Train cooperative operation control method based on reference deep reinforcement learning

Abstract

The invention discloses a train cooperative operation control method based on reference deep reinforcement learning, and the method specifically comprises the steps: building a train cooperative operation simulation environment, setting a train safety distance and the like, and calculating the estimated shortest real-time distance of two trains; setting a reward function, and establishing an input dimensionality reduction reinforcement learning algorithm controller; a reference controller is added, when the train meets a reference control strategy condition, a reference control signal is used for replacing a reinforcement learning control signal, and the part of data is used for optimizing a reinforcement learning control strategy; training the network until the global reward of the network is optimal and the control result is combined with the expectation, and considering that the preliminary training of the network is completed; and loading the reference control strategy and the reinforcement learning control strategy on the real train, and outputting a train control signal according to the real train information to complete the cooperative operation control of the train. According to the method, the optimal strategy training speed is increased, and the robustness of the control strategy in the actual operation process is ensured.

Description

Technical field [0001] The present invention is the field of coordinated control technology of the train, and especially involves a coordinated control method based on the reference to deeply enhanced learning. Background technique [0002] As an important infrastructure and popular transportation of the country, the railway is in the backbone position in China's comprehensive transportation system. With the continuous acceleration of my country's urbanization process and the continuous expansion of urban scale, rail transit construction has entered a period of rapid development, and the role of rail transportation has become more important in the choice of people's travel methods. The scale and quality of the road network, the level of modernization of technical equipment, and the volume of passenger and freight have reached the world's cash or even leading levels. China has become a veritable railway country. [0003] However, China Railway still has insufficient in terms of co...

AI Technical Summary

Problems solved by technology

[0008]Finally, the previous control algorithms were designed based on the idealized mathematical modeling of the train system and the linear fitting of some nonlinear conditions, so in real In the environment, due to problems such as device wear and aging, it is impossible to change its control strategy parameters according to the equipment

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