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Traffic Injury Prevention Volume 17, 2016 - Issue 2
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Original Articles

Development of a method to predict crash risk using trend analysis of driver behavior changes over time

Atsuo MurataDepartment of Intelligent Mechanical Systems, Graduate School of Natural Science and Technology, Okayama University, Okayama, Japan.Correspondence[email protected]
&
Kohei FukudaDepartment of Intelligent Mechanical Systems, Graduate School of Natural Science and Technology, Okayama University, Okayama, Japan.
Pages 114-121 | Received 01 Sep 2014, Accepted 08 May 2015, Published online: 22 Jan 2016

Citations (3)

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Read on this site (1)

Atsuo Murata, Kensuke Naitoh & Waldemar Karwowski. (2017) A method for predicting the risk of virtual crashes in a simulated driving task using behavioural and subjective drowsiness measures. Ergonomics 60:5, pages 714-730.
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Articles from other publishers (2)

Atsuo Murata, Toshihisa Doi & Waldemar Karwowski. (2022) Sensitivity of PERCLOS70 to Drowsiness Level: Effectiveness of PERCLOS70 to Prevent Crashes Caused by Drowsiness. IEEE Access 10, pages 70806-70814.
Crossref
Atsuo Murata, Ippei Kita & Waldemar Karwowski. (2018) Assessment of Driver’s Drowsiness Based on Fractal Dimensional Analysis of Sitting and Back Pressure Measurements. Frontiers in Psychology 9.
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