基于冲突的实时安全分析贝叶斯动态极值建模

IF 12.5 1区 工程技术 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Chuanyun Fu , Tarek Sayed
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引用次数: 35

摘要

利用交通冲突等替代安全措施和极值理论(EVT)模型等技术进行实时安全分析和优化是主动交通安全管理背景下的一个新兴研究课题。然而,现有的实时安全分析EVT模型的预测性能和时间可转移性都建立在模型参数不变的前提下,没有考虑到时间变异性,不适合实时交通数据分析。提出了一种基于冲突的实时安全分析贝叶斯动态极值建模方法,该方法将贝叶斯动态线性模型与极值分布相结合。该方法具有以下几个独特的优点:1)允许模型参数时变;2)将新数据与先验信息相结合,递归更新模型参数,考虑状态空间变化,应对突发趋势变化;3)解释冲突极端事件的时间变异性和非平稳性;4)定量评价道路设施的实时安全水平。该方法被应用于不列颠哥伦比亚省萨里市四个信号交叉口的自行车安全分析。通过改进的冲突时间指标来表征交通冲突。考虑信号周期水平的三个交通参数(交通量、冲击波面积和排比)作为协变量,以解释非平稳性。建立了几个贝叶斯动态和静态极值模型,并生成了两个安全指标,即碰撞风险(RC)和返回水平(RL),以定量表征周期级安全性。RC直接反映了一个循环是否有风险,而RL可以评估单个循环的安全水平。结果表明,与静态模型相比,动态模型可以识别出更多具有正RC或正RL的碰撞危险循环,并且能够根据RL区分单个循环的安全水平。总体而言,动态模型在统计拟合和总体碰撞估计精度方面优于静态模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bayesian dynamic extreme value modeling for conflict-based real-time safety analysis

Real-time safety analysis and optimization using surrogate safety measures such as traffic conflicts and techniques such extreme value theory (EVT) models is an emerging research topic in the context of proactive traffic safety management. However, the predictive performance and temporal transferability of the existing real-time safety analysis EVT models are subject to the assumption of invariant model parameters, which do not account for the temporal variability and is not suitable for real-time traffic data analysis. This study proposes a Bayesian dynamic extreme value modeling approach for conflict-based real-time safety analysis which integrates a Bayesian dynamic linear model with the extreme value distribution. The proposed approach has several unique advantages as it: 1) allows the model parameters to be time-varying; 2) integrates the newer data with prior information to recursively update the model parameters and account for state-space changes and react to sudden trend changes; 3) accounts for temporal variability and non-stationarity in conflict extremes; and 4) quantitatively evaluates the real-time safety levels of a road facility. The proposed approach is applied for cycle-by-cycle safety analysis at four signalized intersections in the city of Surrey, British Columbia. Traffic conflicts are characterized by the modified time to collision indicator. Three traffic parameters (traffic volume, shock wave area, and platoon ratio) at the signal cycle level are considered as covariates to account for non-stationarity. Several Bayesian dynamic and static extreme value models are developed and two safety indices, namely risk of crash (RC) and return level (RL), are generated to quantitatively represent the cycle-level safety. The RC directly reflects whether a cycle is risky while the RL can evaluate the safety levels of individual cycles. The results show that the dynamic model can identify more crash-risk cycles with either a positive RC or a positive RL than the static model and is more capable of differentiating the safety levels for individual cycles in terms of RL. Overall, the dynamic model outperforms the static model in terms of the statistical fit and aggregate crash estimation accuracy.

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来源期刊
CiteScore
22.10
自引率
34.10%
发文量
35
审稿时长
24 days
期刊介绍: Analytic Methods in Accident Research is a journal that publishes articles related to the development and application of advanced statistical and econometric methods in studying vehicle crashes and other accidents. The journal aims to demonstrate how these innovative approaches can provide new insights into the factors influencing the occurrence and severity of accidents, thereby offering guidance for implementing appropriate preventive measures. While the journal primarily focuses on the analytic approach, it also accepts articles covering various aspects of transportation safety (such as road, pedestrian, air, rail, and water safety), construction safety, and other areas where human behavior, machine failures, or system failures lead to property damage or bodily harm.
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