IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i13p7463-d588329.html
   My bibliography  Save this article

Analysis of Drivers’ Eye Movements on Roundabouts: A Driving Simulator Study

Author

Listed:
  • Amin Azimian

    (School of Architecture, The University of Texas at Austin, Austin, TX 78712, USA)

  • Carlos Alberto Catalina Ortega

    (Departamento de Ingeniería de Organización, Universidad de Burgos, 09006 Burgos, Spain)

  • Juan Maria Espinosa

    (Departamento de Ingeniería de Organización, Universidad de Burgos, 09006 Burgos, Spain)

  • Miguel Ángel Mariscal

    (Departamento de Ingeniería de Organización, Universidad de Burgos, 09006 Burgos, Spain)

  • Susana García-Herrero

    (Departamento de Ingeniería de Organización, Universidad de Burgos, 09006 Burgos, Spain)

Abstract

Roundabouts are considered as one of the most efficient forms of intersection that substantially reduce the types of crashes that result in injury or loss of life. Nevertheless, they do not eliminate collision risks, especially when human error plays such a large role in traffic crashes. In this study, we used a driving simulator and an eye tracker to investigate drivers’ eye movements under cell phone-induced distraction. A total of 45 drivers participated in two experiments conducted under distracted and non-distracted conditions. The results indicated that, under distracting conditions, the drivers’ fixation duration decreased significantly on roundabouts, and pupil size increased significantly.

Suggested Citation

  • Amin Azimian & Carlos Alberto Catalina Ortega & Juan Maria Espinosa & Miguel Ángel Mariscal & Susana García-Herrero, 2021. "Analysis of Drivers’ Eye Movements on Roundabouts: A Driving Simulator Study," Sustainability, MDPI, vol. 13(13), pages 1-10, July.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:13:p:7463-:d:588329
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/13/7463/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/13/7463/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lisheng Jin & Qingning Niu & Haijing Hou & Huacai Xian & Yali Wang & Dongdong Shi, 2012. "Driver Cognitive Distraction Detection Using Driving Performance Measures," Discrete Dynamics in Nature and Society, Hindawi, vol. 2012, pages 1-12, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Qin Zeng & Yun Chen & Xiazhong Zheng & Meng Zhang & Donghui Li & Qilin Hu, 2023. "Exploring the Visual Attention Mechanism of Long-Distance Driving in an Underground Construction Cavern: Eye-Tracking and Simulated Driving," Sustainability, MDPI, vol. 15(12), pages 1-25, June.
    2. Qin Zeng & Yun Chen & Xiazhong Zheng & Shiyu He & Donghui Li & Benwu Nie, 2023. "Optimization of Underground Cavern Sign Group Layout Using Eye-Tracking Technology," Sustainability, MDPI, vol. 15(16), pages 1-32, August.
    3. Yu-Ling Hsieh & Ming-Feng Lee & Guey-Shya Chen & Wei-Jie Wang, 2022. "Application of Visitor Eye Movement Information to Museum Exhibit Analysis," Sustainability, MDPI, vol. 14(11), pages 1-15, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wencai Sun & Yihao Si & Mengzhu Guo & Shiwu Li, 2021. "Driver Distraction Recognition Using Wearable IMU Sensor Data," Sustainability, MDPI, vol. 13(3), pages 1-17, January.

    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:gam:jsusta:v:13:y:2021:i:13:p:7463-:d:588329. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.