Traffic congestion index calculation based on BP neural network
DOI: 10.23977/acss.2021.050103 | Downloads: 30 | Views: 1436
Author(s)
Mingxuan Xia 1
Affiliation(s)
1 Leicester International Institute, Dalian University of Technology, Panjin, Liaoning 124000
Corresponding Author
Mingxuan XiaABSTRACT
Aiming at the problem of traffic congestion, the paper analyzed a large number of traffic congestion data in different regions. After analyzing the data, took speed, day of week, bus count, weather and visibility as the most significant factors of traffic congestion time. These factors were preprocessed with Z-score to unify their dimension. In addition, the Bayesian Regularization training algorithm is selected in the BP neural network model to generate the code for predicting traffic congestion time. There is a high correlation between the result of the model and the real record as expected. Then using the BP neural network to analyze the results, get the prediction results and explore the actual deviation to get the advantages and disadvantages of the model, and put forward the improvement and improvement methods in the future.
KEYWORDS
BP Neural network, traffic congestion, Z-score, Bayesian RegularizationCITE THIS PAPER
Mingxuan Xia. Traffic congestion index calculation based on BP neural network. Advances in Computer, Signals and Systems (2021) 5: 23-27. DOI: http://dx.doi.org/10.23977/acss.2021.050103
REFERENCES
[1] John F. Zaki, Amr Ali-Eldin, Sherif E. Hussein, Sabry F. Saraya, Fayez F. Areed. Trafficcongestion prediction based on Hidden Markov Models and contrast measure [J]. Ain Shams Engineering Journal, 2019.
[2] Banoth Ravi, Jaisingh Thangaraj, Shrinivas Petale. Data Traffic Forwarding for Inter-vehicular Communication in VANETs Using Stochastic Method. Department of Electronics Engineering, Indian Institute of Technology. Wireless Personal Communications, 2019.
[3] Mohammadhani Fouladgar, Mostafa Parchami, Ramez Elmasri, Amir Ghaderi. Scalable deep traffic flow neural networks for urban traffic congestion prediction. 2017 International Joint Conference on Neural Networks (IJCNN), 2251-2258, 2017.
[4] Gang-Len Chang, Chih-Chiang Su. Predicting intersection queue with neural network models. Transportation Research Part C: Emerging Technologies 3 (3), 175-191, 1995.
[5] Brian Smith, Michael Demetsky. Short-term traffic flow prediction: neural network approach. Transportation Research Record, 1994.
[6] Mark Dougherty, Howard Kirby, Roger Boyle. The use of neural networks to recognise and predict traffic congestion. Traffic engineering & control 34 (6), 1993. [7] John Gilmore, Naohiko Abe. Neural network models for traffic control and congestion prediction. Journal of Intelligent Transportation Systems 2 (3), 231-252, 1995.
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