Adaptive Train Dwell Scheduling Using Real-Time Passenger Data
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Solution Overview
Problem
Conventional railway scheduling systems fail to dynamically adjust train dwell times at platforms based on real-time passenger data, leading to unnecessary delays due to assumptions about passenger numbers and platform conditions, which can conflict with overall scheduling efficiency and timeliness.
Innovation Solution
A railway scheduling system that utilizes wireless communication with passenger devices and platform cameras to gather real-time data on passenger destinations, numbers, and platform characteristics, employing machine-learning models to predict optimal dwell times for trains, thereby adjusting schedules dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a fixed dwell time is assumed for all trains regardless of actual passenger conditions, then scheduling is simplified and easier to manage, but unnecessary delays occur and scheduling efficiency deteriorates
Solution Approach 1:
The patent applies dynamics by transitioning from static fixed dwell times to dynamic adaptive dwell times. The system continuously collects real-time passenger data (boarding/alighting rates, platform congestion, weather conditions) and adjusts dwell times dynamically for each train based on current conditions, allowing the scheduling system to adapt flexibly rather than relying on predetermined fixed values
Solution Approach 2:
The patent implements feedback mechanisms by collecting real-time data from sensors, passenger mobile devices, and operational systems. This feedback loop provides continuous information about actual passenger flow and platform conditions, enabling the scheduling system to adjust dwell times based on observed conditions rather than assumptions, thereby improving scheduling efficiency while maintaining operational simplicity
2Reliability
If dwell time is extended to ensure sufficient passenger boarding and alighting, then passenger safety and comfort are improved, but train timeliness and track utilization deteriorate
Solution Approach 1:
The patent applies parameter changes by adjusting dwell time based on multiple dynamic parameters including passenger flow rates, platform congestion levels, weather conditions, and train type. Rather than using a single fixed dwell time, the system modifies the time parameter dynamically to match actual conditions, ensuring sufficient time for safe passenger operations while minimizing unnecessary delays
Solution Approach 2:
The patent implements preliminary action by predicting passenger boarding and alighting numbers in advance using historical data and real-time information. The system prepares optimal dwell time recommendations before the train arrives, allowing operators to plan accordingly and avoid both excessive delays and insufficient boarding time, thus balancing safety and timeliness
3Measurement precision
If real-time passenger data collection systems are implemented, then scheduling accuracy and timeliness are improved, but system complexity and infrastructure requirements increase
Solution Approach 1:
The patent applies universality by designing a multi-functional data collection system that serves multiple purposes simultaneously. The same sensor network and data collection infrastructure supports not only dwell time optimization but also passenger flow monitoring, safety surveillance, and operational analytics, thereby reducing overall system complexity through consolidation rather than requiring separate dedicated systems for each function
Solution Approach 2:
The patent implements self-service by enabling the system to automatically collect, process, and analyze passenger data without extensive manual intervention. Automated algorithms process the collected information and generate dwell time recommendations, reducing the need for complex manual scheduling operations and simplifying the overall system architecture while maintaining high measurement precision
Data Source
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AI summary
A method for scheduling a train travelling along a railway track to stop at a platform is disclosed. The method comprises initiating wireless radio communication via a wireless radio communication system with rail passenger wireless communication devices, sending respective requests to the rail passenger wireless communication devices via the wireless radio communication system requesting data representing an intended destination of travel of the respective passengers, receiving respective responses from the rail passenger wireless communication devices via the wireless radio communication system including the requested data representing an intended destination of travel of the respective passengers, determining based on the received responses destinations of the passengers, determining based on the determined destinations of passengers a number of passengers likely to use the platform to board and/or disembark the train, computing based on the determination of the number of passengers using the platform to board and/or disembark the train a time period for the train to stop at the platform, and outputting a schedule signal representing the computed time period.