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山区公路驾驶视觉信息量计算方法研究
引用本文:孟云伟,陈磊,刘博航,陈炳阳,潘晓东. 山区公路驾驶视觉信息量计算方法研究[J]. 交通运输系统工程与信息, 2020, 20(5): 45-50
作者姓名:孟云伟  陈磊  刘博航  陈炳阳  潘晓东
作者单位:1. 重庆交通大学 交通运输学院,重庆 400074;2. 石家庄铁道大学 交通运输学院 河北省交通安全与控制省级重点实验室,石家庄 050043;3. 广西北部湾投资集团有限公司,南宁 530029; 4. 同济大学 交通运输工程学院,上海 201804
基金项目:教育部人文社会科学研究青年基金/ Foundation of Humanities and Social Sciences from Ministry of Education, China(19YJCZH121);重庆市自然科学基金(基础研究与前沿探索专项)/ Natural Science Foundation of Chongqing, China (cstc2019jcyj-msxmX0342);河北省交通安全与控制重点实验室开放课题/ Open Subject of Traffic Safety and Control Lab in Hebei Province(JTKY 2019005).
摘    要:
为解决山区公路中驾驶视觉信息量难以量化的问题,对驾驶视野图像进行分割,根 据HSV颜色模型,提取视野图像的色调、饱和度、亮度值,再结合车速值,在驾驶视觉心理负荷的基础上,提出山区公路路域环境下的驾驶视觉信息量计算方法.通过实车实验,进行数据采集,并验证计算方法.计算结果表明,在半郁闭型空间行驶时,接收的视觉信息量最大;在郁闭型空间中,接收的信息量最小.计算结果与被试实际感受具有一致性,说明本文提出的驾驶视觉信息量计算方法具有可行性,可为路域环境的合理布设提供一定的技术参考.

关 键 词:交通工程  山区公路  驾驶视觉  信息量计算  HSV颜色模型  视觉心理负荷  
收稿时间:2020-04-01

Calculation Method of Visual Information for Driver in Mountainous Highway
MENG Yun-wei,CHEN Lei,LIU Bo-hang,CHEN Bing-yang,PAN Xiao-dong. Calculation Method of Visual Information for Driver in Mountainous Highway[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(5): 45-50
Authors:MENG Yun-wei  CHEN Lei  LIU Bo-hang  CHEN Bing-yang  PAN Xiao-dong
Affiliation:1. College of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, China; 2. Key Laboratory of Traffic Safety and Control of Hebei Province, School of Traffic and Transportation Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China; 3. Guangxi Beibu Gulf Investment Group Co., Ltd, Nanning 530029, China; 4. College of Transportation Engineering, Tongji University, Shanghai 201804, China
Abstract:
In order to quantify the amount of driving visual information in mountain highway, driving vision images are first segmented, the HSV color model is used to extract the hue, saturation and brightness values of the vision image, and the driving visual information calculation method of mountain highway is proposed based on driving vision psychological load. A real vehicle experiment is carried out, then the relevant data are collected, and the above calculation method is used and verified. The results show that the visual information received is the largest when driving in the semi closed space, and the one is the smallest in the closed space. The calculated results are consistent with the actual feelings of the test driver. The calculation method of driving visual information is feasible and can provide some technical reference for the reasonable layout of the road environment.
Keywords:traffic engineering  mountainous highway  driving visual  information calculation  HSV color model  visual psychological load  
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