中文核心期刊
CSCD来源期刊
中国科技核心期刊
RCCSE中国核心学术期刊
重庆交通大学学报（自然科学版）

重庆交通大学学报（自然科学版） ›› 2025, Vol. 44 ›› Issue (10): 65-73.DOI: 10.3969/j.issn.1674-0696.2025.10.09

• 交通+大数据人工智能 • 上一篇    

青年货车驾驶人危险驾驶行为影响因素分析

陈红1，刘洋1，梁子君2，肖赟2，李琛3   

  1. (1. 长安大学 运输工程学院，陕西 西安 710064；2. 合肥大学 城市建设与交通学院，安徽 合肥 230601； 3. 中交第一公路勘察设计研究院有限公司，陕西 西安 710075)
  • 收稿日期:2024-11-10 修回日期:2025-06-20 发布日期:2025-11-06
  • 作者简介:陈红(1963—)，女，湖南湘潭人，教授，博士，主要从事交通运输规划与管理方面的的研究。E-mail：glch@chd.edu.cn
  • 基金资助:
    陕西省交通运输厅2021年度交通科研项目(21-42X)；安徽省自然科学基金项目(2208085ME147)

Influencing Factors of Risky Driving Behavior of Young Truck Drivers

CHEN Hong1，LIU Yang1，LIANG Zijun2，XIAO Yun2，LI Chen3   

  1. (1. College of Transportation Engineering， Changan University， Xian 710064， Shaanxi， China； 2. College of Urban Construction and Transportation， Hefei University， Hefei 230601， Anhui， China； 3. CCCC First Highway Consultants Co., Ltd., Xian 710075， Shaanxi， China)
  • Received:2024-11-10 Revised:2025-06-20 Published:2025-11-06

摘要： 探析青年货车驾驶人危险驾驶行为的影响机制对于提高道路运输行车安全性具有重要意义，基于计划行为理论构建因果图模型，通过问卷调查收集312份职业货车驾驶人数据，综合结构方程模型与贝叶斯网络两种因果推断方法分析心理影响机制。结果表明：不同性别、驾驶时长、违规频率及交通事故经历的青年货车驾驶人的危险驾驶行为频率存在显著差异；扩展计划行为理论模型具有良好的解释力；行为意向、知觉行为控制和风险感知对危险驾驶行为有显著影响，其中行为意向影响效应最大，风险感知为负向影响；17.1%的青年货车驾驶人具有高水平危险驾驶行为；当知觉行为控制和行为意向分别由低状态变为高状态，高水平危险驾驶行为的可能性分别增加了16.1%和32.1%的概率。

关键词: 交通运输工程；危险驾驶行为；青年货车驾驶人；计划行为理论；结构方程模型；贝叶斯网络

Abstract: Exploring the influencing mechanism of risky driving behavior of young truck drivers is of great significance for improving the safety of road transportation. A causal diagram model was constructed based on the theory of planned behavior (TPB). Data from 312 professional truck drivers were collected through a questionnaire survey, and two causal inference methods, namely structural equation model (SEM) and Bayesian network (BN), were integrated to analyze the psychological influencing mechanisms. The results show that: there are significant differences in the frequency of risky driving behaviors of young truck drivers of different genders, driving hours, violation frequencies and crash experience. The extended TPB model demonstrates strong explanatory power. Behavioral intention, perceived behavioral control, and risk perception have a significant impact on risky driving behavior, with behavioral intention having the greatest effect and risk perception having a negative impact. Additionally, 17.1% of young truck drivers exhibit high levels of risky driving behaviors. When perceived behavioral control and behavioral intention shift from a low state to a high state, the probability of high-level risky driving behavior increases by 16.1% and 32.1%, respectively.

Key words: traffic and transportation engineering; risky driving behavior; young truck drivers; theory of planned behavior; structural equation model; Bayesian network

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