基于协方差的随机方法用于预测严重的道路交通相互作用

IF 12.5 1区 工程技术 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Zhankun Chen, Oksana Yastremska-Kravchenko, Aliaksei Laureshyn, Carl Johnsson, Carmelo D’Agostino
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引用次数: 0

摘要

xx 在已经达到一定安全水平或暴露程度较低的情况下,如不同运输自动化水平的混合交通条件下,这是一个常见问题。最近的研究表明,道路使用者和/或道路使用者与基础设施之间的严重交互作用可以直接衡量安全性。然而,考虑到缺乏预测的稳健性和可能存在的选择偏差,仅对最极端事件进行调查可能会导致不确定的结果。在这种情况下,极值理论(EVT)通常被用来推断道路交通互动中的碰撞事故,甚至结合多个指标。本研究扩展了 EVT 范式,提出了一种基于 copula 函数和 EVT 的方法,可对相互作用的严重程度进行更具体、更连续的评估。与纯 EVT 相比,这种新方法将边界扩展到所有严重程度的相互作用,同时隐含地假设安全相关事件与道路伤亡之间的关系是随机的。这种 EVT-copula 方法还与双变量峰值超过阈值(BPOT)进行了比较。结果发现,这两种方法对碰撞概率的预测结果相似。此外,所提出的方法适用于 BPOT 中未适当定义的事件,并且与 BPOT 相比,在以观测结果为基准时,对严重(和不太严重)相互作用的预测更为准确。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stochastic method based on copulas for predicting severe road traffic interactions

A major difficulty in assessing road traffic safety is the scarcity of historical accident data. xxThis is a common problem in contexts where a certain level of safety has been reached or where exposure is low, such as mixed traffic conditions with different levels of transport automation. Recent studies have demonstrated how severe interactions between road users and/or road users and infrastructure can be a direct measure of safety. However, limiting the investigation to only the most extreme events may lead to inconclusive results considering the lack of prediction robustness and the possible selection bias. In this context, extreme value theory (EVT) is commonly used to extrapolate crashes from road traffic interactions, even combining several indicators. The present work extends the EVT paradigm by proposing a method based on copula functions and EVT, which enables a more specific and continuous evaluation of interaction severity. Compared with pure EVT, this new approach extends the boundary to interactions of all severities while implicitly assuming that the relationship between safety-relevant events and road casualties is stochastic. This EVT-copula approach was also compared with bivariate peaks over threshold (BPOT). It was found that the two approaches yield similar prediction results for crash probabilities. Furthermore, the proposed approach applies to events not properly defined in BPOT and provides more accurate predictions for severe (and less severe) interactions compared with BPOT, when benchmarked against observations.

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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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