Suppr超能文献

评估高速公路二次事故风险。

Assessing the risk of secondary crashes on highways.

机构信息

Department of Civil and Urban Engineering, Center for Urban Science and Progress (CUSP), New York University (NYU), One MetroTech Center, 19th Floor, Office 1919Q, Brooklyn, NY 11201, USA.

Department of Civil and Urban Engineering, Center for Urban Science and Progress (CUSP), New York University (NYU), One MetroTech Center, 19th Floor, Brooklyn, NY 11201, USA.

出版信息

J Safety Res. 2014 Jun;49:143-9. doi: 10.1016/j.jsr.2014.03.007. Epub 2014 Apr 24.

Abstract

INTRODUCTION

The occurrence of "secondary crashes" is one of the critical yet understudied highway safety issues. Induced by the primary crashes, the occurrence of secondary crashes does not only increase traffic delays but also the risk of inducing additional incidents. Many highway agencies are highly interested in the implementation of safety countermeasures to reduce this type of crashes. However, due to the limited understanding of the key contributing factors, they face a great challenge for determining the most appropriate countermeasures.

METHOD

To bridge this gap, this study makes important contributions to the existing literature of secondary incidents by developing a novel methodology to assess the risk of having secondary crashes on highways. The proposed methodology consists of two major components, namely: (a) accurate identification of secondary crashes and (b) statistically robust assessment of causal effects of contributing factors. The first component is concerned with the development of an improved identification approach for secondary accidents that relies on the rich traffic information obtained from traffic sensors. The second component of the proposed methodology is aimed at understanding the key mechanisms that are hypothesized to cause secondary crashes through the use of a modified logistic regression model that can efficiently deal with relatively rare events such as secondary incidents. The feasibility and improved performance of using the proposed methodology are tested using real-world crash and traffic flow data.

RESULTS

The risk of inducing secondary crashes after the occurrence of individual primary crashes under different circumstances is studied by employing the estimated regression model. Marginal effect of each factor on the risk of secondary crashes is also quantified and important contributing factors are highlighted and discussed.

PRACTICAL APPLICATIONS

Massive sensor data can be used to support the identification of secondary crashes. The occurrence mechanism of these secondary crashes can be investigate by the proposed model. Understanding the mechanism helps deploy appropriate countermeasures to mitigate or prevent the secondary crashes.

摘要

简介

“二次碰撞”的发生是公路安全中一个关键但研究不足的问题。次生碰撞的发生不仅会增加交通延误,还会增加引发其他事故的风险,这是由初次碰撞引起的。许多公路管理机构对实施安全措施以减少此类碰撞非常感兴趣。然而,由于对关键影响因素的理解有限,他们在确定最合适的措施方面面临着巨大的挑战。

方法

为了弥补这一差距,本研究通过开发一种新的方法来评估高速公路上发生二次碰撞的风险,为二次事故的现有文献做出了重要贡献。该方法由两个主要部分组成,即:(a)准确识别二次碰撞,(b)统计稳健评估影响因素的因果效应。第一部分涉及开发一种改进的二次事故识别方法,该方法依赖于从交通传感器获得的丰富交通信息。所提出方法的第二部分旨在通过使用可以有效地处理二次事故等相对罕见事件的改进逻辑回归模型来理解被假设为导致二次碰撞的关键机制。使用实际的碰撞和交通流量数据测试了使用所提出的方法的可行性和改进性能。

结果

通过使用估计的回归模型,研究了在不同情况下发生单个初次碰撞后引起二次碰撞的风险。还量化了每个因素对二次碰撞风险的边际效应,并突出和讨论了重要的影响因素。

实际应用

大量传感器数据可用于支持二次碰撞的识别。可以通过所提出的模型来研究这些二次碰撞的发生机制。了解发生机制有助于部署适当的对策来减轻或防止二次碰撞。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验