Vehicle Information Processing System for Driver-Specific Assistance
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Solution Overview
Problem
Existing vehicle assistance systems provide uniform assistance based on map or traffic information, which does not account for individual driver behavior and vehicle-specific conditions, leading to complex and uncomfortable assistance for drivers.
Innovation Solution
A vehicle information processing system that sets operation patterns based on driver-specific driving habits and conditions within specified assistance areas, using operation pattern recognition and database association to determine tailored assistance information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If uniform assistance is provided based on map or traffic information, then the assistance system is simple to implement, but the assistance does not match individual driver behavior leading to driver discomfort
Solution Approach 1:
The assistance system dynamically adapts to individual driver behavior by continuously learning and updating operation patterns specific to each driver. The system transitions from static uniform assistance to dynamic personalized assistance by monitoring accelerator and brake operations, identifying characteristic patterns, and providing tailored guidance that evolves with each driver's habits.
Solution Approach 2:
The system changes the parameter of assistance content based on detected operation patterns. By analyzing variations in accelerator release timing, brake application patterns, and deceleration characteristics, the system modifies assistance parameters to match individual driver behaviors, thereby improving adaptability without requiring complete system redesign.
2Measurement precision
If assistance is tailored to individual driver patterns, then driver comfort and accuracy improve, but the system complexity increases
Solution Approach 1:
The system employs feedback mechanisms by continuously monitoring driver operations, comparing actual behavior against learned patterns, and adjusting assistance timing accordingly. This closed-loop approach enables high measurement precision in determining optimal assistance moments while managing system complexity through iterative learning rather than complex upfront programming.
Solution Approach 2:
The assistance system performs self-learning by automatically detecting and storing operation patterns without requiring manual configuration. The system serves itself by autonomously adapting to each driver's behavior through continuous data collection and pattern recognition, reducing the need for complex external calibration systems.
Data Source
AI summary
There is provided a vehicle information processing system for assisting a driver in a specified assistance area. The vehicle information processing system includes operation pattern setting means for setting an operation pattern in the assistance area on the basis of driving operation information of the driver when the driver enters the assistance area and assistance information determining means for determining assistance information for assisting the driver in the assistance area on the basis of the operation pattern in the assistance area which is set by the operation pattern setting means. According to this structure, it is possible to assist the driver using high-accuracy assistance information corresponding to the operation pattern and thus perform assistance suitable for the driver with high accuracy.