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Driving Risk Detection Model of Deceleration Zone in Expressway Based on Generalized Regression Neural Network
Joint Authors
Wang, Linhong
Wang, Zhexuan
Tang, Ruru
Qi, Weiwei
Source
Journal of Advanced Transportation
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-10-10
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Drivers’ mistakes may cause some traffic accidents, and such accidents can be avoided if prompt advice could be given to drivers.
So, how to detect driving risk is the key factor.
Firstly, the selected parameters of vehicle movement are reaction time, acceleration, initial speed, final speed, and velocity difference.
The ANOVA results show that the velocity difference is not significant in different driving states, and the other four parameters can be used as input variables of neural network models in deceleration zone of expressway, which have fifteen different combinations.
Then, the detection model results indicate that the prediction accuracy rate of testing set is up to 86.4%.
An interesting finding is that the number of input variables is positively correlated with the prediction accuracy rate.
By applying the method, the dangerous state of vehicles could be released through mobile internet as well as drivers' start of risky behaviors, such as fatigue driving, drunk driving, speeding driving, and distracted driving.
Numerical analyses have been conducted to determine the conditions required for implementing this detection method.
Furthermore, the empirical results of the present study have important implications for the reduction of crashes.
American Psychological Association (APA)
Qi, Weiwei& Wang, Zhexuan& Tang, Ruru& Wang, Linhong. 2018. Driving Risk Detection Model of Deceleration Zone in Expressway Based on Generalized Regression Neural Network. Journal of Advanced Transportation،Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1181701
Modern Language Association (MLA)
Qi, Weiwei…[et al.]. Driving Risk Detection Model of Deceleration Zone in Expressway Based on Generalized Regression Neural Network. Journal of Advanced Transportation No. 2018 (2018), pp.1-8.
https://search.emarefa.net/detail/BIM-1181701
American Medical Association (AMA)
Qi, Weiwei& Wang, Zhexuan& Tang, Ruru& Wang, Linhong. Driving Risk Detection Model of Deceleration Zone in Expressway Based on Generalized Regression Neural Network. Journal of Advanced Transportation. 2018. Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1181701
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181701