Vehicle Driving Environment Processor for Ideal State Alignment
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Solution Overview
Problem
Conventional information processing systems for vehicles struggle to enable ideal driving conditions, as they often require complex driver interventions and lack effective methods to guide drivers towards optimal vehicle control parameters.
Innovation Solution
An information processing system that acquires N-dimensional vehicle driving parameters and refers to an ideal driving model to recommend adjustments, such as steering angle and acceleration/deceleration, to align the current driving environment with an ideal state, using a processor to display actionable information to the driver.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional information processing systems provide autonomous driving control, then driving automation is improved, but driver guidance towards ideal driving parameters is insufficient
Solution Approach 1:
The system calculates the distance between the current vehicle driving environment and the ideal driving environment region in N-dimensional space, then provides feedback to the driver through the display unit. This feedback mechanism guides the driver to adjust driving parameters to reach the ideal driving state, resolving the contradiction between automation and information loss by adding a closed-loop guidance system.
Solution Approach 2:
The system introduces an intermediary information processing layer that receives autonomous driving control data, compares it with ideal driving parameters stored in the storage unit, and generates guidance information. This intermediary process bridges the gap between automated control and driver awareness, providing actionable recommendations without interfering with autonomous operation.
2Measurement precision
If the system provides detailed recommendation information to guide drivers, then driving precision is improved, but system complexity increases
Solution Approach 1:
The system evaluates driving parameters in N-dimensional space (where N≥2), incorporating multiple parameters such as vehicle speed, steering angle, inter-vehicular distance, and relative speed simultaneously. This multi-dimensional approach enables comprehensive precision assessment without requiring complex individual analysis of each parameter, as the spatial distance calculation naturally integrates all dimensions.
Solution Approach 2:
The system changes the parameter representation by storing ideal driving environment regions as predefined parameter sets in the storage unit. Instead of complex real-time optimization, the system compares current parameters against these pre-defined ideal states, simplifying the processing while maintaining high measurement precision through direct parameter comparison.
3Measurement precision
If the system calculates distance in N-dimensional parameter space, then driving environment assessment accuracy is improved, but computational requirements increase
Solution Approach 1:
The system performs preliminary action by pre-storing ideal driving environment regions with their N-dimensional parameter definitions in the storage unit during system initialization or offline preparation. This pre-processing eliminates the need for complex real-time calculations of ideal states, allowing the processor to simply compare current parameters against pre-computed reference points, thereby reducing computational power requirements while maintaining assessment accuracy.
Data Source
AI summary
An information processing system includes a processor, and the processor acquires a vehicle driving environment composed of N-dimensional parameters, refers to an ideal driving driver model indicating an ideal driving environment region in an N-dimensional coordinate system, and selects one ideal driving environment included in the ideal driving environment region based on a distance between the ideal driving environment region and the acquired vehicle driving environment in the N-dimensional coordinate system.