This paper is concerned with the design of expressway toll station problem based on neural network and traffic flow. Firstly, the design of the toll plaza is mainly through analyzing the daily traffic flow, different charging mode of construction cost and waiting time of the United States. Secondly, exploring traffic conditions is divided into two kinds, based on the traffic flow speed-density flow model. Then, a fuzzy-BP neural network model is constructed, with capacity, cost, and safety factor as the input layers and performance as the output layer. It is concluded that this scheme will reduce the occurrence of traffic accidents, so it is desirable. Considering that the increase in unmanned vehicles will lead to an increase in safety performance, we increase the number of electronic toll stations to improve security performance and reduce the occurrence of traffic accidents.
References
[1]
American Embassy in China (2016) An Overview of the Current Status of American Freeway Charges. http://blog.sina.com.cn/s/blog_67f297b00102wo16.html
[2]
Mo, Z., Yu, J. and Sun, Y. (2003) Poisson Distribution Based Mathematic Model of Producing Vehicles in Microscopic Traffic Simulator. Journal of Wuhan University of Technology, No. 1, 73-75.
[3]
Wang, L. (2013) Constrained Differential Evolution Algorithm for Computing Rank Weights with Analytic History Process. Henan Science, No. 8, 1140-1144.
[4]
Kim, J.G., Kwon, S.T., Yoon, S.C., et al. (2011) Infrared Thermographic Analysis of Railway Brake Disc during Braking. Key Engineering Materials, 488-489, 597-600.
[5]
Chen J.Q., Qian W. and Zhang, C. (2017) Research on Model Optimization Design of Expressway Toll Station. Journal of Times, No. 20.
[6]
Jiang, S.F. and Zhang, S. (2008) Damage Identification Method of Data Fusion Structure Based on Fuzzy Neural Network. Engineering Mechanics, 25, 95-101.
[7]
Yu, J., Zhang, J., Wu, J. and Wang, X. (2015) Evaluation and Strategic Research on Sustainable Supply of Important Mineral Resources. Economic Daily Press, St. Thomas.
[8]
Liu, N., Yang, Y. and Zhao, Y.M. (2009) Evaluation of Teaching Quality with Fuzzy-BP Neural Network. Journal of Sichuan University of Science & Engineering, No. 3, 29-31.
[9]
Satiprasad, S. and Anirban, D. (2016) Environmental Vulnerability Assessment Using Grey Analytic Hierarchy Process Based Model. Elsevier Inc., Haryana, 23-25.