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Traffic Injury Prevention Volume 18, 2017 - Issue 2
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Original Articles

Can variations in visual behavior measures be good predictors of driver sleepiness? A real driving test study

Yonggang WangSchool of Highway, Chang'an University, Xi'an, Shaanxi, ChinaCorrespondence[email protected]
,
Mengyang XinSchool of Highway, Chang'an University, Xi'an, Shaanxi, China
,
Han BaiDepartment of Transportation & Logistics Engineering, Shandong Jiaotong University, Jinan, Shandong, China
&
Yangdong ZhaoCCCC First Highway Consultants Co., Ltd., Xi'an, Shaanxi, China
Pages 132-138 | Received 30 Oct 2015, Accepted 14 Jun 2016, Published online: 19 Jan 2017

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Valeriia Demareva, Valeriia Viakhireva, Irina Zayceva, Inna Isakova, Yana Okhrimchuk, Karina Zueva, Andrey Demarev, Nikolay Nazarov & Julia Edeleva. (2023) Temporal dynamics of subjective sleepiness: A convergence analysis of two scales. Biological Rhythm Research 54:4, pages 369-384.
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Sylwia I. Kaduk, Aaron P. J. Roberts & Neville A. Stanton. (2021) The circadian effect on psychophysiological driver state monitoring. Theoretical Issues in Ergonomics Science 22:5, pages 619-649.
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Articles from other publishers (14)

Hengyan Pan, Haijing He, Yonggang Wang, Yanqiu Cheng & Zhe Dai. (2023) The impact of non-driving related tasks on the development of driver sleepiness and takeover performances in prolonged automated driving. Journal of Safety Research.
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Christopher N. Watling & Madison Home. (2022) Hazard perception performance and visual scanning behaviours: The effect of sleepiness. Transportation Research Part F: Traffic Psychology and Behaviour 90, pages 243-251.
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Christopher N. Watling, Grégoire S. Larue, Joanne M. Wood & Alexander Black. (2022) An on-road examination of daytime and evening driving on rural roads: physiological, subjective, eye gaze, and driving performance outcomes. Attention, Perception, & Psychophysics 84:2, pages 418-426.
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Azhar Quddus, Ali Shahidi Zandi, Laura Prest & Felix J.E. Comeau. (2021) Using long short term memory and convolutional neural networks for driver drowsiness detection. Accident Analysis & Prevention 156, pages 106107.
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Maria Rosaria De Blasiis, Chiara Ferrante & Valerio Veraldi. 2020. Advances in Safety Management and Human Factors. Advances in Safety Management and Human Factors 329 341 .
Yonggang Wang, Ye Luo & Fayu Chen. (2019) Interpreting risk factors for truck crash severity on mountainous freeways in Jiangxi and Shaanxi, China. European Transport Research Review 11:1.
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Ali Shahidi Zandi, Azhar Quddus, Laura Prest & Felix J. E. Comeau. (2019) Non-Intrusive Detection of Drowsy Driving Based on Eye Tracking Data. Transportation Research Record: Journal of the Transportation Research Board 2673:6, pages 247-257.
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Yonggang Wang, Linchao Li & Carlo G. Prato. (2019) The relation between working conditions, aberrant driving behaviour and crash propensity among taxi drivers in China. Accident Analysis & Prevention 126, pages 17-24.
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Alistair W. MacLean. 2019. Handbook of Sleep Research. Handbook of Sleep Research 611 622 .
Yonggang Wang & Jingfeng Ma. (2018) Automation Detection of Driver Fatigue Using Visual Behavior Variables. Archives of Civil Engineering 64:2, pages 175-185.
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Hilal Al-libawy, Ali Al-Ataby, Waleed Al-Nuaimy & Majid A. Al-Taee. (2018) Modular design of fatigue detection in naturalistic driving environments. Accident Analysis & Prevention 120, pages 188-194.
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Xingqiang Ba, Feifei Zhou & Yonggang Wang. (2018) Predicting personal injury crash risk through working conditions, job strain, and risky driving behaviors among taxi drivers. European Transport Research Review 10:2.
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Yonggang Wang, Chengxi Ma & Yanhui Li. (2018) Effects of Prolonged Tasks and Rest Patterns on Driver's Visual Behaviors, Driving Performance, and Sleepiness Awareness in Tunnel Environments: A Simulator Study. Iranian Journal of Science and Technology, Transactions of Civil Engineering 42:2, pages 143-151.
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Brook A. Shiferaw, Luke A. Downey, Justine Westlake, Bronwyn Stevens, Shantha M. W. Rajaratnam, David J. Berlowitz, Phillip Swann & Mark E. Howard. (2018) Stationary gaze entropy predicts lane departure events in sleep-deprived drivers. Scientific Reports 8:1.
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