Development of Driver-Behavior Model Based onWOA-RBM Deep Learning Network

المؤلفون المشاركون

Wang, Yaya
Liu, Junhui
Jia, Yajuan

المصدر

Journal of Advanced Transportation

العدد

المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-11، 11ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2020-09-29

دولة النشر

مصر

عدد الصفحات

11

التخصصات الرئيسية

هندسة مدنية

الملخص EN

Human drivers’ behavior, which is very difficult to model, is a very complicated stochastic system.

To characterize a high-accuracy driver behavior model under different roadway geometries, the paper proposes a new algorithm of driver behavior model based on the whale optimization algorithm-restricted Boltzmann machine (WOA-RBM) method.

This method establishes an objective optimization function first, which contains the training of RBM deep learning network based on the real driver behavior data.

Second, the optimal training parameters of the restricted Boltzmann machine (RBM) can be obtained through the whale optimization algorithm.

Finally, the well-trained model can be used to represent the human drivers’ operation effectively.

The MATLAB simulation results showed that the driver model can achieve an accuracy of 90%.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Liu, Junhui& Jia, Yajuan& Wang, Yaya. 2020. Development of Driver-Behavior Model Based onWOA-RBM Deep Learning Network. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1180729

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Liu, Junhui…[et al.]. Development of Driver-Behavior Model Based onWOA-RBM Deep Learning Network. Journal of Advanced Transportation No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1180729

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Liu, Junhui& Jia, Yajuan& Wang, Yaya. Development of Driver-Behavior Model Based onWOA-RBM Deep Learning Network. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1180729

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1180729