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Analyzing Driving Safety on Prairie Highways: A Study of Drivers’ Visual Search Behavior in Varying Traffic Environments

Author

Listed:
  • Xu Ding

    (School of Energy and Transportation Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China)

  • Haixiao Wang

    (School of Energy and Transportation Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China)

  • Chutong Wang

    (Faculty of Social Science and Public Policy, King’s College London, London WC2R 2LS, UK)

  • Min Guo

    (School of Energy and Transportation Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China)

Abstract

This study aimed to investigate disparities in drivers’ visual search behavior across various typical traffic conditions on prairie highways and analyze driving safety at the visual search level. The study captured eye movement data from drivers across six real-world traffic environments: free driving, vehicle-following, oncoming vehicles, rear vehicles overtaking cut-in, roadside risks, and driving through intersections, by carrying out a real vehicle test on a prairie highway. The drivers’ visual search area was divided into five areas using clustering principles. By integrating the Markov chain and information entropy theory, the information entropy of fixation distribution (IEFD) was constructed to quantify the complexity of drivers’ traffic information search. Additionally, the main area of visual search (MAVS) and the peak-to-average ratio of saccade velocity (PARSV) were introduced to measure visual search range and stability, respectively. The study culminated in the creation of a visual search load evaluation model that utilizes both VIKOR and improved CRITIC methodologies. The findings indicated that while drivers’ visual distribution and transfer modes vary across different prairie highway traffic environments, the current lane consistently remained their primary area of search for traffic information. Furthermore, it was found that each visual search indicator displayed significant statistical differences as traffic environments changed. Particularly when encountering roadside risks, drivers’ visual search load increased significantly, leading to a considerable decrease in driving safety.

Suggested Citation

  • Xu Ding & Haixiao Wang & Chutong Wang & Min Guo, 2023. "Analyzing Driving Safety on Prairie Highways: A Study of Drivers’ Visual Search Behavior in Varying Traffic Environments," Sustainability, MDPI, vol. 15(16), pages 1-29, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:16:p:12146-:d:1213155
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    References listed on IDEAS

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    1. Danish Farooq & Sarbast Moslem & Szabolcs Duleba, 2019. "Evaluation of Driver Behavior Criteria for Evolution of Sustainable Traffic Safety," Sustainability, MDPI, vol. 11(11), pages 1-15, June.
    2. Miura, Ayako & Tomoeda, Akiyasu & Nishinari, Katsuhiro, 2020. "Formularization of entropy and anticipation of metastable states using mutual information in one-dimensional traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    3. Wenhui Zhang & Jing Dai & Yulong Pei & Penghui Li & Ying Yan & Xinqiang Chen, 2016. "Drivers’ Visual Search Patterns during Overtaking Maneuvers on Freeway," IJERPH, MDPI, vol. 13(11), pages 1-15, November.
    4. Qian Xu & Tang-yi Guo & Fei Shao & Xue-jiao Jiang, 2017. "Division of Area of Fixation Interest for Real Vehicle Driving Tests," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-10, May.
    5. Ting Shang & Hongjiao Qi & An Huang & Tangzhi Liu, 2022. "A comparative driving safety study of mountainous expressway individual tunnel and tunnel group based on eye gaze behavior," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-18, February.
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