Suppr超能文献

数量安全:基于挪威行人过街设施样本的估计

Safety-in-numbers: Estimates based on a sample of pedestrian crossings in Norway.

作者信息

Elvik Rune

机构信息

Institute of Transport Economics, Gaustadalleen 21, NO-0349 Oslo, Norway.

出版信息

Accid Anal Prev. 2016 Jun;91:175-82. doi: 10.1016/j.aap.2016.03.005. Epub 2016 Mar 16.

Abstract

Safety-in-numbers denotes the tendency for the risk of accident for each road user to decline as the number of road users increases. Safety-in-numbers implies that a doubling of the number of road users will be associated with less than a doubling of the number of accidents. This paper investigates safety-in-numbers in 239 pedestrian crossings in Oslo and its suburbs. Accident prediction models were fitted by means of negative binomial regression. The models indicate a very strong safety-in-numbers effect. In the final model, the coefficients for traffic volume were 0.05 for motor vehicles, 0.07 for pedestrians and 0.12 for cyclists. The coefficient for motor vehicles implies that the number of accidents is almost independent of the number of motor vehicles. The safety-in-numbers effect found in this paper is stronger than reported in any other study dealing with safety-in-numbers. It should be noted that the model explained only 21% of the systematic variation in the number of accidents. It therefore cannot be ruled out that the results are influenced by omitted variable bias. Any such bias would, however, have to be very large to eliminate the safety-in-numbers effect.

摘要

人多安全效应指的是随着道路使用者数量的增加,每个道路使用者发生事故的风险呈下降趋势。人多安全效应意味着道路使用者数量翻倍时,事故数量的增长不到一倍。本文对奥斯陆及其郊区的239个行人横道的人多安全效应进行了调查。通过负二项回归拟合事故预测模型。这些模型显示出非常强烈的人多安全效应。在最终模型中,机动车交通量系数为0.05,行人交通量系数为0.07,自行车交通量系数为0.12。机动车系数意味着事故数量几乎与机动车数量无关。本文发现的人多安全效应比其他任何关于人多安全效应的研究报告都要强。需要注意的是,该模型仅解释了事故数量系统变化的21%。因此,不能排除结果受到遗漏变量偏差影响的可能性。然而,任何此类偏差都必须非常大才能消除人多安全效应。

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