电动自行车事故和车牌使用影响因素分析

交通运输系统工程与信息 ›› 2017, Vol. 17 ›› Issue (3): 229-234.

电动自行车事故和车牌使用影响因素分析

周继彪¹，郭延永^{*2, 3}，吴瑶³，董升¹

1. 宁波工程学院建筑与交通工程学院，浙江宁波315211；2. 英属哥伦比亚大学应用科学学院土木工程系，加拿大温哥华V6T 1Z4；3. 东南大学交通学院，南京210096

收稿日期:2016-11-21 修回日期:2017-02-16 出版日期:2017-06-25 发布日期:2017-06-26
作者简介:周继彪(1986-)，男，山东菏泽人，讲师，博士.
基金资助:
浙江省公益技术应用研究计划项目/PublicWelfare Technology Application Foundation of Zhejiang Province, China (2016C33256)；浙江省自然科学基金/ Natural Science Foundation of Zhejiang Province, China (LY17E080013)；宁波市自然科学基金/Natural Science Foundation of Ningbo City, China (2015A610298).

Assessing Factors Related to E-bike Crash and E-bike License Plate Use

ZHOU Ji-biao ¹, GUO Yan-yong ^{2, 3}, WU Yao ³, DONG Sheng ¹

1. School of Civil and Transportation Engineering, Ningbo University of Technology, Ningbo 315211, China; 2. Department of Civil Engineering, Faculty of Apply Since, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada; 3. School of Transportation, Southeast University, Nanjing 210096, China

Received:2016-11-21 Revised:2017-02-16 Online:2017-06-25 Published:2017-06-26

摘要/Abstract

摘要：

为分析电动自行车事故和车牌使用影响因素，采用问卷调查和电话访谈方式采集了宁波市862 个电动自行车用户有效样本，利用统计学方法构建了Bivariate Probit (BP)联立方程模型，计算了显著影响因素的边际效应，量化分析了电动自行车事故和车牌使用影响因素效用，并检验了两者之间潜在的关联关系.结果表明：BP模型不仅可以识别电动自行车事故和车牌使用的影响因素，而且可以有效刻画两者之间的潜在联系；两者之间关联系数为-0.475，表明电动自行车车牌的使用可以降低电动自行车事故概率；模型结果显示性别、年龄、驾驶执照、家庭是否拥有小汽车、电动自行车驾龄、法律遵守程度、驾驶行为、危险感知度等具有统计显著性，是影响电动自行车事故和车牌使用的显著因素.

关键词: 交通工程, 事故影响因素, Bivariate Probit (BP)模型, 电动自行车, 车牌使用

Abstract:

In order to analyze the contributory factors associated with the e-bike involved crash and license plate use, 862 samples of Ningbo e- bike riders were collected using the questionnaire survey method and telephone interview survey method. Based on the statistical theory, a Bivariate Probit (BP) model is developed to simultaneously examine the factors that affect e- bike involved crash and e- bike license plate use among e-biker riders. Marginal effects for contributory factors are calculated to quantify their impacts on the outcomes. The results show that the BP model can not only identify the affecting factors for e- bike involved crash and license plate use, but also reflect potential relationships between them; the correlation parameter of the e-bike involved crash and license plate use is -0.475, indicating that e-bike license plate use can reduce the probability of the e- bike involved crash; several contributory factors, including gender, age group, driving license, car in household, experiences in using e-bike, law compliance, and aggressive driving behaviors are found to have significant impacts on both of e-bike involved crash and license plate use.

Key words: traffic engineering, contributory factors, Bivariate Probit model, electric bicycle, license plate use

中图分类号:

U491.1

周继彪，郭延永，吴瑶，董升. 电动自行车事故和车牌使用影响因素分析[J]. 交通运输系统工程与信息, 2017, 17(3): 229-234.

ZHOU Ji-biao, GUO Yan-yong, WU Yao, DONG Sheng. Assessing Factors Related to E-bike Crash and E-bike License Plate Use[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(3): 229-234.

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链接本文: http://www.tseit.org.cn/CN/abstract/abstract19437.shtml

http://www.tseit.org.cn/CN/Y2017/V17/I3/229

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