Train Schedule Diagram Processor for Delay Robustness
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Solution Overview
Problem
Railway companies face delays in service planning diagrams, leading to decreased sales and increased costs due to lack of delay robustness in existing scheduling systems.
Innovation Solution
An information processing apparatus and method that calculates adjustment amounts of event times in train schedules based on restriction conditions and evaluation indicators to create diagrams that ensure quick-deliverability and delay robustness, by inputting and processing train line information, event-to-event interval data, and performance requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional scheduling systems are used to create train diagrams, then the scheduling process is simple, but the diagrams lack delay robustness and cause service delays
Solution Approach 1:
The system performs preliminary calculations of adjustment amounts for event times based on restriction conditions and evaluation indicators before actual scheduling decisions are made. This allows the diagram to be pre-optimized for delay robustness, enabling quick response to delays without complex real-time computations.
Solution Approach 2:
The patent replaces manual or simple automated scheduling methods with an information processing apparatus that uses automated calculation algorithms. The system automatically computes adjustment amounts by comparing event times against restriction conditions and evaluation indicators, substituting mechanical scheduling processes with intelligent computational systems.
2Loss of time
If event times are adjusted to improve delay robustness, then passengers arrive earlier and delays are minimized, but the calculation complexity increases
Solution Approach 1:
The scheduling problem is segmented into manageable components: restriction conditions (minimum/maximum time intervals), evaluation indicators (quick-deliverability, delay robustness), and adjustment amount calculations for individual event times. This segmentation allows complex optimization to be broken down into systematic, computable steps that reduce overall calculation complexity.
Solution Approach 2:
The system changes parameters by calculating specific adjustment amounts for event times based on multiple evaluation indicators. Instead of making qualitative scheduling decisions, the system quantitatively adjusts event time parameters to optimize delay robustness while satisfying restriction conditions, thereby reducing delay losses through precise parameter optimization.
3Productivity
If multiple evaluation indicators are used to optimize diagram performance, then quick-deliverability and delay robustness are improved, but the computation time increases
Solution Approach 1:
The system performs preliminary calculations of adjustment amounts using multiple evaluation indicators before the scheduling is executed. By pre-computing the optimal adjustments based on quick-deliverability and delay robustness indicators, the system avoids time-consuming optimizations during actual operations, thereby improving productivity without excessive computation time penalties.
Data Source
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AI summary
An information processing apparatus according to an approach includes a diagram processor configured to calculate, based on a first diagram of first to n-th train lines including at least one time of: times of departure of a vehicle from stop positions, times of arrival of the vehicle at the stop positions, and times of pass of the vehicle through the stop positions, an adjustment amount of the time; and an output diagram creator configured to create a second diagram based on the calculated adjustment amount and the first diagram.