Vehicle Settings Transfer via Server-Side Profile Translation
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Solution Overview
Problem
Current vehicle systems lack mechanisms to transfer and adapt a vehicle operator's preferred settings from one vehicle to another, as settings such as throttle sensitivity, seat positions, and lighting configurations are specific to each vehicle's configuration, making it difficult to use preferred settings across different vehicles.
Innovation Solution
A system comprising vehicle computers, data collectors, a network, and a server with a predictor module and classifier module that uses collected data, vehicle data, and profile data to generate and translate settings for different vehicles, employing predictive modeling and machine-learning techniques to create universal representation models for vehicle settings, allowing for the adaptation of settings across various vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If vehicle settings are customized for each specific vehicle configuration, then the settings are optimized for that vehicle's performance and comfort, but the settings cannot be transferred to other vehicles with different configurations
Solution Approach 1:
The patent segments vehicle settings into two distinct layers: (1) operator-specific preferences and behavioral patterns, and (2) vehicle-specific configuration parameters. This segmentation allows operator profiles to be transferred across vehicles while vehicle-specific parameters remain localized to each vehicle's configuration, resolving the contradiction between customization and transferability.
Solution Approach 2:
The patent introduces a server as an intermediary that stores operator profiles and facilitates the transfer of settings between vehicles. The server acts as a mediator that receives vehicle data from multiple vehicles, processes operator preferences, and generates adapted settings for different vehicle configurations, enabling settings transferability without sacrificing optimization.
2Adaptability or versatility
If a universal settings model is used across all vehicles, then settings can be transferred between vehicles, but the settings cannot be optimized for vehicle-specific configurations
Solution Approach 1:
The patent applies local quality by allowing different parts of the settings system to have different levels of universality. Operator preferences (e.g., climate control preferences, seat position preferences) are made universal and transferable, while vehicle-specific parameters (e.g., throttle sensitivity, brake sensitivity) are localized to each vehicle's configuration. This enables partial transferability without sacrificing vehicle-specific optimization.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting settings parameters based on the target vehicle's configuration data. When transferring settings from one vehicle to another, the system modifies parameters to match the destination vehicle's capabilities and specifications, ensuring optimization for each vehicle while maintaining the ability to transfer settings across the fleet.
3Speed
If vehicle settings are stored locally in each vehicle, then the settings are immediately available for use, but the settings cannot be updated or transferred when operators use different vehicles
Solution Approach 1:
The patent implements preliminary action by pre-storing operator profiles and preferences in a centralized server before the operator actually uses a vehicle. When an operator approaches or enters a vehicle, the system proactively retrieves and applies the appropriate settings from the server, ensuring immediate availability without requiring real-time transfer during vehicle operation. This preliminary preparation enables both speed and transferability.
Solution Approach 2:
The patent incorporates feedback mechanisms where vehicle computers continuously communicate with the server to update operator profiles based on actual usage patterns and preferences observed in different vehicles. This feedback loop ensures that settings are not only transferred but also refined and updated over time, improving both availability and adaptability across the vehicle fleet.
Data Source
AI summary
An computing device is configured to detect that a user device is approaching the vehicle. An identifier for the user device and an identifier for the vehicle is transmitted to a remote server. A model is used to generate settings data in the vehicle, wherein the model is generated at least in part based on the identifier for the user device and the identifier for the vehicle. At least one setting for the at least one component in the vehicle is generated according to the model, and is applied to the at least one component in the vehicle.