Journal of South China University of Technology(Natural Science Edition) ›› 2024, Vol. 52 ›› Issue (9): 142-152.doi: 10.12141/j.issn.1000-565X.230579

• Traffic & Transportation Engineering • Previous Articles     Next Articles

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

CHEN Bingshuo1(), LI Yang2(), ZHAO Xiaohua1, LIU Xiaoming1   

  1. 1.School of Urban Transportation, Beijing University of Technology, Beijing 100124, China
    2.Department of Road Traffic Management, Beijing Police College, Beijing 102202, China
  • Received:2023-09-14 Online:2024-09-25 Published:2024-01-05
  • Contact: 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
  • About author: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
  • Supported by:
    Beijing Municipal Education Commission Science and Technology Plan General Project(KM202014019001)

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

CLC Number: