High-speed train parking control method and system based on deep learning

Abstract

The invention discloses a high-speed train parking control method and system based on deep learning, and relates to the technical field of rail transit management and control. The method comprises thesteps of: obtaining a training data set; establishing a convolutional neural network; training and optimizing the convolutional neural network by using the training data set to obtain an optimized convolutional neural network; acquiring actual operation data of a to-be-controlled train; inputting the actual operation data into the optimized convolutional neural network to obtain a parking position of the to-be-controlled train; judging whether the parking position of the to-be-controlled train is 0 or not; if so, outputting a brake command; and if not, returning to the step of acquiring the actual operation data of the to-be-controlled train. Accurate parking of the high-speed train can be achieved without a large amount of cost.

Description

technical field

[0001] The invention relates to the technical field of rail traffic management and control, in particular to a high-speed train parking control method and system based on deep learning. Background technique

[0002] Rail transportation has been fully developed in my country due to its advantages of energy saving, comfort, environmental protection, safety, punctuality and convenience. High-speed railways can not only greatly reduce the travel cost of passengers and reduce the burden on passengers, but also drive the economy along the line and narrow regional differences. As of the end of 2019, the operating mileage of China's high-speed railways has reached 35,000 kilometers, accounting for more than two-thirds of the world. In 2019, the number of passengers sent by China's high-speed railway sports trains ranked first in the world, with a cumulative total of 2.29 billion for the year person-times. As one of the seven major areas of new infrastructure, high-...

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