Vehicle Behavior Recognizer for Proactive Assistance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Infotainment systems in vehicles lack access to all operational systems, limiting their ability to provide personalized and proactive assistance to users beyond specific functions, as they rely on data from only particular systems and cannot integrate with other vehicle functions.
Innovation Solution
A computing structure with a software architecture that includes a behavior recognizer, which receives user event data, determines when proactive assistance is needed, and uses user behavior and machine state models to provide personalized help through suitable modalities, such as recommendations or instructions, by accessing and analyzing data from various vehicle systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If infotainment systems rely on data from only particular systems, then the system complexity is reduced, but the personalization and assistance capability is limited
Solution Approach 1:
The patent introduces a behavior recognizer as an intermediary component that sits between multiple vehicle systems and the infotainment system. This mediator collects data from various sources (climate control, audio system, navigation, etc.), processes it through user behavior and machine state models, and generates personalized assistance without requiring direct complex integration between all vehicle systems. The behavior recognizer acts as a buffer that simplifies the overall system architecture while enabling comprehensive personalization.
2Ease of operation
If the system provides proactive assistance based on user behavior patterns, then the user experience is improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by continuously monitoring and storing user behavior patterns and machine states in advance. The behavior recognizer maintains user behavior models and machine state models that are pre-populated with historical data. When a user interaction occurs, the system can quickly query these pre-built models rather than analyzing raw data from scratch, significantly reducing real-time processing time while still providing personalized proactive assistance.
Solution Approach 2:
The system applies partial action by selectively generating assistance only for specific user behaviors that match predefined patterns in the behavior models. Rather than continuously analyzing all possible user actions, the system focuses computational resources on识别ing and responding to meaningful behavior patterns, thereby reducing overall processing requirements while maintaining high user experience quality for relevant interactions.
3Loss of information
If the system integrates data from all vehicle systems, then the assistance relevance is improved, but the data security and privacy risks increase
Solution Approach 1:
The behavior recognizer extracts only the specific data elements needed for behavior analysis from each vehicle system, rather than collecting and storing all available data. The system extracts relevant behavioral patterns and machine states while leaving the detailed raw data in their source systems. This extraction approach maintains information completeness for personalization purposes while minimizing the storage and transmission of sensitive personal information, thereby reducing privacy risks.
Data Source
AI summary
The present disclosure relates to systems for implementing a computer-readable storage device comprising instructions, including a behavior recognizer, that, when executed by a system having a processor, cause the processor to perform operations, for providing personalized proactive assistance to a vehicle user. The operations comprise receiving a behavior input data package comprising a sequence of user events using the behavior recognizer, and determining the behavior input data package indicates proactive assistance to be presented to the vehicle user by the system, using a user behavior model and a machine state model of the behavior recognizer. The disclosure also relates to methods for providing personalized proactive assistance to a vehicle user.