不同极值建模技术在基于交通冲突的碰撞风险估算中的交叉比较

IF 12.5 1区 工程技术 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Depeng Niu , Tarek Sayed , Chuanyun Fu , Fred Mannering
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引用次数: 0

摘要

极值理论(EVT)模型最近在利用交通冲突数据进行碰撞风险估算方面越来越受欢迎。极值模型包括两种基本方法:块状最大值方法和峰值超过阈值方法,每种方法都有几种变体。然而,目前还缺乏对这两种方法及其变体在碰撞风险估计中的应用进行全面比较。本研究通过比较不同的极值建模技术并评估其在估计碰撞频率方面的性能,弥补了这一空白。在非稳态贝叶斯分层建模框架内,所分析的模型包括块最大值模型、r 最大阶统计量模型,以及具有固定阈值和动态阈值的峰值超过阈值模型,适用于单变量和双变量交通冲突案例。分析利用了从加拿大不列颠哥伦比亚省萨里市四个信号灯路口收集的修改后碰撞时间和蚕食后时间冲突指标数据。结果表明,在 r 最大阶统计量模型中加入额外的阶统计量可提高预测性能,尤其是在极端冲突样本有限的情况下。此外,与使用固定阈值相比,在峰值超过阈值模型中使用动态阈值可提高模型拟合度,并获得更准确的碰撞频率估计值。虽然在单变量情况下,区块最大值模型和峰值超过阈值模型的性能随所选冲突指标的不同而变化,但采用动态阈值的双变量峰值超过阈值模型的总体预测准确性优于相应的区块最大值模型。这可能是由于动态阈值能有效地精确识别真正关键的极端冲突。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A cross-comparison of different extreme value modeling techniques for traffic conflict-based crash risk estimation

Extreme Value Theory (EVT) models have recently gained increasing popularity for crash risk estimation using traffic conflict data. Extreme value modeling consists of two fundamental approaches: the block maxima approach and the peak-over-threshold approach, each with several variants. However, a comprehensive comparison of these two approaches and their variants in crash risk estimation is lacking. This study bridges this gap by comparing different extreme value modeling techniques and evaluating their performance in estimating crash frequencies. Within a non-stationary Bayesian hierarchical modeling framework, the analyzed models include the block maxima model, the r largest order statistic model, and the peak-over-threshold model with the fixed and dynamic threshold, across univariate and bivariate traffic conflict cases. The analysis utilizes modified time-to-collision and post-encroachment time conflict indicator data collected from four signalized intersections in the City of Surrey, British Columbia, Canada. The results show that incorporating additional order statistics in the r largest order statistic model improves predictive performance, particularly with limited extreme conflict samples. Moreover, employing the dynamic threshold within the peak-over-threshold model enhances model goodness-of-fit and yields more accurate crash frequency estimates compared to using the fixed threshold. While the performance of the block maxima and peak-over-threshold models varies with the selected conflict indicator in the univariate case, the bivariate peak-over-threshold model with the dynamic threshold exhibits superior overall prediction accuracy over the corresponding block maxima model. This is likely due to the effectiveness of the dynamic threshold in precisely identifying truly critical extreme conflicts.

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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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