IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-981-16-8016-8_9.html
   My bibliography  Save this book chapter

Effects of Congestion on Drivers’ Speed Choice: Assessing the Mediating Role of State Aggressiveness Based on Taxi Floating Car Data

In: Logic-Driven Traffic Big Data Analytics

Author

Listed:
  • Shaopeng Zhong

    (Dalian University of Technology
    Southwest Jiaotong University)

  • Daniel (Jian) Sun

    (Chang’an University
    Shanghai Jiao Tong University)

Abstract

Inappropriate cruising speed, such as speeding, is one of the major contributors to the road safety, which increases both the quantitative number and severity of traffic accidents. Previous studies have indicated that traffic congestion is one of the primary causes of drivers’ frustration and aggression, which may lead to inappropriate speed choice. In this study, the large taxi floating car data (FCD) was used to empirically evaluate how traffic congestion-related negative moods, defined as state aggressiveness, affected drivers’ speed choice. The indirect effect of traffic delay on the cruising speed adjustment through the state aggressiveness was assessed through the mediation analysis. Furthermore, the moderated mediation analysis was performed to explore the effect of driver type, value of time, and working duration on the mediation role of state aggressiveness. The results proved that the state aggressiveness was the mediator of the relationship between travel delays and driving speed adjustment, and the mediation role was different across various driver types. As compared to the aggressive drivers, the normal drivers and the steady drivers tended to behave more aggressively after experiencing non-recurrent congestion during the early stage of the trips. When the value of time was high, steady drivers were more likely to adjust their speed choice although the effect was not statistically significant for other driver types. The validation results indicated that the speed model incorporating state aggressiveness could better predict the travel time than the traditional speed model that only considering the specific expected speed distribution. The prediction results for the manifest indicators of state aggressiveness, such as the maximum speed and the speed deviation, also demonstrated a reasonable reflection of the field data.

Suggested Citation

  • Shaopeng Zhong & Daniel (Jian) Sun, 2022. "Effects of Congestion on Drivers’ Speed Choice: Assessing the Mediating Role of State Aggressiveness Based on Taxi Floating Car Data," Springer Books, in: Logic-Driven Traffic Big Data Analytics, chapter 0, pages 183-202, Springer.
  • Handle: RePEc:spr:sprchp:978-981-16-8016-8_9
    DOI: 10.1007/978-981-16-8016-8_9
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:sprchp:978-981-16-8016-8_9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.