Journal of Transportation Systems Engineering and Information Technology ›› 2020, Vol. 20 ›› Issue (2): 151-156.

• Systems Engineering Theory and Methods • Previous Articles     Next Articles

Defensive Driving Behavior Analysis Model with Follow-up Surveys

GAO Hong-li1, 2, 3, GAO Li-ying4, YANGWei-cheng5, FAN Shuang-shuang1, 6   

  1. 1. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 611756, China; 2. School of Automobile and Transportation, Xihua University, Chengdu 610039, China; 3. Vehicle Measurement, Control and Safety Key Laboratory of Sichuan Province, Chengdu 610039, China; 4. Department of Automotive Engineering, Sichuan Vocational and Technical College of Communications, Chengdu 611130, China; 5. Chengdu Textile College, Chengdu 611731, China; 6. Sichuan(Chengdu)Consulting Service Center for Academicians of Chinese Academy of Science & Engineering, Chengdu 610041, China
  • Received:2019-10-05 Revised:2019-12-08 Online:2020-04-25 Published:2020-04-30

基于持续跟踪调查的防御性驾驶行为分析模型

高红丽*1, 2, 3,高丽英4,杨炜程5,范双双1, 6   

  1. 1. 西南交通大学交通运输与物流学院,成都 611756;2. 西华大学汽车与交通学院,成都 610039; 3. 汽车测控与安全四川省重点实验室,成都 610039;4. 四川交通职业技术学院汽车工程系,成都 611130; 5. 成都纺织高等专科学校,成都 611731;6.四川(成都)两院院士咨询服务中心,成都 610041
  • 作者简介:高红丽(1976-),女,山东曹县人,副教授,博士生.
  • 基金资助:

    国家自然科学基金/ National Natural Science Foundation of China(61873216).

Abstract:

This study mainly deals with the problem of quantitatively measuring psychological process of defensive driving behavior. The defensive driving behavior scale is designed by defining the concept of defensive driving behavior. The analysis model was developed based on the theory of planned behavior (TPB). In the model, the prior behaviors, behavioral attitude, subjective norms, and perceived control are predictive variables; the behavioral intention is intermediary variable, and the subsequent behaviors are outcome variables. Questionnaire data were collected from non- professional drivers at two time points separated by three months. TPB variables, demographic information, and prior behavior were measured at the first survey and subsequent behavior was measured at the second survey. 213 valid and matching questionnaires were obtained from two surveys. The analysis results show that, subjective norms have no significant impact on defensive driving intention. The perceived control (0.40), behavior attitude (0.29), and past driving behavior (0.26) have positive impact on behavior intention. Behavioral attitude, perceived control, and prior behaviors can explain subsequent behaviors to some extent through the behavioral intention (0.36).

Key words: traffic engineering, defensive driving behavior, theory of planned behavior, non- professional drivers, follow-up survey

摘要:

为解决防御性驾驶行为心理作用过程缺少定量描述的问题,在界定防御性驾驶行为内涵的基础上,设计防御性驾驶行为量表. 基于计划行为理论,构建以过去防御性驾驶行为、行为态度、主观规范和知觉行为控制为预测变量,行为意图为中介变量,后续防御性驾驶行为为结果变量的分析模型. 对非职业驾驶员在间隔3 个月的两个时间点跟踪调查,第1 次调查内容包括过去防御性驾驶行为、TPB变量、个人基本信息,第2 次调查包括后续防御性驾驶行为和个人基本信息,获得两次调查数据完全匹配的有效问卷213 份. 对有效数据分析显示:主观规范对防御性驾驶行为意向不显著,知觉行为控制、行为态度和过去防御性驾驶行为对防御性驾驶行为意向影响值分别为0.40、0.29 和0.26;行为态度、知觉行为控制和过去驾驶行为通过行为意向(0.36),可以在一定程度上对后续行为进行解释.

关键词: 交通工程, 防御性驾驶行为, 计划行为理论, 非职业驾驶员, 跟踪调查

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