Learning the Car-following Behavior of Drivers Using Maximum Entropy Deep Inverse Reinforcement Learning
المؤلفون المشاركون
المصدر
Journal of Advanced Transportation
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-11-21
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
The present study proposes a framework for learning the car-following behavior of drivers based on maximum entropy deep inverse reinforcement learning.
The proposed framework enables learning the reward function, which is represented by a fully connected neural network, from driving data, including the speed of the driver’s vehicle, the distance to the leading vehicle, and the relative speed.
Data from two field tests with 42 drivers are used.
After clustering the participants into aggressive and conservative groups, the car-following data were used to train the proposed model, a fully connected neural network model, and a recurrent neural network model.
Adopting the fivefold cross-validation method, the proposed model was proved to have the lowest root mean squared percentage error and modified Hausdorff distance among the different models, exhibiting superior ability for reproducing drivers’ car-following behaviors.
Moreover, the proposed model captured the characteristics of different driving styles during car-following scenarios.
The learned rewards and strategies were consistent with the demonstrations of the two groups.
Inverse reinforcement learning can serve as a new tool to explain and model driving behavior, providing references for the development of human-like autonomous driving models.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhou, Yang& Fu, Rui& Wang, Chang. 2020. Learning the Car-following Behavior of Drivers Using Maximum Entropy Deep Inverse Reinforcement Learning. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1175666
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhou, Yang…[et al.]. Learning the Car-following Behavior of Drivers Using Maximum Entropy Deep Inverse Reinforcement Learning. Journal of Advanced Transportation No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1175666
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhou, Yang& Fu, Rui& Wang, Chang. Learning the Car-following Behavior of Drivers Using Maximum Entropy Deep Inverse Reinforcement Learning. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1175666
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1175666
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