Lane changing and keeping as mediating variables to investigate the impact of driving habits on efficiency: An EWM-GRA and CB-SEM approach with trajectory data

IF 2.3 4区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IET Intelligent Transport Systems Pub Date : 2023-12-01 DOI:10.1049/itr2.12447

Tianshi Wang, Huapu Lu, Zhiyuan Sun, Jianyu Wang

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Abstract

This paper uses the Entropy Weight Method-Grey Relational Analysis (EWM-GRA) and Covariance Base Structural Equations Model (CB-SEM) to study the relationships between driving habits and efficiency. EWM-GRA ranks 12 indicators in terms of their relevance of lane-changing and driving efficiency. Based on this, a CB-SEM-based framework to describe the relevance between driving habits and lane-changing is established, focusing on the effects of lane-changing and car-following behaviour. To validate the established framework, NGSIM trajectory data is used as measurement variables to describe latent variables. Several hypotheses about the relationships between the latent variables in this framework are proposed, and they are verified using trajectory data. The results show that driving habits have a direct impact on efficiency, and this impact becomes more significant when associated with lane-change behaviour.

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以变道和保持车道为中介变量研究驾驶习惯对效率的影响:基于轨迹数据的EWM-GRA和CB-SEM方法

本文采用熵权法-灰色关联分析(EWM-GRA)和协方差基结构方程模型(CB-SEM)研究驾驶习惯与效率之间的关系。EWM-GRA根据12项指标与变道和驾驶效率的相关性进行排名。在此基础上，建立了一个基于cb - sem的框架来描述驾驶习惯和变道之间的相关性，重点关注变道和车辆跟随行为的影响。为了验证所建立的框架，使用NGSIM轨迹数据作为测量变量来描述潜在变量。提出了该框架中潜在变量之间关系的若干假设，并用轨迹数据对这些假设进行了验证。结果表明，驾驶习惯对效率有直接影响，当与变道行为相关时，这种影响变得更加显著。

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来源期刊

IET Intelligent Transport Systems 工程技术-运输科技

CiteScore

6.50

自引率

7.40%

发文量

159

审稿时长

3 months

期刊介绍： IET Intelligent Transport Systems is an interdisciplinary journal devoted to research into the practical applications of ITS and infrastructures. The scope of the journal includes the following: Sustainable traffic solutions Deployments with enabling technologies Pervasive monitoring Applications; demonstrations and evaluation Economic and behavioural analyses of ITS services and scenario Data Integration and analytics Information collection and processing; image processing applications in ITS ITS aspects of electric vehicles Autonomous vehicles; connected vehicle systems; In-vehicle ITS, safety and vulnerable road user aspects Mobility as a service systems Traffic management and control Public transport systems technologies Fleet and public transport logistics Emergency and incident management Demand management and electronic payment systems Traffic related air pollution management Policy and institutional issues Interoperability, standards and architectures Funding scenarios Enforcement Human machine interaction Education, training and outreach Current Special Issue Call for papers: Intelligent Transportation Systems in Smart Cities for Sustainable Environment - https://digital-library.theiet.org/files/IET_ITS_CFP_ITSSCSE.pdf Sustainably Intelligent Mobility (SIM) - https://digital-library.theiet.org/files/IET_ITS_CFP_SIM.pdf Traffic Theory and Modelling in the Era of Artificial Intelligence and Big Data (in collaboration with World Congress for Transport Research, WCTR 2019) - https://digital-library.theiet.org/files/IET_ITS_CFP_WCTR.pdf