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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.

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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: Wang, Tianshi1 (AUTHOR), Lu, Huapu1 (AUTHOR), Sun, Zhiyuan2 (AUTHOR) sunzhiyuan@bjut.edu.cn, Wang, Jianyu3 (AUTHOR)
Source: IET Intelligent Transport Systems (Wiley-Blackwell). Feb2024, Vol. 18 Issue 2, p230-243. 14p.
Subjects: Lane changing, Structural equation modeling, Motor vehicle driving, Latent variables, Habit
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. [ABSTRACT FROM AUTHOR]
Copyright of IET Intelligent Transport Systems (Wiley-Blackwell) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 175282502
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PubType: Academic Journal
PubTypeId: academicJournal
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  Label: Title
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  Data: 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.
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  Data: <searchLink fieldCode="AR" term="%22Wang%2C+Tianshi%22">Wang, Tianshi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lu%2C+Huapu%22">Lu, Huapu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sun%2C+Zhiyuan%22">Sun, Zhiyuan</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> sunzhiyuan@bjut.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Wang%2C+Jianyu%22">Wang, Jianyu</searchLink><relatesTo>3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22IET+Intelligent+Transport+Systems+%28Wiley-Blackwell%29%22">IET Intelligent Transport Systems (Wiley-Blackwell)</searchLink>. Feb2024, Vol. 18 Issue 2, p230-243. 14p.
– Name: Subject
  Label: Subjects
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  Data: <searchLink fieldCode="DE" term="%22Lane+changing%22">Lane changing</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+equation+modeling%22">Structural equation modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Motor+vehicle+driving%22">Motor vehicle driving</searchLink><br /><searchLink fieldCode="DE" term="%22Latent+variables%22">Latent variables</searchLink><br /><searchLink fieldCode="DE" term="%22Habit%22">Habit</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  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. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of IET Intelligent Transport Systems (Wiley-Blackwell) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1049/itr2.12447
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 230
    Subjects:
      – SubjectFull: Lane changing
        Type: general
      – SubjectFull: Structural equation modeling
        Type: general
      – SubjectFull: Motor vehicle driving
        Type: general
      – SubjectFull: Latent variables
        Type: general
      – SubjectFull: Habit
        Type: general
    Titles:
      – TitleFull: 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.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Wang, Tianshi
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            NameFull: Lu, Huapu
      – PersonEntity:
          Name:
            NameFull: Sun, Zhiyuan
      – PersonEntity:
          Name:
            NameFull: Wang, Jianyu
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          Dates:
            – D: 01
              M: 02
              Text: Feb2024
              Type: published
              Y: 2024
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            – TitleFull: IET Intelligent Transport Systems (Wiley-Blackwell)
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