Characterization of Driver Dynamic Visual Perception Under Different Road Linearity Conditions

Drivers’ visual characteristics have an important impact on traffic safety, but existing studies are mostly limited to single-scene analyses and lack a systematic study on the dynamic changes in drivers’ eye tracking characteristics on different road sections. In this study, 23 drivers were recruite...

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Main Authors: Zhenxiang Hao, Jianping Hu, Jin Ran, Xiaohui Sun, Yuhang Zheng, Chengzhang Li
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/15/11/6076
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author Zhenxiang Hao
Jianping Hu
Jin Ran
Xiaohui Sun
Yuhang Zheng
Chengzhang Li
author_facet Zhenxiang Hao
Jianping Hu
Jin Ran
Xiaohui Sun
Yuhang Zheng
Chengzhang Li
author_sort Zhenxiang Hao
collection DOAJ
description Drivers’ visual characteristics have an important impact on traffic safety, but existing studies are mostly limited to single-scene analyses and lack a systematic study on the dynamic changes in drivers’ eye tracking characteristics on different road sections. In this study, 23 drivers were recruited to wear the aSee Glasses eye tracking device and driving tests were conducted on four typical road sections, namely, straight ahead, turning, climbing, and downhill. The average fixation duration, pupil diameter, and the saccade amplitude of the eye tracking were collected, one-way analysis of variance (ANOVA) was used to explore the differences between the different road sections, and a mathematical model of changes in the visual characteristics over time was constructed, based on the fitting of the data. Computerized fitting models of changes over time were also constructed using the Origin 2021 software. The results show that different road sections had significant effects on drivers’ visual tasks: the longest average fixation duration was found in the straight road section, the largest pupil diameter was found in the curved road section, and the highest saccade amplitude was found in the downhill road section, reflecting the influence of the complexity of the driving task on the cognitive load. The fitted model further reveals the dynamic change law of eye tracking indicators over time, providing a quantitative basis for modeling driving behavior and visual tasks. This study provides a theoretical basis and practical reference for the optimal design of advanced driver assistance systems, traffic safety management, and road planning.
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spelling doaj-art-a1555edfe55a4ee1a153cae01d49a1112025-08-20T03:11:30ZengMDPI AGApplied Sciences2076-34172025-05-011511607610.3390/app15116076Characterization of Driver Dynamic Visual Perception Under Different Road Linearity ConditionsZhenxiang Hao0Jianping Hu1Jin Ran2Xiaohui Sun3Yuhang Zheng4Chengzhang Li5School of Traffic and Transportation Engineering, Xinjiang University, Urumqi 830017, ChinaSchool of Traffic and Transportation Engineering, Xinjiang University, Urumqi 830017, ChinaSchool of Traffic and Transportation Engineering, Xinjiang University, Urumqi 830017, ChinaSchool of Traffic and Transportation Engineering, Xinjiang University, Urumqi 830017, ChinaSchool of Traffic and Transportation Engineering, Xinjiang University, Urumqi 830017, ChinaSchool of Traffic and Transportation Engineering, Xinjiang University, Urumqi 830017, ChinaDrivers’ visual characteristics have an important impact on traffic safety, but existing studies are mostly limited to single-scene analyses and lack a systematic study on the dynamic changes in drivers’ eye tracking characteristics on different road sections. In this study, 23 drivers were recruited to wear the aSee Glasses eye tracking device and driving tests were conducted on four typical road sections, namely, straight ahead, turning, climbing, and downhill. The average fixation duration, pupil diameter, and the saccade amplitude of the eye tracking were collected, one-way analysis of variance (ANOVA) was used to explore the differences between the different road sections, and a mathematical model of changes in the visual characteristics over time was constructed, based on the fitting of the data. Computerized fitting models of changes over time were also constructed using the Origin 2021 software. The results show that different road sections had significant effects on drivers’ visual tasks: the longest average fixation duration was found in the straight road section, the largest pupil diameter was found in the curved road section, and the highest saccade amplitude was found in the downhill road section, reflecting the influence of the complexity of the driving task on the cognitive load. The fitted model further reveals the dynamic change law of eye tracking indicators over time, providing a quantitative basis for modeling driving behavior and visual tasks. This study provides a theoretical basis and practical reference for the optimal design of advanced driver assistance systems, traffic safety management, and road planning.https://www.mdpi.com/2076-3417/15/11/6076dynamic visual propertieseye tracking indexesdifferent road sectionsone-way ANOVA
spellingShingle Zhenxiang Hao
Jianping Hu
Jin Ran
Xiaohui Sun
Yuhang Zheng
Chengzhang Li
Characterization of Driver Dynamic Visual Perception Under Different Road Linearity Conditions
Applied Sciences
dynamic visual properties
eye tracking indexes
different road sections
one-way ANOVA
title Characterization of Driver Dynamic Visual Perception Under Different Road Linearity Conditions
title_full Characterization of Driver Dynamic Visual Perception Under Different Road Linearity Conditions
title_fullStr Characterization of Driver Dynamic Visual Perception Under Different Road Linearity Conditions
title_full_unstemmed Characterization of Driver Dynamic Visual Perception Under Different Road Linearity Conditions
title_short Characterization of Driver Dynamic Visual Perception Under Different Road Linearity Conditions
title_sort characterization of driver dynamic visual perception under different road linearity conditions
topic dynamic visual properties
eye tracking indexes
different road sections
one-way ANOVA
url https://www.mdpi.com/2076-3417/15/11/6076
work_keys_str_mv AT zhenxianghao characterizationofdriverdynamicvisualperceptionunderdifferentroadlinearityconditions
AT jianpinghu characterizationofdriverdynamicvisualperceptionunderdifferentroadlinearityconditions
AT jinran characterizationofdriverdynamicvisualperceptionunderdifferentroadlinearityconditions
AT xiaohuisun characterizationofdriverdynamicvisualperceptionunderdifferentroadlinearityconditions
AT yuhangzheng characterizationofdriverdynamicvisualperceptionunderdifferentroadlinearityconditions
AT chengzhangli characterizationofdriverdynamicvisualperceptionunderdifferentroadlinearityconditions