A multiple membership multilevel negative binomial model for intersection crash analysis

IF 12.5 1区 工程技术 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Analytic Methods in Accident Research Pub Date : 2022-09-01 DOI:10.1016/j.amar.2022.100228
Ho-Chul Park , Byung-Jung Park , Peter Y. Park
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引用次数: 2

Abstract

Many intersections belong to more than one zone, but most research has not considered the effects of multiple zones in intersection crash analysis. This issue is known as a boundary problem. Unobserved heterogeneity between zones can lead to model misspecification which can result in biased parameter estimates and poor model fitting performance. This study investigated the issue using five years of intersection crash data from the City of Regina, Saskatchewan, Canada. The study developed three multiple membership multilevel negative binomial models to reduce unobserved zonal-level heterogeneity. Each multiple membership multilevel model used a different weight strategy. When the fitting performance of the three multiple membership multilevel models was compared with two additional models, a traditional single level model and a conventional multilevel model, all three multiple membership multilevel models had a better fitting performance. Five individual-level and seven group-level variables were statistically significant (90% confidence level) in all the models with five of the individual-level and four of the group-level variables statistically significant at the 99% confidence level. The multiple membership multilevel models also helped to prevent the underestimation of group-level variance and type I statistical errors that tend to occur with single level models and conventional multilevel models. In particular, the three multiple membership multilevel models produced more accurate results for intersections with a large AADT. As intersections with a large AADT are known to have more crashes, multiple membership multilevel models are likely to be more useful than single level models and conventional multilevel models when selecting intersections for safety improvement. The study recommends the adoption of a multiple membership multilevel model to improve fitting performance and reduce the boundary problem for intersections affected by more than one zone.

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交叉口碰撞分析的多隶属度多层负二项模型
许多交叉口属于多个区域,但大多数研究并未在交叉口碰撞分析中考虑多个区域的影响。这个问题被称为边界问题。区域间未观察到的异质性可能导致模型的错误规范,从而导致参数估计有偏,模型拟合性能差。这项研究使用了加拿大萨斯喀彻温省里贾纳市五年的交叉路口碰撞数据来调查这个问题。该研究建立了三个多成员多水平负二项模型,以减少未观察到的区域水平异质性。每个多成员多级模型使用不同的权重策略。将三种多隶属度多层模型与传统单层模型和传统多层模型的拟合性能进行比较,结果表明三种多隶属度多层模型均具有较好的拟合性能。5个个体水平变量和7个群体水平变量在所有模型中均具有统计学显著性(90%置信水平),其中5个个体水平变量和4个群体水平变量在99%置信水平上具有统计学显著性。多隶属度多层模型还有助于防止单水平模型和传统多层模型容易出现的群体水平方差低估和I型统计误差。特别是对于AADT较大的交叉口,三种多隶属度多层模型的结果更为准确。由于已知具有较大AADT的交叉口发生较多的碰撞,因此在选择安全性改进的交叉口时,多成员多层模型可能比单层模型和传统多层模型更有用。研究建议采用多隶属度多层模型来提高拟合性能,并减少受多个区域影响的交叉口的边界问题。
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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.
期刊最新文献
Determinants influencing alcohol-related two-vehicle crash severity: A multivariate Bayesian hierarchical random parameters correlated outcomes logit model Effects of sample size on pedestrian crash risk estimation from traffic conflicts using extreme value models Editorial Board A cross-comparison of different extreme value modeling techniques for traffic conflict-based crash risk estimation The role of posted speed limit on pedestrian and bicycle injury severities: An investigation into systematic and unobserved heterogeneities
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