View in EDS

Optimization of Signalized Intersections in Mixed Traffic: A Coordinated Platoon–Signal Control Method Considering the Backward-Looking Effect.

Saved in:
Bibliographic Details
Title: Optimization of Signalized Intersections in Mixed Traffic: A Coordinated Platoon–Signal Control Method Considering the Backward-Looking Effect.
Authors: Li, Xinyuan1 (AUTHOR) xinyuan_li2021@163.com, Ma, Minghui2 (AUTHOR), Liang, Shidong3 (AUTHOR) sdliang@hotmail.com, Li, Qi4 (AUTHOR) liqi9373@126.com, Yang, Jufen5 (AUTHOR) yangjufenabc@126.com, Chen, Fei6 (AUTHOR) 1424133@qq.com
Source: Journal of Transportation Engineering. Part A. Systems. Jul2026, Vol. 152 Issue 7, p1-17. 17p.
Subjects: Signalized intersections, Traffic signal control systems, Traffic engineering, Traffic congestion, Traffic flow, Autonomous vehicles
Abstract: Mixed traffic flows involving connected autonomous vehicles (CAVs) and human-driven vehicles (HDVs) present new opportunities and challenges for signalized intersections. Although intelligent control strategies have been extensively studied for such environments, most existing approaches neglect the backward-looking effect, in which a driver adjusts not only to the preceding vehicle but also in response to the immediate follower. This omission limits the effectiveness of platoon-based control in mixed traffic. To address this gap, a coordinated platoon–signal control method incorporating a backward-looking effect (CPSC-BLE) is proposed. The framework integrates bidirectional vehicle interactions into platoon trajectory planning and couples them with adaptive signal timing, linking microscopic platoon behavior with macroscopic signal optimization. The approach enhances platoon coherence, improves green time utilization, and mitigates stop-and-go oscillations. Simulation results demonstrate that the proposed CPSC-BLE framework effectively smooths vehicle trajectories, reduces travel delays, and lowers fuel consumption compared with conventional control strategies. These findings highlight the potential of control strategies informed by the backward-looking effect to improve both efficiency and stability in mixed traffic intersections. Practical Applications: Traffic congestion at urban intersections is one of the most common problems faced by cities, often leading to longer travel times, higher fuel use, and greater emissions. This study introduces a new method to improve how groups of vehicles move through signalized intersections when both connected automated vehicles and human-driven vehicles are present. The key idea is to recognize that drivers are not only influenced by the car in front of them, but also adjust their behavior based on the car behind them. By accounting for this two-way influence within a group of vehicles, the proposed method allows traffic signals to better coordinate with connected autonomous vehicle movements. In practice, this means that traffic lights can adjust their green times in real time to match the actual flow of vehicle groups, helping entire platoons of vehicles pass through intersections smoothly. This approach reduces wasted green light time, prevents unnecessary stops, and helps human-driven vehicles at the back of queues move more efficiently. The method can be applied in cities where automated vehicles are gradually being introduced, offering a pathway to ease congestion, lower fuel consumption, and improve the overall reliability of urban traffic systems. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Transportation Engineering. Part A. Systems is the property of American Society of Civil Engineers 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
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 193805634
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Optimization of Signalized Intersections in Mixed Traffic: A Coordinated Platoon–Signal Control Method Considering the Backward-Looking Effect.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Li%2C+Xinyuan%22">Li, Xinyuan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> xinyuan_li2021@163.com</i><br /><searchLink fieldCode="AR" term="%22Ma%2C+Minghui%22">Ma, Minghui</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liang%2C+Shidong%22">Liang, Shidong</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> sdliang@hotmail.com</i><br /><searchLink fieldCode="AR" term="%22Li%2C+Qi%22">Li, Qi</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> liqi9373@126.com</i><br /><searchLink fieldCode="AR" term="%22Yang%2C+Jufen%22">Yang, Jufen</searchLink><relatesTo>5</relatesTo> (AUTHOR)<i> yangjufenabc@126.com</i><br /><searchLink fieldCode="AR" term="%22Chen%2C+Fei%22">Chen, Fei</searchLink><relatesTo>6</relatesTo> (AUTHOR)<i> 1424133@qq.com</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Journal+of+Transportation+Engineering%2E+Part+A%2E+Systems%22">Journal of Transportation Engineering. Part A. Systems</searchLink>. Jul2026, Vol. 152 Issue 7, p1-17. 