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利用交通执法摄像机收集的数据调查信号交叉口交通违法行为的影响因素。

Investigating influence factors of traffic violations at signalized intersections using data gathered from traffic enforcement camera.

机构信息

School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, China.

National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu, China.

出版信息

PLoS One. 2020 Mar 4;15(3):e0229653. doi: 10.1371/journal.pone.0229653. eCollection 2020.

DOI:10.1371/journal.pone.0229653
PMID:32130254
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7055877/
Abstract

To effectively reduce traffic violations that often cause severe crashes at signalized intersections, exploring their contributing factors seems hugely urgent and essential. This study attempted to investigate the influence factors of wrong-way driving (WWD), red-light-running (RLR), violating traffic markings (VTM), and driving in the inaccurate oriented lane (DIOL) at signalized intersections by using data collected from traffic enforcement camera in Hohhot, China. To this end, an ordinary multinomial logit model was developed. By considering the unobserved heterogeneity between observations, a random effects multinomial logit model was proposed as well. After that, the marginal effects of explanatory variables were computed. The outcomes showed that non-local vehicles were more likely to commit WWD and VTM than local vehicles. WWD and RLR frequently occurred in the daytime and evening (6:00-23:59), and on most days within a week. RLR and DIOL mainly happened in June and July. The left-turn lane ratio significantly increased RLR and DIOL. The cloudy, partly cloudy, and rainy days obviously increased WWD and VTM. The temperature from 21 to 30 degrees centigrade was apparently associated with the higher likelihoods of RLR and DIOL. According to the findings of this study, some intervention measures, targeting different vehicle types and considering temporal factors, road, and weather conditions, were recommended to reduce WWD, RLR, VTM, and DIOL at signalized intersections.

摘要

为了有效减少经常导致信号灯交叉口严重事故的交通违法行为,探索其影响因素显得非常紧迫和必要。本研究试图通过使用在中国呼和浩特市交通执法摄像机收集的数据来研究信号灯交叉口错误驾驶(WWD)、闯红灯(RLR)、违反交通标志(VTM)和驾驶不正确导向车道(DIOL)的影响因素。为此,开发了一个普通多项逻辑回归模型。考虑到观测值之间的未观察到的异质性,还提出了随机效应多项逻辑回归模型。之后,计算了解释变量的边际效应。结果表明,非本地车辆比本地车辆更容易发生 WWD 和 VTM。WWD 和 RLR 经常发生在白天和晚上(6:00-23:59),以及一周中的大多数日子。RLR 和 DIOL 主要发生在 6 月和 7 月。左转车道比例显著增加了 RLR 和 DIOL。多云、部分多云和雨天明显增加了 WWD 和 VTM。21 到 30 摄氏度的温度与 RLR 和 DIOL 的更高可能性明显相关。根据本研究的结果,建议采取一些干预措施,针对不同类型的车辆,并考虑时间因素、道路和天气条件,以减少信号灯交叉口的 WWD、RLR、VTM 和 DIOL。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d84/7055877/42f0f35f67ba/pone.0229653.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d84/7055877/fec63e91bdf4/pone.0229653.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d84/7055877/f233967131d2/pone.0229653.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d84/7055877/a87790a59607/pone.0229653.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d84/7055877/42f0f35f67ba/pone.0229653.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d84/7055877/fec63e91bdf4/pone.0229653.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d84/7055877/f233967131d2/pone.0229653.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d84/7055877/a87790a59607/pone.0229653.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d84/7055877/42f0f35f67ba/pone.0229653.g004.jpg

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