== Abstract ==

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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.

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Document type: Article

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== Full document ==

<pdf>Media:Draft_Content_684620146-beopen459-9030-document.pdf</pdf>

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== Original document ==

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The different versions of the original document can be found in:

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* [http://downloads.hindawi.com/journals/jat/2018/8014385.pdf http://downloads.hindawi.com/journals/jat/2018/8014385.pdf] under the license https://creativecommons.org/licenses/by

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* [http://dx.doi.org/10.1155/2018/8014385 http://dx.doi.org/10.1155/2018/8014385] under the license cc-by

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* [http://downloads.hindawi.com/journals/jat/2018/8014385.pdf http://downloads.hindawi.com/journals/jat/2018/8014385.pdf],

: [http://downloads.hindawi.com/journals/jat/2018/8014385.xml http://downloads.hindawi.com/journals/jat/2018/8014385.xml],

: [http://dx.doi.org/10.1155/2018/8014385 http://dx.doi.org/10.1155/2018/8014385] under the license http://creativecommons.org/licenses/by/4.0

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* [http://dx.doi.org/10.1155/2018/8014385 http://dx.doi.org/10.1155/2018/8014385],

: [https://doaj.org/toc/0197-6729 https://doaj.org/toc/0197-6729],

: [https://doaj.org/toc/2042-3195 https://doaj.org/toc/2042-3195] under the license http://creativecommons.org/licenses/by/4.0/

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* [https://www.hindawi.com/journals/jat/2018/8014385 https://www.hindawi.com/journals/jat/2018/8014385],

: [http://downloads.hindawi.com/journals/jat/2018/8014385.pdf http://downloads.hindawi.com/journals/jat/2018/8014385.pdf],

: [https://opus.lib.uts.edu.au/bitstream/10453/134383/1/8014385.pdf https://opus.lib.uts.edu.au/bitstream/10453/134383/1/8014385.pdf],

: [https://opus.lib.uts.edu.au/handle/10453/134383 https://opus.lib.uts.edu.au/handle/10453/134383],

: [https://academic.microsoft.com/#/detail/2896124624 https://academic.microsoft.com/#/detail/2896124624]

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