中国安全科学学报 ›› 2018, Vol. 28 ›› Issue (2): 21-27.doi: 10.16265/j.cnki.issn1003-3033.2018.02.004

• 安全人体学 • 上一篇    下一篇

摩托车驾驶员闯红灯的行为意向研究

杨鸿泰1,2 副教授, 苏帆1, 刘小寒1, 濮莉3 讲师, 李延来1,2 教授, 刘昱岗**1,2 教授   

  1. 1 西南交通大学 交通运输与物流学院,四川 成都 610031;
    2 西南交通大学 综合交通运输智能化国家地方联合工程实验室,四川 成都 610031;
    3 西南交通大学 建筑与设计学院,四川 成都 610031
  • 收稿日期:2017-11-17 修回日期:2018-01-09 出版日期:2018-02-28 发布日期:2020-11-17
  • 通讯作者: ** 刘昱岗(1978—),男,湖南株洲人,博士,教授,主要从事城市及区域交通规划方面的研究。E-mail:yugangliu@home.swjtu.edu.cn。
  • 作者简介:杨鸿泰 (1987—),男,山东潍坊人,博士,副教授,主要从事交通安全、出行需求分析与预测等方面的研究。E-mail: yanghongtai@swjtu.cn。
  • 基金资助:
    山地城市交通系统与安全重庆市重点实验室开放基金资助(KTSS201605); 中国博士后科学基金资助(2016M600749);同济大学道路与交通工程教育部重点实验室开放基金资助(K201603);中央高校基本科研业务费专项资金资助(2682017CX019)。

Study on motorcycle drivers' intention to run red light

YANG Hongtai1,2, SU Fan1, LIU Xiaohan1, PU Li3, LI Yanlai1,2, LIU Yugang1,2   

  1. 1 School of Transportation and Logistics, Southwest Jiaotong University, Chengdu Sichuan 610031, China;
    2 National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu Sichuan 610031, China;
    3 School of Architecture and Design, Southwest Jiaotong University, Chengdu Sichuan 610031, China
  • Received:2017-11-17 Revised:2018-01-09 Online:2018-02-28 Published:2020-11-17

摘要: 为提高道路交通安全水平,基于计划行为理论(TPB)研究摩托车驾驶员闯红灯的行为意向。设计调查问卷,获得160份有效样本;采用最优子集法筛选TPB基本变量、扩展变量和人口统计学变量,得到包含态度、危险认知、过去行为、预期情感、是否有汽车驾照和是否发生过交通事故等6个变量的最优子集;使用分层回归分析最优子集对闯红灯行为意向的解释能力,并提出相应的交通安全干预措施。结果表明:该子集可以解释闯红灯行为意向方差的29.6%,态度对闯红灯行为意向有最显著的正向影响,危险认知对闯红灯行为意向有显著的负向影响,过去行为和是否有汽车驾照在显著性水平为0.1时也对该意向具有显著的正向影响。应重点从纠正摩托车驾驶员对闯红灯的态度、提高危险认识和加强交管部门监管等方面,制定安全干预措施。

关键词: 交通安全, 计划行为理论(TPB), 摩托车, 闯红灯行为意向, 最优子集法

Abstract: In order to improve the road safety, this paper studies red light running behavior intentions of motorcycle users by employing TPB. A survey questionnaire was designed and 160 valid responses were received. Best subset method was used to gain a best variable subset including attitude, perceived risk, past behavior, anticipated affect, license status and history of traffic accidents. Hierarchical regression was constructed to understand the explanatory power of the best subset with respect to red light running behavior intention, and related traffic safety interventions were presented. The results revealed that the best subset can explain 29.6% of the variance of the intention, attitude has the most significant positive effect on the intention, perceived risk has a significant negative effect on intention, and past behavior and license status also have significant positive effects at 0.1 signicance level, and that traffic safety intervention measures should be formulated by focusing on attitude and perceived risk of motorcycle users towards RLR behavior and regulations coming from traffic management departments.

Key words: traffic safety, theory of planned behavior(TPB), motorcycle, red light running behavior intention, best subset selectio

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