Driving Risk Detection Model of Deceleration Zone in Expressway Based on Generalized Regression Neural Network
المؤلفون المشاركون
Wang, Linhong
Wang, Zhexuan
Tang, Ruru
Qi, Weiwei
المصدر
Journal of Advanced Transportation
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-10-10
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص 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.
نمط استشهاد جمعية علماء النفس الأمريكية (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
نمط استشهاد الجمعية الأمريكية للغات الحديثة (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
نمط استشهاد الجمعية الطبية الأمريكية (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
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1181701
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر