AI Vehicle Assistant Personalization via Segmented Data Modules
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Solution Overview
Problem
There is a lack of AI-based vehicle assistants that can respond to user queries based on collected user data and sensor data from vehicles, failing to provide personalized responses or recommendations to drivers.
Innovation Solution
A method and system that utilize a vehicle computing device to receive commands, retrieve associated data, identify responses, and communicate these responses back to the vehicle for display or audio output, leveraging contextual information and user preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If AI-based vehicle assistant collects and processes user data and sensor data to provide personalized responses, then the personalization and relevance of responses improve, but the system complexity and data processing requirements increase
Solution Approach 1:
The system is divided into multiple independent modules: data collection module, data processing module, response generation module, and user interface module. Each module performs a specific function, allowing the complex AI system to be managed through segmented components that can be developed, tested, and maintained independently while working together to provide personalized vehicle assistant responses.
2Measurement precision
If the vehicle assistant processes multiple types of data (user data, sensor data, contextual information), then the quality and accuracy of responses improve, but the data processing time and computational resources increase
Solution Approach 1:
User data and preference information are collected and pre-processed in advance to build user profiles and contextual models before actual queries occur. This preliminary preparation allows the system to quickly retrieve and apply relevant information when processing real-time sensor data and generating responses, reducing latency while maintaining high accuracy.
3Loss of information
If the system integrates multiple data sources and sensors at the vehicle, then the comprehensiveness of information available for responses improves, but the ease of operation and system integration difficulty worsen
Solution Approach 1:
The system employs a universal data interface and standardized communication protocols that allow multiple different sensor types and data sources to be integrated through a common framework. This multi-functional approach enables the system to handle diverse data formats and sources uniformly, reducing integration complexity while maintaining comprehensive information gathering across all vehicle systems.
Data Source
AI summary
An intelligent vehicle assistant consistent with the present disclosure may collect user preferences, user data, and data associated with a vehicle when providing information or instructions to a person in the vehicle by sending messages to a vehicle computer. The vehicle assistant may acquire preferences or data from the vehicle via a wired diagnostic port or via a wireless communication interface. Queries from a person may be received by the vehicle computer and may be sent to the intelligent vehicle assistant that interprets those commands and that evaluates contextual information to identify and send responses to the queries that may be provided to the person via an audio interface or via a display. These query responses may be based on a current context of the vehicle and past behaviors of the person.