[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v653y2024ics0378437124006228.html
   My bibliography  Save this article

Emissions-reduction strategy for connected autonomous vehicles on mixed traffic freeways

Author

Listed:
  • Qin, Yanyan
  • Xiao, Tengfei
  • He, Zhengbing
Abstract
Acceleration and deceleration behaviors negatively affect car-following dynamics of vehicles on freeways, leading to traffic oscillations, thus increasing transportation emissions. The emergence of connected autonomous vehicles (CAVs) offers a potential to mitigate these effects. This paper aims to propose a car-following strategy for CAVs to reduce transportation emissions on mixed traffic freeways. Firstly, we adopted the calibrated Gipps model to characterize car-following behaviors of human-driven vehicles (HDVs). Based on this, we proposed a car-following strategy for CAVs designed to mitigate traffic oscillations and reduce transportation emissions. Subsequently, we introduced a simulation framework for analyzing transportation emissions. Finally, considering foggy weather as a practical application, we validated the effectiveness of our proposed CAV car-following strategy, by evaluating transportation emissions under different conditions, including three emission categories, varying CAV market presentation rates (MPRs), two foggy levels, and four speed limits. The results show a close correlation between transportation emissions and traffic oscillations, indicating that increased oscillations result in higher emissions. The proposed CAV strategy demonstrates significant efficacy in mitigating traffic oscillations and reducing transportation emissions in foggy weather. As the MPR of CAVs equipped with our strategy increases, transportation emissions decrease gradually. Specifically, at an MPR of 1, the average reductions in CO, HC, and NOx emissions reach 16.99 %, 11.65 %, and 20.82 %, respectively. Following findings from our analysis, recommended insights are provided for speed limit strategy and CAV dedicated lane management for mixed traffic on foggy freeways, from the perspective of reducing emissions.

Suggested Citation

  • Qin, Yanyan & Xiao, Tengfei & He, Zhengbing, 2024. "Emissions-reduction strategy for connected autonomous vehicles on mixed traffic freeways," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 653(C).
    • Handle: RePEc:eee:phsmap:v:653:y:2024:i:c:s0378437124006228
    DOI: 10.1016/j.physa.2024.130113
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437124006228
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2024.130113?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:653:y:2024:i:c:s0378437124006228. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.