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Dynamic Response Characteristics of Drivers’ Visual Search Behavior to Road Horizontal Curve Radius: Latest Simulation Experimental Results

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Listed:
  • Jinliang Xu

    (School of Highway, Chang’an University, Xi’an 710064, China)

  • Yongji Ma

    (School of Highway, Chang’an University, Xi’an 710064, China)

  • Chao Gao

    (School of Highway, Chang’an University, Xi’an 710064, China)

  • Tian Xin

    (School of Highway, Chang’an University, Xi’an 710064, China)

  • Houfu Yang

    (School of Highway, Chang’an University, Xi’an 710064, China)

  • Wenyu Peng

    (School of Highway, Chang’an University, Xi’an 710064, China)

  • Zhiyuan Wan

    (School of Highway, Chang’an University, Xi’an 710064, China)

Abstract

Road horizontal curves, which significantly influence drivers’ visual search behavior and are closely linked to traffic safety, also constitute a crucial factor in sustainable road traffic development. This paper uses simulation driving experiments to explore the dynamic response characteristics of 27 typical subject drivers’ visual search behavior regarding road horizontal curve radius. Results show that in a monotonous, open road environment, the driver’s visual search is biased towards the inside of the curve; as the radius increases, the 85th percentile value of the longitudinal visual search length gradually increases, the 85th percentile value of the horizontal search angle gradually decreases, the 85th percentile value of vehicle speed gradually increases, and the dispersion and bias of the gaze points gradually decrease. The search length, horizontal angle, and speed approach the level of straight road sections (380 m, 10° and 115 km/h, respectively). When R ≥ 1200 m, a driver’s dynamic visual search range reaches a stable distribution state that is the same as that of a straight road. A dynamic visual search range distribution model for drivers on straight and horizontal curved road sections is constructed. Based on psychological knowledge such as attention resource theory and eye–mind theory, a human factor engineering explanation was provided for drivers’ attention distribution and speed selection mechanism on road horizontal curve sections. The research results can provide theoretical references for the optimization design of road traffic, decision support to improve the driver training system, and a theoretical basis for determining the visual search characteristics of human drivers in autonomous driving technology, thereby promoting the safe and sustainable development of road traffic.

Suggested Citation

  • Jinliang Xu & Yongji Ma & Chao Gao & Tian Xin & Houfu Yang & Wenyu Peng & Zhiyuan Wan, 2025. "Dynamic Response Characteristics of Drivers’ Visual Search Behavior to Road Horizontal Curve Radius: Latest Simulation Experimental Results," Sustainability, MDPI, vol. 17(5), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:5:p:2197-:d:1604514
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    References listed on IDEAS

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    1. Cihe Chen & Zijian Lin & Shuguang Zhang & Feng Chen & Peiyan Chen & Lin Zhang, 2021. "The Compatibility between the Takeover Process in Conditional Automated Driving and the Current Geometric Design of the Deceleration Lane in Highway," Sustainability, MDPI, vol. 13(23), pages 1-17, December.
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