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首页> 外文期刊>Accident Analysis and Prevention >Estimation of safety performance functions for urban intersections using various functional forms of the negative binomial regression model and a generalized Poisson regression model
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Estimation of safety performance functions for urban intersections using various functional forms of the negative binomial regression model and a generalized Poisson regression model

机译：使用负二项式回归模型的各种功能形式和广义泊松回归模型估算城市交叉路口的安全性能函数

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摘要

Intersections are established dangerous entities of a highway system due to the challenging and unsafe roadway environment they are characterized for drivers and other road users. In efforts to improve safety, an enormous interest has been shown in developing statistical models for intersection crash prediction and explanation. The selection of an adequate form of the statistical model is of great importance for the accurate estimation of crash frequency and the correct identification of crash contributing factors. Using a six-year crash data, road infrastructure and geometric design data, and traffic flow data of urban intersections, we applied three different functional forms of negative binomial models (i.e., NB-1, NB-2, NB-P) and a generalized Poisson (GP) model to develop safety performance functions (SPF) by crash severity for signalized and unsignalized intersections. This paper presents the relationships found between the explanatory variables and the expected crash frequency. It reports the comparison of different models for total, injury & fatal, and property damage only crashes in order to obtain ones with the maximum estimation accuracy. The comparison of models was based on the goodness of fit and the prediction performance measures.The fitted models showed that the traffic flow and several variables related to road infrastructure and geometric design significantly influence the intersection crash frequency. Further, the goodness of fit and the prediction performance measures revealed that the NB-P model outperformed other models in most crash severity levels for signalized intersections. For the unsignalized intersections, the GP model was the best performing model. When only the NB models were compared, the functional form NB-P performed better than the traditional NB-1 and, more specifically, the NB-2 models. In conclusion, our findings suggest a potential improvement in the estimation accuracy of the SPFs for urban intersections by applying the NB-P and GP models.
机译：由于具有挑战性和不安全的道路环境，交叉口是高速公路系统的危险实体，他们的特点是司机和其他道路使用者。在提高安全性的努力中，开发交叉口碰撞预测和解释的统计模型方面已经显示了巨大的兴趣。选择适当形式的统计模型对于准确估计碰撞频率和正确识别碰撞贡献因素的正确估计是重要的。使用六年的崩溃数据，道路基础设施和几何设计数据以及城市交叉路口的交通流量数据，我们应用了三种不同的负二项式模型（即NB-1，NB-2，NB-P）和A广义泊松（GP）模型通过崩溃的严重性来开发安全性能功能（SPF），用于信号和无信号化交集。本文介绍了解释变量与预期碰撞频率之间的关系。它报告了对总，伤害和致命模式的不同模型的比较，并且物业损坏只崩溃，以获得最大估计精度的崩溃。模型的比较基于适合的良好和预测性能措施。拟合模型表明，交通流量和与道路基础设施和几何设计相关的几个变量显着影响交叉碰撞频率。此外，适合的良好和预测性能措施揭示了NB-P型号在最大碰撞严重性水平中表现出的其他模型，用于信号交叉点。对于无罪化的交叉路口，GP模型是表现最好的模型。当比较NB模型时，功能形式的NB-P比传统的NB-1更好，更具体地是NB-2型号。总之，我们的研究结果表明，通过应用NB-P和GP模型，对城市交叉路口的SPF估算准确性的估算准确性潜在改进。

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