AI Rail Vehicle Control Device for Autonomous Operation
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Solution Overview
Problem
Current rail vehicle control systems require permanent communication with higher-level monitoring devices, limiting independent driving capabilities and relying heavily on signal box supervision.
Innovation Solution
Implementing an AI-based control device trained on predetermined routes using machine learning, which enables direct communication with other rail vehicles and records data for improved control behavior, allowing for autonomous operation and reduced dependency on signal box monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If traditional signal box monitoring is used to control rail vehicles, then safety and centralized control are ensured, but independent driving capability and automation level are limited
Solution Approach 1:
The control device is equipped with AI that enables it to independently control the rail vehicle without continuous external supervision. The system records measurement data during journeys and uses machine learning to improve its own control behavior, making the system self-improving and self-sufficient while maintaining safety
Solution Approach 2:
The patent introduces direct communication between rail vehicles as an intermediary mechanism. Instead of all vehicles communicating through the signal box, vehicles can exchange information directly, reducing the bottleneck and dependency on centralized control while maintaining coordination
2Extent of automation
If AI-based control with machine learning is implemented, then autonomous operation and self-sufficiency are achieved, but data processing requirements and training complexity increase
Solution Approach 1:
The control device performs preliminary data collection by recording measurement data during normal operation. This data is stored and later used for machine learning training, allowing the system to continuously improve its AI capabilities without requiring external intervention or complex real-time processing
Solution Approach 2:
The control device serves multiple functions: it controls the vehicle operation, records measurement data, processes data through machine learning, and communicates with other vehicles. This multi-functionality reduces the need for separate specialized systems and simplifies the overall architecture
3Reliability
If direct communication between rail vehicles is implemented, then coordination and safety are improved, but communication system complexity increases
Solution Approach 1:
The communication functionality is merged with the existing control device rather than being implemented as a separate system. The control device already processes vehicle operation data and controls actuators, so adding communication capabilities leverages existing hardware and software resources, reducing overall system complexity
Data Source
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AI summary
The invention relates, inter alia, to a rail vehicle (10, 11, 12) having a control device (100) for controlling the rail vehicle (10, 11, 12). According to the invention, the control device (100) is based on artificial intelligence and has been trained to control the rail vehicle (10, 11, 12) on at least one predefined section of track.