Train Track Data Verification System Using GPS and Aggregate Positioning
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Solution Overview
Problem
Current train management and control systems face limitations in accurately collecting, processing, and maintaining track and train data, leading to potential safety issues due to errors in initial data creation and processing speeds of on-board controllers, which affect safe and effective train operation.
Innovation Solution
A data improvement system and method that includes an initial database and a verification database, with a processing device to receive and compare data fields, determine error data, and provide corrected track and train data, ensuring accurate track positioning and operation by utilizing GPS inputs and aggregate position data from multiple trains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If more data is collected and processed to improve track database accuracy, then data accuracy improves, but processing time and system complexity increase
Solution Approach 1:
The system segments track data into multiple data fields (e.g., geographic coordinates, elevation, gradient, curve information) that can be independently verified and processed. This allows parallel processing of different data aspects, improving overall processing efficiency while maintaining comprehensive accuracy checks.
Solution Approach 2:
The system performs preliminary data validation and error checking during the data collection and initial processing stages, rather than waiting for complete data assembly. This early detection and correction approach reduces the need for reprocessing and accelerates the overall data improvement workflow.
2Reliability
If more data fields are verified and processed, then data reliability improves, but device complexity increases
Solution Approach 1:
The processing device is designed with multi-functional capabilities to handle various data field verifications (geographic accuracy, elevation data, gradient information, curve parameters) using a unified processing framework. This universal approach improves data reliability across multiple parameters without proportionally increasing system complexity.
Solution Approach 2:
The system implements feedback mechanisms where verification results from one data field inform the processing of subsequent fields. Error patterns detected in initial verifications trigger targeted additional checks in related data fields, creating an adaptive verification process that improves reliability while managing complexity through intelligent resource allocation.
3Reliability
If comprehensive track data is maintained in the database, then operational safety improves, but data processing speed decreases
Solution Approach 1:
The system applies different verification and processing intensities to different data fields based on their criticality to operational safety. High-priority fields (e.g., track geometry, gradient, curve information) receive comprehensive verification, while less critical fields undergo streamlined processing. This differentiated approach maintains safety-critical accuracy while preserving overall processing speed.
Data Source
AI summary
A data improvement system, including an initial database, a verification database, and a processing device in communication with the initial database and the verification database. The processing device receives data from the initial database and the verification database, and determines verification data based thereon. A track data improvement system and a track database improvement system are also disclosed.