A method and system for intelligent arrangement of train route based on machine learning

Abstract

The present invention is a method and system for intelligent arrangement of train routes based on machine learning, which is characterized in that it includes a data collection module, a central processing module, a scheduling module, and a safety monitoring module; Adjustment; the processor in the scheduling module can analyze the safety monitoring data, and transmit the impact analysis data to the data analysis unit of the central processing module, and the data analysis unit can quickly update the data. Compared with the prior art, the present invention adopts the safety monitoring module, which can monitor the running data of trains and tracks at all times, and transmit the abnormal state to the dispatching module in time. The processor in the dispatching module is preset with a large number of abnormal analysis subroutines, which can analyze Abnormal data, and transmit the abnormal processing data to the data analysis unit in the central processing module in time, the train arrangement unit can adjust the train arrangement unit in time, which greatly improves the efficiency of train arrangement and the safety of train operation.

Description

technical field [0001] The invention belongs to the field of train transportation, in particular to a method and system for intelligently arranging train routes based on machine learning. Background technique [0002] During the operation of domestic trains, the arrangement of train schedules is one of the most basic plans before trains run. Usually, before the normal departure of the train, the dispatcher needs to adjust the basic timetable prepared in advance as the train's running plan based on experience, so that the train can run according to the existing plan. In actual operation of trains, timetables are often adjusted due to changes in passenger flow and transportation organization methods to meet actual operational requirements. Therefore, how to efficiently and reliably adjust the timetable plan will help to improve the operation and management level of urban rail transit and the quality of transportation services. [0003] The current timetable is still at the l...

AI Technical Summary

Problems solved by technology

[0003] The current timetable is still at the level of manual compilation and computer-aided compilation, and the automatic compilation of train timetables has not been realized. Therefore, the arrangement of timetables requires dispatchers to spend a lot of time to compile, and even due to the lack of experience of dispatchers, lead to The unbalanced arrangement of the train schedule can easily lead to too few or too many trains picking up and departing at the same time

With the implementation of the precise management of the urban rail system and the opening of the new line, the update frequency of the timetable arrangement of the line is relatively high, which greatly increases the labor intensity of the staff

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