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首页> 外文期刊>Journal of Safety Research >Development of pedestrian-and vehicle-related safety performance functions using Bayesian bivariate hierarchical models with mode- specific covariates
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Development of pedestrian-and vehicle-related safety performance functions using Bayesian bivariate hierarchical models with mode- specific covariates

机译:使用模式 - 特定的协变量的贝叶斯二抗体分层模型开发行人和车辆相关的安全性能函数

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Introduction: Pedestrian safety is a major concern as traffic crashes are the leading cause of fatalities and injuries for commuters. Traffic safety research in the past has developed various strategies to counteract traffic crashes, including the safety performance function (SPF). However, there is still a need for research dedicated to enhancing the SPF for pedestrians from perspectives of methodological framework and data input. To fill this gap, this study aims to add to the current SPF development practice literature by focusing on pedestrian-involved collisions, while considering the typical vehicle ones as well. Methods: First, bivariate models are used to account for the common unobserved heterogeneity shared by the pedestrian-and vehicle-related crashes at the same intersections. Second, variable importance ranking technique is used, along with correlation analysis, to determine mode-specific feature input. Third, the exposure information for both modes, annual pedestrian count, and annual daily vehicles traveled are used for model development. Fourth, a recent Bayesian inference approach (integrated nested Laplace approximation (INLA)) was adopted for bivariate setting. Finally, different evaluation criteria are used to facilitate comprehensive model assessment. Results: The results reveal different statistically significant factors contributing to each of the modes. The offset intersection provides better safety performance for both pedestrians and drivers as compared to other intersection designs. The model findings also corroborate the sensibility of using the bivariate models, rather than the separate univariate ones. Practical Applications: The study shows that pedestrians are more vulnerable to various intersection features such as left-turn channelization, intersection control, urban and rural population group, presence of signal mastarm on the cross-street, and mainline average daily traffic. Greater focus should be directed toward such intersection features to improve pedestrian safety. (c) 2021 The Authors. Published by the National Safety Council and Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
机译:介绍:行人安全是交通崩溃是通勤者死亡和伤害的主要关切。过去的交通安全研究已经开发出各种策略来抵消交通崩溃,包括安全性能功能(SPF)。但是,仍有必要从方法论框架和数据输入的角度来看,致力于为行人增强SPF的研究。为了填补这一差距,本研究旨在通过专注于行人涉及的碰撞,增加当前的SPF开发实践文献,同时考虑典型的车辆。方法:首先,双方模型用于考虑由相同交叉路口的行人和与车辆相关碰撞共享的共同的不受欢迎的异质性。其次,使用可变重要性排名技术,以及相关性分析,以确定特定模式特征输入。第三,旅行的两种模式,年度行人计数和年度日常车辆的曝光信息用于模型开发。第四,采用了最近贝叶斯推理方法(集成嵌套的拉普拉斯近似(Inla))进行了双相差异。最后,使用不同的评估标准来促进综合模型评估。结果:结果显示了对每个模式有贡献的不同统计上有关因素。与其他交叉点设计相比,偏移交叉点为行人和司机提供更好的安全性能。模型发现还证实了使用双方模型的敏感性,而不是单独的单变量。实际应用:该研究表明,行人更容易受到各种交叉点特征,如左转信道,交叉路口控制,城乡人口小组,交叉路口信号Mastarm的存在,以及主线平均日常交通。应更大的焦点来指向这种交叉点,以改善行人安全性。 (c)2021作者。由国家安全委员会和elestvier有限公司出版。这是CC的公开访问文章刊登执照(http://creativecommons.org/licenses/by/4.0/)。

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