Method and system for controlling heavy-haul train based on reinforcement learning
US11205124B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 26, 2021 |
| Grant date | Dec 21, 2021 |
| Priority date | — |
| Expiry date | Feb 26, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/044
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure provides a method and system for controlling a heavy-haul train based on reinforcement learning. The method includes: obtaining operation state information of a heavy-haul train at a current time point; obtaining a heavy-haul train action of a next time point according to the operation state information of the heavy-haul train at the current time point and a heavy-haul train virtual controller, and sending the heavy-haul train action of the next time point to a heavy-haul train control unit to control operation of the heavy-haul train. The heavy-haul train virtual controller is obtained by training a reinforcement learning network according to operation state data of the heavy-haul train and an expert strategy network; the reinforcement learning network includes one actor network and two critic networks; the reinforcement learning network is constructed according to a soft actor-critic (SAC) reinforcement learning algorithm.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.