Navigation Controller Adapting Performance to Driver Habits
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current navigation systems operate at a fixed performance level, failing to adapt to individual driver characteristics and varying driving conditions, resulting in suboptimal usability and display performance.
Innovation Solution
An apparatus and method that collect driver characteristic and driving condition data to dynamically adjust navigation performance by prioritizing device operations, using a learning mechanism to determine optimal performance settings for frequently used functions and driving modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If navigation system operates at fixed performance level, then system stability is maintained, but usability and display performance are suboptimal
Solution Approach 1:
The navigation system dynamically adjusts performance parameters based on real-time driving conditions and driver characteristics. The controller modifies display refresh rates, processing priorities, and resource allocation dynamically rather than maintaining fixed performance levels, enabling adaptation to varying operational contexts.
Solution Approach 2:
The system changes operational parameters such as frame per second values, processing priorities, and display performance settings based on collected driver characteristic data and driving condition data. This allows the navigation system to optimize performance parameters for different situations without requiring complete system redesign.
2Loss of information
If controller operates multiple displays, then information output capability is improved, but navigation performance per display is reduced
Solution Approach 1:
The controller applies different performance priorities to different displays based on their specific functions and importance. Critical navigation information receives higher processing priority and performance allocation, while secondary displays receive adjusted resources. This local differentiation optimizes the balance between information output capability and per-display performance.
3Ease of operation
If navigation performance is optimized for specific driver characteristics, then usability is improved, but system complexity increases
Solution Approach 1:
The navigation system automatically collects driver characteristic data and driving condition data, then autonomously determines and applies optimal performance settings without requiring manual user configuration. The system learns and adapts to individual driver preferences over time, improving usability while keeping the interface simple.
Solution Approach 2:
The system continuously monitors driver behavior patterns, usage habits, and driving conditions, then uses this feedback to automatically adjust performance parameters. This closed-loop approach enables the system to optimize usability based on actual usage patterns without increasing operational complexity for the user.
Data Source
AI summary
Provided is a navigation system, which is effectively used depending on driver characteristics and driving conditions, wherein display performance of DUCs including a cluster, front/rear AVNs, and operation systems thereof are controlled through a single controller.