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- Title
自学习算法在列车自动驾驶系统的应用.
- Authors
薛文静; 张东海
- Abstract
Domestic train control has the characteristics of multi-objective, large delay, uncertainty and so on. With the wisdom development of urban rail transit, these problems are increasingly prominent. There is an urgent need for self-learning algorithm to adapt to the changing characteristics of the circuit and reduce the cost of manual debugging. The self-learning algorithm can identify the environmental changes and improve the algorithm automatically, which is suitable for the current development stage of rail transit. This paper summarizes the new challenges of the existing algorithms of automatic train operation system, introduces the key technologies and indicators, current situation, problems and shortcomings of the existing algorithms, and then analyzes the application direction of self-learning algorithm in the automatic train operation system, finally prospects the self-learning algorithm to help the construction of intelligent transportation.
- Subjects
URBAN growth; DEBUGGING; ALGORITHMS; WISDOM; URBAN transit systems; INTELLIGENT transportation systems
- Publication
Railway Signalling & Communication Engineering, 2022, Vol 19, Issue 10, p68
- ISSN
1673-4440
- Publication type
Article
- DOI
10.3969/j.issn.1673-4440.2022.10.013