Vehicle User Profile Translation Across Different Car Platforms
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Solution Overview
Problem
Existing vehicle customization systems struggle to seamlessly transfer and apply user preferences across different vehicle brands and models, making it complex to achieve a personalized driving experience.
Innovation Solution
A networked system that includes mobile devices and vehicles, utilizing machine learning to estimate vehicle function configurations based on user profiles and control vehicle settings accordingly, enabling dynamic customization across different vehicle platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vehicle customization systems use traditional data transfer methods (e.g., NFC) to transfer user profiles, then the transfer process is simple and direct, but the system cannot accurately translate and adapt user preferences across different vehicle brands and models
Solution Approach 1:
The patent introduces a cloud-based server as an intermediary between the mobile device and the vehicle. The server receives user profile data, translates it into vehicle-specific configuration parameters, and sends the adapted settings to the target vehicle. This intermediary enables accurate cross-brand preference translation without requiring direct complex integration between diverse vehicle systems.
Solution Approach 2:
The customization system is segmented into separate functional modules: a mobile device for data collection, a cloud server for translation and processing, and the vehicle for execution. This segmentation allows each component to specialize in specific tasks, improving overall accuracy while managing complexity through modular architecture.
2Adaptability or versatility
If the system transfers complete user profiles directly to the vehicle, then the personalization is comprehensive, but the transfer time and data processing load increase
Solution Approach 1:
The system extracts only the essential user preference parameters from the complete profile and transfers these condensed settings to the vehicle. The cloud server performs the extraction and translation of critical parameters (seat positions, mirror angles, climate preferences) while filtering out redundant information, thereby reducing transfer time while maintaining personalization completeness.
Solution Approach 2:
The cloud server performs preliminary processing and translation of user profiles before they reach the vehicle. By pre-translating and optimizing the data format in advance, the system reduces the processing burden on the vehicle and accelerates the final configuration application, thus reducing overall transfer and setup time.
3Speed
If the vehicle system processes and applies all user profile settings locally, then the personalization response is fast, but the system requires complex translation capabilities for different vehicle platforms
Solution Approach 1:
The cloud server acts as a centralized translation intermediary that handles the complex task of converting user profiles into vehicle-specific parameters. This removes the translation complexity from the vehicle's local system, allowing the vehicle to simply receive and apply pre-processed settings, thus maintaining fast response speed while reducing onboard computational requirements.
4Adaptability or versatility
If the system stores complete vehicle configuration data in the mobile device, then the user profile is comprehensive, but the storage requirements and security risks increase
Solution Approach 1:
The system extracts and stores only essential user preference parameters in the mobile device rather than complete vehicle configuration data. Non-critical or vehicle-specific data is either omitted from mobile storage or encrypted, reducing the attack surface while maintaining the core personalization functionality.
Solution Approach 2:
The cloud server serves as a secure intermediary that handles sensitive data processing and storage. By moving comprehensive configuration data to a secured cloud environment with professional security measures, the system reduces security risks associated with storing complete profiles on mobile devices while maintaining data accessibility for personalization.
Data Source
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AI summary
A vehicle that can be customized and personalized via a mobile user profile. The vehicle can include a body, a powertrain, vehicle electronics, and a computing system. The computing system of the vehicle can be configured to: receive data fields of a driver profile of a user from a mobile device; estimate, using machine learning, configurations of vehicle functions for the vehicle according to the data fields; and control settings of a set of components of the vehicle, via the vehicle electronics, according to the estimated configurations.