Traffic safety performance evaluation in a connected vehicle environment with queue warning and speed harmonization applications

IF 2.4 3区 工程技术 Q3 TRANSPORTATION Journal of Transportation Safety & Security Pub Date : 2023-11-03 DOI:10.1080/19439962.2023.2273545
Adekunle Adebisi, John E. Ash
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Abstract

AbstractWith the increased adoption of connected vehicle (CV) technologies, safety information is becoming increasingly available to drivers. This study investigates three main questions (1) Do CV-based traffic management applications improve safety on roadways with existing infrastructure-based traffic management systems? (2) Can combining two CV technologies have a greater impact on safety than a single CV technology? and (3) Do geometric and traffic composition factors impact the efficiency of CV technologies? We applied a rarely-used CV dataset and conducted a comprehensive simulation analysis of varying conditions and CV penetration rates that studies have not considered. Two CV applications (queue warning and speed harmonization) implemented in the Intelligent Network Flow Optimization experiment in Seattle, WA were evaluated. Results showed that driver safety performance, based on speed metrics (standard deviation and percentage of extreme values) improved under the CV driving conditions. Combining conventional variable speed limit systems with queue warnings also improved safety for CV drivers. Furthermore, the implementation of a single CV application (queue warning) showed positive changes in the aforementioned speed metrics, congestion mitigation, and reduced conflicts. With the two CV applications combined, no significant differences were observed. Additional tests investigated the impacts of lane changes and roadway attributes on safety in the CV environment.Keywords: connected vehiclesdriving informationtraffic safetytraffic simulation Author contributionsAdekunle Adebisi: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Validation, Visualization, Writing - original draft, Writing - review & editing. John Ash: Conceptualization, Supervision, Methodology, Validation, Writing - review & editing.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis research was not part of any funded project.
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基于队列预警和速度协调的网联车辆环境下的交通安全性能评价
摘要随着车联网技术的日益普及,驾驶员可以获得越来越多的安全信息。本研究调查了三个主要问题:(1)基于cv的交通管理应用程序是否可以提高现有基于基础设施的交通管理系统在道路上的安全性?(2)两种CV技术的结合是否比单一CV技术对安全性的影响更大?(3)几何和交通构成因素是否影响CV技术的效率?我们使用了一个很少使用的CV数据集,并对研究未考虑的不同条件和CV渗透率进行了全面的模拟分析。对西雅图智能网络流优化实验中两种CV应用(队列预警和速度协调)进行了评价。结果表明,在CV工况下,基于速度指标(标准差和极值百分比)的驾驶员安全性能有所提高。将传统的变速限制系统与队列警告相结合,也提高了CV驾驶员的安全性。此外,单个CV应用程序(队列警告)的实现在上述速度指标、拥塞缓解和减少冲突方面显示出积极的变化。结合两种CV应用,没有观察到显著差异。其他测试还研究了车道变化和道路属性对CV环境下安全性的影响。关键词:网联汽车、驾驶信息、交通安全、交通仿真作者投稿:萨德库勒·阿德比斯:概念化、数据策展、形式分析、调查、方法论、资源、验证、可视化、写作-初稿、写作-审稿编辑。约翰·阿什:概念化,监督,方法论,验证,写作-审查和编辑。披露声明作者未报告潜在的利益冲突。本研究不是任何资助项目的一部分。
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来源期刊
CiteScore
6.00
自引率
15.40%
发文量
38
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