups,and the proximity of tunnels to interchanges significantly influence driving workload.A positive correlation was observed between driving workload and bridge size,whereas driving workload exhibited a negative correlation with the length of connection sections between tunnel groups and the distance from tunnels to interchanges.The thresholds of high,medium and low intensity levels of driving workload on mountain expressway are 0.54 and 0.26.Scenarios with bridge-tunnel groups composed of large or super-large bridges,tunnel groups with distances less than 300 m,and tunnel-to-interchange sections with distances less than 400 m were classified as high-risk driving workload scenarios.It is advisable to implement an intelligent lighting system within expressway tunnels,establish light-reducing structures at tunnel entrances,and in scenarios where tunnels are located in close proximity to interchanges,consider installing designated lane-changing zones within suitable tunnel sections to facilitate smooth lane transitions.

关 键 词：驾驶负荷 山区高速公路 组合赋权法 自然驾驶试验 

分 类 号：U491.25[交通运输工程—交通运输规划与管理]