E3S Web Conf.
Volume 253, 20212021 International Conference on Environmental and Engineering Management (EEM 2021)
|Number of page(s)||4|
|Section||Intelligent Environmental Monitoring and Quality Technology Assessment|
|Published online||06 May 2021|
Short-term Traffic Flow Prediction Based on Deep Learning Model
China Automotive Technology & Research Center Co., Ltd. Tianjin, China
In order to improve the prediction accuracy of the intelligent transportation system and provide effective support for the dynamic control and guidance of the highway management department, with the goal of minimizing the short-term traffic flow prediction error, the long-term short-term memory (LSTM) model is trained, fitted and adjusted based on the deep learning framework. In addition, the established model is used to predict the short-term traffic flow of the expressway during holidays and working days. At the same time, the traffic flow was simulated by microscopic simulation software to further verify the feasibility of the LSTM algorithm.
© The Authors, published by EDP Sciences, 2021
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