Dynamic Timetable Adjustment for Railway Congestion Control
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Solution Overview
Problem
Existing technologies struggle to provide transportation capacity suitable for varying movement demands, particularly in situations where there are insufficient vehicles or delays in vehicle deployment, leading to congestion and operational inefficiencies.
Innovation Solution
A timetable modification device that dynamically updates train schedules based on predicted movement demand, using sensors and historical data to adjust train operations and resource allocation, ensuring optimal capacity and congestion levels across railway lines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the number of trains is increased to reduce congestion and meet higher movement demand, then passenger comfort and service quality improve, but service cost increases and fare may rise
Solution Approach 1:
The patent implements dynamic timetable adjustment that allows train schedules to be flexibly modified in real-time based on actual movement demand. The system can increase train frequency during high-demand periods and reduce it during low-demand periods, replacing the static timetable with a dynamic one that adapts to changing conditions, thereby optimizing the balance between transportation capacity and service cost
Solution Approach 2:
The system changes the parameter of train operation frequency based on predicted movement demand. By using demand prediction results to adjust the number of trains and their schedules, the system optimizes transportation capacity to match actual needs, avoiding the waste of maintaining high capacity during low-demand periods while ensuring sufficient capacity during peak periods
2Quantity of substance
If turn-around time is lengthened to decrease operating density, then the number of trains required decreases, but transportation capacity is reduced and cannot meet higher movement demand
Solution Approach 1:
The system dynamically adjusts turn-around time based on movement demand predictions. During high-demand periods, turn-around time is shortened to increase operating density and transportation capacity. During low-demand periods, turn-around time can be lengthened to reduce the number of trains needed. This dynamic adjustment replaces the fixed turn-around time approach, allowing the system to optimize both the number of trains and transportation capacity according to actual conditions
3Productivity
If the number of vehicles is increased to operate more trains, then transportation capacity increases, but vehicle availability becomes insufficient when spare vehicles are physically deficient
Solution Approach 1:
The system dynamically adjusts train schedules and operating density based on movement demand predictions rather than relying on increasing vehicle inventory. By optimizing the utilization of existing vehicles through flexible timetable adjustment, the system can achieve higher transportation capacity without requiring additional spare vehicles, thus resolving the contradiction between transportation capacity and vehicle availability
4Ease of operation
If train schedules are statically predetermined, then operational simplicity is maintained, but the system cannot adapt to varying movement demand and congestion conditions
Solution Approach 1:
The patent transitions from static timetable management to dynamic timetable adjustment. The system automatically modifies train schedules based on real-time movement demand predictions, replacing the fixed predetermined schedule with a flexible dynamic one that continuously adapts to changing conditions, thereby maintaining ease of operation while dramatically improving demand responsiveness
Solution Approach 2:
The system implements a feedback mechanism where movement demand predictions are continuously fed into the timetable adjustment system. The predicted demand information serves as feedback that triggers automatic schedule modifications, creating a closed-loop control system that maintains operational simplicity while achieving high adaptability to varying demand conditions
Data Source
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AI summary
The present invention makes it possible to supply transportation capacity suitable for movement demand in numerous circumstances. A timetable modification device for changing a timetable representing a train control target, in accordance with a movement demand prediction result indicating, for each time period, the number and destination of passengers at each station at which the train stops, the timetable modification device having a violation position extraction program P01a for calculating the degree of congestion of a train on the basis of predicted demand information representing a movement demand prediction result and extracting a violation position at which the degree of congestion is outside a predetermined allowed range, and a timetable correction program P01b for changing a timetable so as to include a change in the destination of the train so that the degree of congestion of the violation position is within the allowed range or so that the degree of congestion of the violation position approaches the allowed range.