华南理工大学学报(自然科学版) ›› 2021, Vol. 49 ›› Issue (3): 131-138,148.doi: 10.12141/j.issn.1000-565X.200094

所属专题: 2021年交通运输工程

• 交通运输工程 • 上一篇    下一篇

基于雾天高速车路协同模拟驾驶的驾驶人视觉信息加工模式

李雪玮 赵晓华 李振龙 杨家夏 荣建   

  1. 北京工业大学 交通工程北京市重点实验室,北京 100124
  • 收稿日期:2020-03-02 修回日期:2020-09-20 出版日期:2021-03-25 发布日期:2021-03-01
  • 通信作者: 李振龙(1976-),男,博士,副教授,主要从事智能交通及驾驶行为研究. E-mail:lzl@bjut.edu.cn
  • 作者简介:李雪玮(1993-),女,博士生,主要从事驾驶行为及智能交通研究
  • 基金资助:
    国家国际科技合作专项资助 ( 2017YFE0134500) ; 汽车安全与节能国家重点实验室开放基金资助项目 ( KF2017) 

Driver's Visual Information Processing Mode in Foggy Highway Cooperative Vehicle-Infrastructure System Environment Based on Simulated Driving

LI Xuewei ZHAO Xiaohua LI Zhenlong YANG Jiaxia RONG Jian   

  1. Beijing Key Laboratory of Traffic Engineering,Beijing University of Technology,Beijing 100124,China
  • Received:2020-03-02 Revised:2020-09-20 Online:2021-03-25 Published:2021-03-01
  • Contact: 李振龙(1976-),男,博士,副教授,主要从事智能交通及驾驶行为研究. E-mail:lzl@bjut.edu.cn
  • About author:李雪玮(1993-),女,博士生,主要从事驾驶行为及智能交通研究
  • Supported by:
    Supported by the International Science & Technology Cooperation Program of China ( 2017YFE0134500)

摘要: 为探讨雾天高速公路车路协同系统信息介入对驾驶人视觉信息加工模式的影响,首先,依托驾驶模拟平台设计了车路协同环境下的雾天高速公路驾驶模拟实验,获取驾驶人的视觉行为参数; 其次,将前方道路定义为关键兴趣区域,分别提取驾驶人在全局水平及兴趣区域的注视、扫视等显性视觉特性指标,并分析其分布规律; 最后,采用因子分析方法获取信息提取因子、感知密度因子及信息搜索因子共 3 个公因子,以表征雾天高速公路车路协同系统作用下驾驶人的视觉信息加工模式。结果表明,车路协同系统的应用会显著影响驾驶人的扫视行为及对前方道路的视觉资源分配,多元信息的介入改变了原有的信息分布,使驾驶员的信息提取效率提高,信息感知密度降低,信息搜索效率提高。文中研究结果可为车路协同系统人机交互终端的设计及安全应用提供理论参考和技术保障。

关键词: 车路协同, 模拟驾驶, 雾天预警, 视觉信息加工

Abstract: The aim of this paper is to explore the influence of the cooperative vehicle-infrastructure system in foggy highway on the driver's visual information processing mode. Firstly,based on the driving simulation platform,a cooperative vehicle-infrastructure system in foggy highway ( CVIS-HF) was designed to obtain the driver's visual behavior parameters. Next,the road ahead was defined as area of interest,and the driver's fixation,saccade and other explicit visual behavior indexes at the global level and area of interest were extracted and analyzed. Finally,three common factors,information extraction factor,perceptual density factor and information search,were obtained by using factor analysis method to characterize the driver's visual information processing mode under the effect of CVIS-HF. The results show that the application of CVIS-HF significantly affects the driver's scanning behavior and the allocation of visual resources for the road ahead. The original information distribution is changed by the intervention of cooperative vehicle-infrastructure system information,which improves the efficiency of information extraction and information search,but reduces the perceptual information density. The research results can provide theoretical reference and technical support for the design and safety application of human machine interface ( HMI) in cooperative vehicle-infrastructure system.

Key words: cooperative vehicle-infrastructure system, simulated driving, fog warning, visual information processing

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