吉林大学学报(工学版) ›› 2019, Vol. 49 ›› Issue (4): 1107-1113.doi: 10.13229/j.cnki.jdxbgxb20180189

• • 上一篇    

电动两轮车风险驾驶行为及事故影响因素分析

江亮1,2(),贺宜1,2()   

  1. 1. 武汉理工大学 智能交通系统研究中心,武汉 430063
    2. 武汉理工大学 水路公路交通安全控制与装备教育部工程研究中心,武汉 430063
  • 收稿日期:2018-03-05 出版日期:2019-07-01 发布日期:2019-07-16
  • 通讯作者: 贺宜 E-mail:1066345082@qq.com;heyi@whut.edu.cn
  • 作者简介:江亮(1979-),男,博士研究生. 研究方向:交通安全,交通工程. E-mail:1066345082@qq.com
  • 基金资助:
    国家自然科学基金项目(51605350)

Risky driving behavior and influencing factors analysis for electric two⁃wheeler

Liang JIANG1,2(),Yi HE1,2()   

  1. 1. Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China
    2. Engineering Research Center for Transportation Safety, Ministry of Education, Wuhan University of Technology, Wuhan 430063, China
  • Received:2018-03-05 Online:2019-07-01 Published:2019-07-16
  • Contact: Yi HE E-mail:1066345082@qq.com;heyi@whut.edu.cn

摘要:

为探究电动两轮车风险驾驶行为产生的原因及其影响因素,通过问卷调查方式对183位电动两轮车骑行者进行问卷调查,经过探索性因素分析(EFA)得到了包括风险驾驶行为、情绪状态、利他主义、风险感知能力、驾驶自信和冒险意识的6因子结构模型。研究了统计学信息、6因子与交通事故之间的相互关系,构建了基于Logistic回归的交通事故预测模型,利用验证性因素分析(CFA)对该模型进行了验证。研究表明:日均里程、风险驾驶行为、工作时长、冒险意识是影响交通事故的重要参数。

关键词: 交通运输系统工程, 电动两轮车, 驾驶行为, 交通事故, 影响因素, 致因分析

Abstract:

In order to explore the causes and influencing factors of risky driving behavior of electric two-wheeled vehicles, a questionnaire survey was conducted among 183 electric two-wheeled cyclists. After exploratory factor analysis (EFA), a 6-factor structural model was established. These factors include risk driving behavior, emotion State, altruism, risk perception, driving self-confidence and risk awareness. The relationship between statistical information, the 6 factors and traffic accidents were studied to establish a traffic accident prediction model based on Logistic regression. This model was validated by the Factor Analysis (CFA). Research shows that daily mileage, risk driving behavior, working hours, risk awareness are important parameters affecting traffic accidents.

Key words: engineering of communication and transportation system, electric two?wheeler, driving behavior, road accident, influencing factors, cause analysis

中图分类号: 

  • U121

表1

KMO和Bartlett检验"

检验方法数值
KMO检验0.849
巴特利特球度检验近似χ24149.884
df741
Sig.0.000

图1

碎石图"

表2

风险驾驶行为问卷信度检验结果"

序号问卷项目因子
123456
1日常工作强度0.871
2平时心态很放松0.873
3对已经发生的事情不担心0.870
4很容易适应新环境0.873
5担心坏事发生0.871
6担心所有的事情0.869
7遇事能保持冷静0.876
8很少抱怨0.871
9易发脾气0.870
10容易失落0.868
11喜欢刺激0.868
12喜欢尝试新事物0.871
13做事方式直接0.871
14做事不考虑后果0.868
15从不尝试滑翔和蹦极等危险运动0.871
16乐于帮助别人0.873
17人缘好,受欢迎0.874
18乐于关心其他人0.873
19与别人相处有困难0.870
20不喜欢为他人的事情浪费时间0.871
21不喜欢嘈杂热闹的音乐0.870
2222.即便在陌生道路上行驶,我也可以处理任何突发状况0.872
23我有能力处理行驶中的任何危险状况0.873
24与两侧高速行驶的车辆并排骑行0.866
25与前面车辆距离过近以至紧急情况难以停下来0.867
26不注意观察,骑车从支路直接插到主路上0.867
27拐弯速度过快以至失控0.867
28骑车不仅是为了送快件也是为了乐趣0.870
29骑(电动)摩托车让我很放松0.869
30为图方便,认为可以逆向行驶0.865
31认为如果车技好,可以超速0.865
32认为道路条件好,可以超速0.865
33直行或转弯时,不看后视镜观察后方情况0.866
34骑车转弯时不看红绿灯0.867
35为赶时间,在狭窄的车辆缝隙之间钻行0.865
36喜欢比其他车辆骑得更快0.867
37在晚上或者凌晨超速骑行0.866
38酒后骑车0.868
39骑车闯红灯0.866

表3

变量间相关性分析(样本容量n=183)"

序号12345678910
1年龄
2从业年限0.227
3日均骑行次数0.0730.204
4日均里程0.0450.0680.009
5工作时长0.0250.0100.0850.016
6风险驾驶行为0.0450.0590.0370.0300.136
7正面情绪状态0.0160.0440.1100.1170.0850.089
8利他主义0.0450.0040.0860.0770.1360.0360.046
9风险感知能力0.0410.0190.0270.0070.0340.0470.085*0.024
10驾驶自信0.0040.0800.0830.0410.0770.0590.0220.0140.014
11冒险意识0.0360.0740.0640.1110.0280.0900.0130.0350.0470.020

表4

Logistic回归分析结果"

变量BWalsSig.Exp (B)
风险驾驶行为0.9476.5820.0102.579
正面情绪状态1.0584.3160.0382.880
利他主义-0.3670.6850.4080.693
风险感知能力0.3260.8860.3471.386
驾驶自信-0.3750.7310.3930.687
冒险意识0.0550.0190.8911.056
年龄0.0530.7310.3931.055
从业年限0.0070.0100.9201.007
日均送快件数0.0000.0030.9561.000
日均里程-0.0430.8360.3600.958
工作时长0.0940.1470.7011.098
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