Driving Position Estimation via Segmented Likelihood
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Solution Overview
Problem
Existing vehicle seat and steering adjustment systems fail to provide a perfect fit for users when transitioning from one vehicle model to another, as they do not account for individual user preferences and varying vehicle configurations.
Innovation Solution
A driving position adjusting system that includes a storage device for statistical data on user preferences, a detection device to identify user selections, an estimation device to calculate the most probable optimal driving position in a second vehicle based on Bayesian inference, and a control device to adjust the driving position accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If coordinate data on three-dimensional coordinate axes using accelerator pedal position as reference is used to adjust device settings in different vehicle types, then the adjustment process can be standardized across vehicle models, but the adjustment result may not provide a perfect fit due to different seat configurations in different vehicle types
Solution Approach 1:
The patent changes the reference parameter from accelerator pedal position to steering wheel position, and introduces probabilistic parameters (likelihood values) to represent user preferences. This allows the system to adapt to different vehicle configurations while maintaining adjustment accuracy by using statistically derived preferences rather than fixed coordinate mappings
Solution Approach 2:
The patent creates a probabilistic preference model that copies user adjustment behaviors across different vehicle types. Instead of directly copying coordinate data, it copies the statistical patterns of user preferences and applies them to estimate optimal positions in different vehicle configurations
2Measurement precision
If statistical data on user preferences is collected and stored for multiple vehicle types, then the estimation accuracy for optimal driving position can be improved, but the data storage and processing complexity increases
Solution Approach 1:
The patent segments the adjustable range of each device into multiple divided ranges and calculates separate likelihood values for each segment. This segmentation approach simplifies the statistical data structure compared to storing continuous coordinate data, while still providing accurate estimation by identifying the most probable range segment
Solution Approach 2:
The patent transforms complex continuous position data into discrete probabilistic segments. By converting continuous adjustment ranges into divided segments with associated likelihood values, the system reduces data complexity while maintaining estimation accuracy through statistical inference
Data Source
AI summary
A driving position adjusting system automatically adjusts a driving position in a second vehicle appropriately to a target user based on a driving position in a first vehicle adjusted by the target user. The driving position adjusting system includes a storage device, a detection device, an estimation device, a transmission device, and a control device. The storage device stores statistic data. The detection device detects a selected one of a plurality of divided range segments of the driving position in the first vehicle, the selected one being selected by the target user. The estimation device estimates an optimum one of the plurality of divided range segments in the second vehicle based on the statistic data and the selected one. The transmission device transmits to the second vehicle the optimum one in the second vehicle. The control device controls the driving position in the second vehicle correspondingly to the optimum one.