Driving strategy determination method, device, electronic device and storage medium
By constructing the directed acyclic map and energy consumption boundary matrix of the target route in the train automatic driving system, the driving strategy is pruned, which solves the problems of large calculation volume and low accuracy in the existing technology, and achieves efficient and accurate driving strategy planning.
CN115675583BActive Publication Date: 2025-04-04NAT HIGH SPEED TRAIN QINGDAO TECH INNOVATION CENT +1
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Patent Information
- Application Number
- CN202110863230.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2021-07-29
- Publication Date
- 2025-04-04
- Estimated Expiration
- 2041-07-29
AI Technical Summary
Technical Problem
The existing train autonomous driving system has a large amount of calculation in energy saving optimization, which is difficult to meet real-time requirements, and the accuracy of driving strategy planning is low.
Method used
By determining the directed acyclic graph of the target route, identifying the attribute information of multiple pass points and nodes, building an energy consumption boundary matrix, and pruning the driving strategy to obtain the optimal target driving strategy.
Benefits of technology
The calculation process of driving strategy planning is simplified, the accuracy of the strategy is improved, and the real-time requirements are met.
✦ Generated by Eureka AI based on patent content.
Abstract
The present disclosure relates to a driving strategy determination method, device, electronic device and storage medium, which determines a directed acyclic graph including a plurality of driving strategies corresponding to a target route and a plurality of pass points in the target route, determines an energy consumption boundary matrix according to the first attribute information of the nodes in each driving strategy, the second attribute information of the paths connecting the nodes and the third attribute information of the pass points, and further prunes each driving strategy according to the first attribute information of each node, the second attribute information of each path and the energy consumption boundary matrix, and obtains a target driving strategy corresponding to the target route. The embodiment of the present disclosure prunes each driving strategy through the attributes of the pass points in the target route and the attributes of the nodes and paths in the directed acyclic graph, thereby achieving the solution of the accurate optimal driving strategy, simplifying the calculation process, satisfying the real-time nature of the calculation process, and improving the accuracy of the final driving strategy.
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