Research on Speed Limit of Freeway Tunnel Group Based on Artificial Neural Network

Abstract:

According to the traffic conditions in the typical freeway tunnel group in China, an artificial neural network model is constructed for the purpose of predicting the operating speed in freeway tunnel group in this paper. In this model, some input variables are selected from four aspects, including time factors, traffic dynamic factors, road conditions and tunnel environment, and the output variable is the operating speed. Then the sensitivity analysis method is selected to study the effects of input variables on output variable. The results show that this algorithm can avoid the difficulty of constructing traffic flow model comparing to the traditional algorithm, and it is suitable to realize online modeling for speed limit of freeway tunnel group. Results of this research are practical and effective, and it may provide a theoretical foundation for speed limit of freeway tunnel group.

• Periodical: Applied Mechanics and Materials (Volumes 97-98)
• Pages: 892-895
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.97-98.892
• Online since: September 2011
• Authors: Sheng Rui Zhang, Hui Li Yan, Wen Jing Niu, Rui Cao
• Keywords: Artificial Neural Network (ANN), Freeway Tunnel Group, Speed Limit, Traffic Engineering (TE)

References

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