Lu Pan, Tolliver Denver
Assistant Professor of Transportation, Upper Great Plains Transportation Institute, Dept. 2880, North Dakota State University, Fargo, ND 58108-6050, USA.
Director and Professor of Transportation, Upper Great Plains Transportation Institute, Dept. 2880, North Dakota State University, Fargo, ND 58108-6050, USA.
Accid Anal Prev. 2016 May;90:73-81. doi: 10.1016/j.aap.2016.02.012. Epub 2016 Feb 27.
Considerable research has focused on roadway accident frequency analysis, but relatively little research has examined safety evaluation at highway-rail grade crossings. Highway-rail grade crossings are critical spatial locations of utmost importance for transportation safety because traffic crashes at highway-rail grade crossings are often catastrophic with serious consequences. The Poisson regression model has been employed to analyze vehicle accident frequency as a good starting point for many years. The most commonly applied variations of Poisson including negative binomial, and zero-inflated Poisson. These models are used to deal with common crash data issues such as over-dispersion (sample variance is larger than the sample mean) and preponderance of zeros (low sample mean and small sample size). On rare occasions traffic crash data have been shown to be under-dispersed (sample variance is smaller than the sample mean) and traditional distributions such as Poisson or negative binomial cannot handle under-dispersion well. The objective of this study is to investigate and compare various alternate highway-rail grade crossing accident frequency models that can handle the under-dispersion issue. The contributions of the paper are two-fold: (1) application of probability models to deal with under-dispersion issues and (2) obtain insights regarding to vehicle crashes at public highway-rail grade crossings.
大量研究集中在道路事故频率分析上，但对公路-铁路平交道口的安全评估研究相对较少。公路-铁路平交道口是交通安全至关重要的关键空间位置，因为公路-铁路平交道口的交通事故往往具有灾难性后果。多年来，泊松回归模型一直被用作分析车辆事故频率的良好起点。泊松最常用的变体包括负二项式和零膨胀泊松。这些模型用于处理常见的碰撞数据问题，如过度离散（样本方差大于样本均值）和零值占优（样本均值低且样本量小）。在极少数情况下，交通碰撞数据显示为欠离散（样本方差小于样本均值），而泊松或负二项式等传统分布无法很好地处理欠离散问题。本研究的目的是调查和比较各种能够处理欠离散问题的替代公路-铁路平交道口事故频率模型。本文的贡献有两个方面：（1）应用概率模型处理欠离散问题；（2）获得关于公共公路-铁路平交道口车辆碰撞的见解。
