智能汽车变道盲区影像对驾驶员认知负荷与安全性的影响
Effects of Blind Area Display of Intelligent Vehicles on Drivers'Cognitive Load and Safety During Lane Change
岳李圣飒 1潘昱蓉 1孙剑 1朱奕昕 1崔晓烨 1李奕劼1
作者信息
- 1. 同济大学道路与交通工程教育部重点实验室,上海 201804
- 折叠
摘要
智能汽车变道盲区影像在为驾驶员提供更多环境信息的同时也可能增加驾驶员的认知负荷.针对这一问题,提出改进AttenD算法,建立认知负荷与驾驶员注视点分布的关系模型,对3种智能汽车品牌车辆开展实车路测实验,分析多种外部条件下驾驶员与不同变道盲区影像交互过程中注视特征、驾驶行为特征以及认知负荷的差异.结果表明,增大盲区影像面积、提高盲区影像面积占中控屏面积的比例、减少扫视路径冗余能降低变道过程中的认知负荷.
Abstract
While providing more environmental information to drivers,the blind area display of intelligent vehicles during lane changes may also increase the driver's cognitive load.To address this issue,this paper presents an improved AttenD algorithm,which establishes a relationship model between the cognitive load and distribution of drivers'fixation points.Field tests were conducted on three intelligent brand cars,and differences in drivers'gaze characteristics,driving behavior characteristics,and cognitive load during the interaction between the driver and lane-changing blind area display were analyzed.Results show that increasing the size of the blind area display,increasing the blind area's ratio on the center control panel,and minimizing unnecessary scanning movements can reduce the cognitive load and improve the safety during lane changes.
关键词
智能汽车/变道盲区影像/认知负荷/变道安全/AttenD算法Key words
intelligent vehicle/lane-changing blind area display/cognitive load/lane change safety/AttenD algorithm引用本文复制引用
基金项目
国家自然科学基金(52125208)
上海市软科学研究计划(23692123300)
出版年
2024
国家科技期刊平台
NSTL
万方数据