Traffic Status Prediction of Arterial Roads Based on the Deep Recurrent Q-Learning
Joint Authors
Hao, Wei
Gao, Zhibo
Yi, Kefu
Rong, Donglei
Zeng, Qiang
Wu, Wenguang
Wei, Chongfeng
Scepanovic, Biljana
Source
Journal of Advanced Transportation
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-19
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
With the exponential growth of traffic data and the complexity of traffic conditions, in order to effectively store and analyse data to feed back valid information, this paper proposed an urban road traffic status prediction model based on the optimized deep recurrent Q-Learning method.
The model is based on the optimized Long Short-Term Memory (LSTM) algorithm to handle the explosive growth of Q-table data, which not only avoids the gradient explosion and disappearance but also has the efficient storage and analysis.
The continuous training and memory storage of the training sets are used to improve the system sensitivity, and then, the test sets are predicted based on the accumulated experience pool to obtain high-precision prediction results.
The traffic flow data from Wanjiali Road to Shuangtang Road in Changsha City are tested as a case.
The research results show that the prediction of the traffic delay index is within a reasonable interval, and it is significantly better than traditional prediction methods such as the LSTM, K-Nearest Neighbor (KNN), Support Vector Machines (SVM), exponential smoothing method, and Back Propagation (BP) neural network, which shows that the model proposed in this paper has the feasibility of application.
American Psychological Association (APA)
Hao, Wei& Rong, Donglei& Yi, Kefu& Zeng, Qiang& Gao, Zhibo& Wu, Wenguang…[et al.]. 2020. Traffic Status Prediction of Arterial Roads Based on the Deep Recurrent Q-Learning. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1176315
Modern Language Association (MLA)
Hao, Wei…[et al.]. Traffic Status Prediction of Arterial Roads Based on the Deep Recurrent Q-Learning. Journal of Advanced Transportation No. 2020 (2020), pp.1-17.
https://search.emarefa.net/detail/BIM-1176315
American Medical Association (AMA)
Hao, Wei& Rong, Donglei& Yi, Kefu& Zeng, Qiang& Gao, Zhibo& Wu, Wenguang…[et al.]. Traffic Status Prediction of Arterial Roads Based on the Deep Recurrent Q-Learning. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1176315
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1176315