Vehicle Control Using Brain Wave Error Monitoring
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Solution Overview
Problem
Current vehicle control systems do not effectively monitor and respond to passenger intentions and errors in real-time, leading to potential safety issues and inefficient navigation.
Innovation Solution
A mobility controlling method and apparatus that utilizes error monitoring through response-locked Event-Related Potentials (ERPs) such as ERN and Pe to analyze brain wave signals, determining error factors and providing feedback to adjust vehicle operations based on passenger intentions and error detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If brain wave signals are collected and analyzed in real-time to monitor passenger intentions, then passenger safety and comfort are improved, but device complexity and energy consumption increase
Solution Approach 1:
The patent replaces traditional mechanical control interfaces (steering wheels, pedals) with a brain-computer interface that directly detects and responds to passenger intentions through ERP signals. This substitution enables more intuitive and safer control while reducing the complexity of physical interaction mechanisms.
Solution Approach 2:
The patent introduces ERP signals as an intermediary between the passenger's intentions and the vehicle control system. The sensing unit detects ERP signals from the passenger's brain, and the controlling unit translates these signals into appropriate vehicle responses, creating a reliable communication channel that improves safety without requiring complex physical interfaces.
2Measurement precision
If ERP signals are continuously monitored and analyzed, then error detection accuracy is improved, but energy consumption and processing time increase
Solution Approach 1:
The patent employs periodic sampling of ERP signals at specific time points (T1, T2, T3) rather than continuous monitoring. The sensing unit collects ERP signals at predetermined intervals, and the error monitoring unit analyzes these periodic samples to detect errors. This periodic approach maintains detection accuracy while significantly reducing energy consumption compared to continuous monitoring.
Solution Approach 2:
The patent performs preliminary analysis of ERP signal characteristics to identify relevant error-related patterns before full error detection is required. The error monitoring unit is configured to recognize specific ERP patterns (such as error-related negativity) that indicate potential errors, allowing the system to maintain high detection accuracy while minimizing continuous processing demands.
3Reliability
If multiple ERP components (ERN, Pe, CRN, Pc) are analyzed, then error monitoring comprehensiveness is improved, but device complexity and data processing requirements increase
Solution Approach 1:
The patent segments the ERP signal analysis into distinct components (ERN, Pe, CRN, Pc) with specific time windows and analysis parameters for each. The error monitoring unit processes each ERP component separately according to its characteristics, which simplifies the overall processing complexity while maintaining comprehensive error monitoring coverage.
Solution Approach 2:
The patent creates a universal error monitoring framework that can detect multiple types of errors through a single integrated system. The same sensing unit and controlling unit handle all ERP components and error types, making the system multi-functional without proportionally increasing hardware complexity. The system universally applies error detection logic across different ERP signals.
Data Source
AI summary
A mobility controlling method and apparatus based on error monitoring are provided. The mobility controlling method includes: collecting an Event-Related Potential (ERP) for at least one passenger in a mobility for a predetermined time, determining an error factor by analyzing the ERP that is collected for the predetermined time, and performing mobility feedback based on the error factor.