{"title":"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","authors":"Tianshi Wang, Huapu Lu, Zhiyuan Sun, Jianyu Wang","doi":"10.1049/itr2.12447","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12447","citationCount":"0","resultStr":"{\"title\":\"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\",\"authors\":\"Tianshi Wang, Huapu Lu, Zhiyuan Sun, Jianyu Wang\",\"doi\":\"10.1049/itr2.12447\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":50381,\"journal\":{\"name\":\"IET Intelligent Transport Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2023-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12447\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Intelligent Transport Systems\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/itr2.12447\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Intelligent Transport Systems","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/itr2.12447","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
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
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.
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