华南理工大学学报(自然科学版) >

2024 , Vol. 52 >Issue 9: 142 - 152

DOI: https://doi.org/10.12141/j.issn.1000-565X.230579

交通运输工程

老年驾驶人认知驾驶能力评价及影响因素研究

  • 陈兵硕 ,
  • 李洋 ,
  • 赵晓华 ,
  • 刘小明
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  • 1.北京工业大学 城市交通学院，北京 100124
    2.北京警察学院 道路交通管理系，北京 102202
陈兵硕（1995—），女，博士生，主要从事驾驶行为与安全研究。E-mail： bingshuo2018@163.com
李洋（1979—），男，博士，高级工程师，主要从事交通管理和交通法规研究。

收稿日期: 2023-09-14

  网络出版日期: 2024-01-03

基金资助

北京市教育委员会科技计划项目(KM202014019001)

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Study on Evaluation and Influencing Factors of Cognitive Driving Ability in Elderly Drivers

  • CHEN Bingshuo ,
  • LI Yang ,
  • ZHAO Xiaohua ,
  • LIU Xiaoming
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  • 1.School of Urban Transportation, Beijing University of Technology, Beijing 100124, China
    2.Department of Road Traffic Management, Beijing Police College, Beijing 102202, China
李洋（1979—），男，博士，高级工程师，主要从事交通管理和交通法规研究。E-mail： yang_li009@163.com

Received date: 2023-09-14

  Online published: 2024-01-03

Supported by

Beijing Municipal Education Commission Science and Technology Plan General Project(KM202014019001)

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摘要

我国老年驾驶人数量持续增长，驾驶人结构的变化给交通安全带来了挑战。相比于其他年龄段驾驶人，老年人生心理功能逐渐衰退，更容易发生交通事故。认知功能与驾驶安全表现显著相关。从注意反应能力、执行处理能力、空间感知能力3项认知功能领域出发，研究老年人驾驶特征，设计驾驶模拟实验风险事件，获得认知驾驶行为数据，分析青年人、中年人、老年人驾驶行为特征的差异性；采用主客观结合的方法确定指标权重，提出认知驾驶行为指数计算方法；以驾驶人属性和认知功能为自变量，以认知驾驶行为指数为因变量，建立广义线性混合模型，探究不同因素对认知驾驶能力的影响。结果表明年龄、周驾驶频率、自我调节和TMT-B（Trail Making Test-B）与认知驾驶行为指数显著相关，MMSE（Mini-Mental State Examination）为边缘显著相关；老年驾驶人的认知驾驶行为指数受个体特质影响较大；相较于老年人，青年人认知驾驶行为指数更差，中年人更好；周驾驶频率低的人比周驾驶频率高的人认知驾驶行为指数更好；自我调节频率为低和中的驾驶人，比频率为高的驾驶人认知驾驶行为指数更好；TMT-B测量认知正常的驾驶人比认知障碍驾驶人的认知驾驶行为指数更好。该研究从交通事故的人因机理角度出发，探究老年驾驶人面对的认知挑战，提出老年人认知驾驶行为指数计算方法并解析影响因素，为简化老年人驾驶适宜性评价程序、制定驾驶安全干预策略提供参考。

关键词： 老年驾驶人; 认知功能; 驾驶行为; 安全评价; 交通管理

本文引用格式

陈兵硕 , 李洋 , 赵晓华 , 刘小明 . 老年驾驶人认知驾驶能力评价及影响因素研究[J]. 华南理工大学学报(自然科学版), 2024 , 52(9) : 142 -152 . DOI: 10.12141/j.issn.1000-565X.230579

Abstract

The number of elderly drivers in China continues to grow, and the changes in the driver structure pose challenges to traffic safety. Compared to drivers in other age groups, elderly drivers’ psychological function gradually declines and they are more prone to traffic accidents. Cognitive function is significantly correlated with driving safety performance. Based on the driving characteristics of elderly people, this article started from three cognitive functional areas of attention response ability, executive processing ability, and spatial perception ability, and designed driving simulation experiments to obtain cognitive driving behavior data. It analyzed the differences in driving behavior characteristics among young people, middle-aged people, and elderly people. By combining subjective and objective methods to determine indicator, weights, a method for calculating the cognitive driving behavior index was proposed. A generalized linear mixed model was established with driver attributes and cognitive function as independent variables and cognitive driving behavior index as dependent variable to explore the impact of different factors on cognitive driving ability. The results showed that age, weekly driving frequency, self-regulation, and TMT-B (Trail Making Test-B) were significantly correlated with cognitive driving behavior index, with MMSE (Mini-mental State Examination) showing marginal significant correlation. The cognitive driving behavior index of elderly drivers was greatly influenced by individual traits. Compared to the elderly, the cognitive driving behavior index of young people was worse, while that of middle-aged people was better. People with lower weekly driving frequency had better cognitive driving behavior index than those with higher weekly driving frequency. Drivers with low and medium self-regulation frequencies have better cognitive driving behavior indices than those with high self-regulation frequencies. TMT-B measurement showed that the cognitive driving behavior index of drivers with normal cognition was better than those with cognitive impairment. Starting from the perspective of human factors in traffic accidents, this study explored the cognitive challenges faced by elderly drivers, proposed a calculation method for the cognitive driving behavior index of elderly people, and analyzed the influencing factors, providing reference for simplifying the evaluation process of elderly driving suitability and formulating driving safety intervention strategies.

Key words： elderly driver; cognitive function; driving behavior; safety evaluation; traffic management

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