17p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Signalized+intersections%22">Signalized intersections</searchLink><br /><searchLink fieldCode="DE" term="%22Traffic+signal+control+systems%22">Traffic signal control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Traffic+engineering%22">Traffic engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Traffic+congestion%22">Traffic congestion</searchLink><br /><searchLink fieldCode="DE" term="%22Traffic+flow%22">Traffic flow</searchLink><br /><searchLink fieldCode="DE" term="%22Autonomous+vehicles%22">Autonomous vehicles</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Mixed traffic flows involving connected autonomous vehicles (CAVs) and human-driven vehicles (HDVs) present new opportunities and challenges for signalized intersections. Although intelligent control strategies have been extensively studied for such environments, most existing approaches neglect the backward-looking effect, in which a driver adjusts not only to the preceding vehicle but also in response to the immediate follower. This omission limits the effectiveness of platoon-based control in mixed traffic. To address this gap, a coordinated platoon–signal control method incorporating a backward-looking effect (CPSC-BLE) is proposed. The framework integrates bidirectional vehicle interactions into platoon trajectory planning and couples them with adaptive signal timing, linking microscopic platoon behavior with macroscopic signal optimization. The approach enhances platoon coherence, improves green time utilization, and mitigates stop-and-go oscillations. Simulation results demonstrate that the proposed CPSC-BLE framework effectively smooths vehicle trajectories, reduces travel delays, and lowers fuel consumption compared with conventional control strategies. These findings highlight the potential of control strategies informed by the backward-looking effect to improve both efficiency and stability in mixed traffic intersections. Practical Applications: Traffic congestion at urban intersections is one of the most common problems faced by cities, often leading to longer travel times, higher fuel use, and greater emissions. This study introduces a new method to improve how groups of vehicles move through signalized intersections when both connected automated vehicles and human-driven vehicles are present. The key idea is to recognize that drivers are not only influenced by the car in front of them, but also adjust their behavior based on the car behind them. By accounting for this two-way influence within a group of vehicles, the proposed method allows traffic signals to better coordinate with connected autonomous vehicle movements. In practice, this means that traffic lights can adjust their green times in real time to match the actual flow of vehicle groups, helping entire platoons of vehicles pass through intersections smoothly. This approach reduces wasted green light time, prevents unnecessary stops, and helps human-driven vehicles at the back of queues move more efficiently. The method can be applied in cities where automated vehicles are gradually being introduced, offering a pathway to ease congestion, lower fuel consumption, and improve the overall reliability of urban traffic systems. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Transportation Engineering. Part A. Systems is the property of American Society of Civil Engineers 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.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=193805634
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1061/JTEPBS.TEENG-9281
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 17
        StartPage: 1
    Subjects:
      – SubjectFull: Signalized intersections
        Type: general
      – SubjectFull: Traffic signal control systems
        Type: general
      – SubjectFull: Traffic engineering
        Type: general
      – SubjectFull: Traffic congestion
        Type: general
      – SubjectFull: Traffic flow
        Type: general
      – SubjectFull: Autonomous vehicles
        Type: general
    Titles:
      – TitleFull: Optimization of Signalized Intersections in Mixed Traffic: A Coordinated Platoon–Signal Control Method Considering the Backward-Looking Effect.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Li, Xinyuan
      – PersonEntity:
          Name:
            NameFull: Ma, Minghui
      – PersonEntity:
          Name:
            NameFull: Liang, Shidong
      – PersonEntity:
          Name:
            NameFull: Li, Qi
      – PersonEntity:
          Name:
            NameFull: Yang, Jufen
      – PersonEntity:
          Name:
            NameFull: Chen, Fei
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 07
              Text: Jul2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 24732907
          Numbering:
            – Type: volume
              Value: 152
            – Type: issue
              Value: 7
          Titles:
            – TitleFull: Journal of Transportation Engineering. Part A. Systems
              Type: main
ResultId 1