Adaptive Driving Position Control via Zone-Based Probability Estimation
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Solution Overview
Problem
Existing vehicle driving position adjustment systems fail to accurately adapt to individual user preferences, which can change based on environmental conditions and physical state, leading to suboptimal seating and steering configurations.
Innovation Solution
A system that detects environmental and physical information upon user entry, utilizing statistical data and inference models to estimate and adjust the driving position to the user's most likely preference, incorporating sensors for temperature, time, and heart rate, and updating probability data based on user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the driving position is adjusted based only on user figure data from camera and sensor, then the adjustment process is simple, but the accuracy of matching user preference is insufficient
Solution Approach 1:
The environment is divided into multiple environment zones and physical condition is divided into multiple condition zones. Statistical data is stored for each zone combination, allowing the system to select appropriate probability data based on the current zone classification, thereby improving adjustment accuracy without requiring a single complex detection model
Solution Approach 2:
The system dynamically selects statistical data based on detected environment and condition zones. The driving position adjustment is not fixed but adapts according to the current environmental and physical state, enabling the system to respond to changing user preferences while maintaining manageable system complexity
2Adaptability or versatility
If the driving position is adjusted based on fixed profile information from IC card, then the initial setup is quick, but the system cannot adapt to changes in user preference
Solution Approach 1:
Statistical data representing probability distributions of preferred driving positions is pre-calculated and stored for each combination of environment zones and condition zones. This preliminary preparation allows the system to quickly determine optimal positions without real-time computation, adapting to user preference changes while minimizing adjustment time
Solution Approach 2:
The system uses detected environmental and physical condition information as feedback to select appropriate statistical data. This feedback mechanism enables the system to automatically adapt to changing user preferences based on current conditions without requiring manual reconfiguration or additional time for adjustment
Data Source
AI summary
A detector detects at least one of environmental information on the environment and physical information on the user's physical condition, when the user gets into a vehicle. Each of the environment and the physical condition is divided into a plurality of zones. A memory stores statistical data each representing the probability of the user selecting one of the driving positions in the vehicle in one of the zones. One of the driving positions can, from the probabilities allotted to them, be estimated to be optimum for the user in the zone into which the detected information falls. As a result, even if the user's preference in driving position changes with the environment or the user's physical condition in which the user gets into the vehicle, it is possible to adjust the driving position automatically according to the current preference.