Prediction for Percentage of Vehicle Entering Expressway Rest Area Based on BP Neural Network

Abstract:

In order to scientifically decide the percentage of vehicle entering expressway rest area, based on analyzing the influencing factors relating to the percent of mainline traffic stopping, a BP neural network prediction model for it was put forward. Finally, The Xinzheng Rest Area (XRA) was taken as an example for verifying the feasibility of the prediction model and determining the influence degree of the Shijiazhuang-Wuhan high-speed railway on the percentage of mainline vehicles entering XRA. The result shows that the model had a high precision and reliability.

• Periodical: Applied Mechanics and Materials (Volumes 178-181)
• Pages: 1956-1960
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.178-181.1956
• Online since: May 2012
• Authors: Xiao Yan Shen, Hao Xue Liu, Jia Liu
• Keywords: BP Neural Network (BPNN), Expressway, Percentage of Vehicle Entering Expressway Rest Area, Rest Area

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