Enhancing real-time conflict identification using trajectory data: Exploring the impact of interactions among traffic flow state variables

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作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Wu, Dan;Wu, Gaoming

通讯作者：

Wu, GM

作者机构：

[Wu, Dan] Cent South Univ, Sch Traff & Transportat Engn, Changsha, Peoples R China.

[Wu, Gaoming] Changsha Univ Sci & Technol, Sch Traff & Transportat Engn, 22 Shaoshan South Rd, Changsha 410075, Hunan, Peoples R China.

通讯机构：

[Wu, GM ] C

Changsha Univ Sci & Technol, Sch Traff & Transportat Engn, 22 Shaoshan South Rd, Changsha 410075, Hunan, Peoples R China.

语种：

英文

关键词：

Traffic safety;conflict identification;traffic flow state;interaction term;logistic regression model;machine learning

期刊：

Traffic Injury Prevention

ISSN：

1538-9588

年：

2025

卷：

期：

页码：

182-190

DOI：

10.1080/15389588.2024.2404715

基金类别：

Postgraduate Research and Innovation Project of Central South University [1053320220263]

机构署名：

本校为通讯机构

院系归属：

交通运输工程学院

摘要：

Objective This study aims to address the limitations of using historical crash data and trajectory data for crash and conflict identification. Specifically, it focuses on enhancing real-time conflict identification by investigating the influence of traffic flow state variables and their interactions on conflicts. This study aims to address the limitations of using historical crash data and trajectory data for crash and conflict identification. Specifically, it focuses on enhancing real-time conflict identification by investigating the influence...

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Enhancing real-time conflict identification using trajectory data: Exploring the impact of interactions among traffic flow state variables

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