[1]冯忠祥,张秀伟,储灿辉.视觉遮挡条件下儿童过街危险感知类型判定方法[J].长安大学学报(自然科学版),2024,44(2):123-135.[doi:10.19721/j.cnki.1671-8879.2024.02.012]
　FENG Zhong-xiang,ZHANG Xiu-wei,CHU Can-hui.Determination of perceived types of street crossing hazards for children under visual occlusion conditions[J].Journal of Chang’an University (Natural Science Edition),2024,44(2):123-135.[doi:10.19721/j.cnki.1671-8879.2024.02.012]
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视觉遮挡条件下儿童过街危险感知类型判定方法()
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长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
第44卷
期数:
2024年2期
页码:
123-135
栏目:
交通工程
出版日期:
2024-03-01

文章信息/Info

Title:
Determination of perceived types of street crossing hazards for children under visual occlusion conditions
文章编号:
1671-8879(2024)02-0123-13
作者:
冯忠祥; 张秀伟; 储灿辉
(合肥工业大学 汽车与交通工程学院,安徽 合肥 230009)
Author(s):
FENG Zhong-xiang;  ZHANG Xiu-wei;  CHU Can-hui
(School of Automobile and Traffic Engineering, Hefei University of Technology, Hefei 230009, Anhui, China)
关键词:
交通工程;  儿童;  试验研究;  危险感知类型;  线性判别分析;  视野遮挡
Keywords:
traffic engineering;  child;  experimental research;  hazard perception type;  linear discriminant analysis;  visual field occlusion
分类号:
U491
DOI:
10.19721/j.cnki.1671-8879.2024.02.012
文献标志码:
A
摘要:
为了解儿童在视觉遮挡条件下过街的视觉注意力特征,对儿童的危险感知类型进行划分,招募48名儿童完成危险感知能力测试试验,收集儿童视觉注意力特征等信息,基于危险感知效用量化方法,通过主观危险感知度和情境客观危险度量化儿童危险感知效用值,借助k-means聚类方法,将儿童在视野遮挡测试情境下的288个危险感知效用值用肘部法、轮廓系数法和戴维斯-波尔丁指数法3种方法确定最佳簇数为3,因此将儿童危险感知类型划分为谨慎型、均衡型和激进型。从儿童视觉注意力特征、人口特征和道路环境特征方面选取危险感知类型特征因素,通过机器学习构建线性判别分析模型(LDA),并与随机森林、k近邻、朴素贝叶斯、BP神经网络和径向基函数神经网络5种常见的分类模型进行效果对比,将70%的数据作为训练集用于模型学习,将30%的数据作为测试集以测试模型,通过模型分类准确度和精确度、召回率、F1分数的宏观平均值比较各模型的分类性能。研究结果表明:LDA模型的分类准确率达到83.91%,模型的泛化能力最佳,最适合儿童过街危险感知判定模型的构建。研究结果对不同危险感知类型的儿童群体差异性进行了阐述,有助于了解儿童的个体差异,有望进一步指导道路安全教育的个性化和定制化发展。
Abstract:
In order to characterize children's visual attention for street crossing under visually occluded conditions and to classify the types of hazard perceptions of children, 48 children were recruited to complete the risk perception ability test experiment, and information such as children's visual attention characteristics were collected. Based on the risk perception utility quantification method, the risk perception utility values of children were quantified by children's subjective risk perception degree and situational objective risk degree. With the help of k-means clustering method, the best cluster number of 288 risk perception utility values of children in the visual field occlusion test situation was determined by elbow method, contour coefficient method and DBI index method, so the types of children's risk perception were divided into cautious type and DBI index method. The characteristics of risk perception types were selected from the aspects of children's visual attention characteristics, demographic characteristics and road environment characteristics.Linear discriminant analysis model(LDA)was constructed by machine learning and the results were compared with five common classification models, namely random forest, k nearest neighbor, naive Bayes, BP neural network and radial basis function neural network. 70% of the data were used as training sets for model learning, and 30% of the data were used as test sets to test the model. The classification performance of the models was compared by macro-averages of model classification accuracy and precision, recall, and F1 score. The results show that the classification accuracy ofLDA reaches 83.91%, and the model has the best generalization ability, which is most suitable for the construction of children's risk perception judgment model. The research results illustrate the group differences of children with different types of risk perception, which is helpful to understand the individual differences of children and is expected to further guide the individualized and customized development of road safety education.9 tabs, 10 figs, 26 refs.

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备注/Memo

备注/Memo:
收稿日期:2023-10-19
基金项目:国家自然科学基金项目(52272345,71971073); 安徽省住房城乡建设科学技术计划项目(2021-YF43)
作者简介:冯忠祥(1982-),男,安徽含山人,教授,工学博士,E-mail:fzx@hfut.edu.cn。
更新日期/Last Update: 2024-03-01