Rail Operation Plan Changes Using Staged Disruption Control
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Solution Overview
Problem
Existing operation plan change assistance systems fail to effectively utilize changes in operation plan stages to prevent disruption spread, relying heavily on operator knowledge and experience, especially in complex situations.
Innovation Solution
An operation plan change assistance device and method that generates an operation plan change determination model to create staged change proposals by inputting train operation content and past plan changes, using a neural network to predict and optimize future plan changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a determination model based only on delay amount is used, then the system is simple to operate, but it cannot effectively utilize staged plan changes to prevent disruption spread
Solution Approach 1:
The patent segments the operation plan change process into multiple stages, where the determination model evaluates not only the delay amount but also the combination of plan change types, their implementation order, and potential inconsistencies at each stage. This segmentation allows the system to systematically prevent disruption spread while maintaining operational simplicity through automated multi-criteria evaluation.
2Reliability
If complex multi-stage plan changes are implemented, then disruption spread is prevented, but the system requires extensive operator knowledge and experience
Solution Approach 1:
The determination model operates autonomously to evaluate and determine appropriate staged plan changes without requiring extensive operator knowledge. The system self-services by automatically analyzing delay amounts, plan change combinations, implementation orders, and potential inconsistencies, thereby reducing dependency on operator expertise while maintaining high reliability in preventing disruption spread.
3Reliability
If staged plan changes are implemented to handle complex situations, then disruption spread is controlled, but the system cannot create widely accepted proposals without operator experience
Solution Approach 1:
The determination model incorporates feedback mechanisms that evaluate the acceptability of staged plan changes by analyzing the combination of change types, their order of implementation, and potential inconsistencies. This feedback loop enables the system to create proposals that are both reliable in controlling disruption spread and adaptable to operator preferences, achieving wide acceptance without requiring extensive operator experience.
Data Source
AI summary
An operation plan change assistance system includes a determination model generation unit configured to generate an operation plan change determination model that receives information about a train operation content before a certain point in time and information about a change in an operation plan executed before the point in time and outputs information about a change in operation plan to be executed next; and an operation plan change proposal creation unit configured to input information about a train operation content before a point in time designated by a user and information about a change in an operation plan executed before the designated point in time, create change candidates that are candidates for each change in an operation plan to be executed in stages after the designated point in time, specify a change candidate that satisfies a predetermined condition, and create the specified change candidate as an operation plan change proposal.