In-Vehicle POI Selection Using User Action History and Sound Signals
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing in-vehicle systems fail to select a Point of Interest (POI) based on current user information, relying solely on past actions without considering real-time user inputs and states.
Innovation Solution
A control apparatus and system that estimate an expected passage route and user state using current position and action history, and extract keywords from user utterances to select suitable POIs, integrating these factors for POI selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If POI selection is based solely on past user actions, then the system can maintain simple processing, but the POI selection lacks personalization and relevance to current user needs
Solution Approach 1:
The system performs preliminary actions by pre-processing user action history to extract behavioral patterns and pre-processing sound signals to identify user needs. The user action history storage unit stores processed historical data, and the sound signal processing unit prepares user utterances for analysis, enabling faster and more personalized POI selection without overwhelming processing complexity during runtime
Solution Approach 2:
The system segments the POI selection process into distinct functional modules: user action estimation unit that analyzes historical behavior, sound signal processing unit that captures current user needs, and POI selection unit that integrates both inputs. This segmentation allows each module to handle specific tasks independently, maintaining manageable complexity while achieving comprehensive personalization
2Measurement precision
If the system integrates both past user behavior and current user inputs for POI selection, then POI selection accuracy improves, but the processing complexity increases
Solution Approach 1:
The system introduces intermediary processing units that bridge past user behavior and current user inputs. The user action estimation unit acts as an intermediary that translates historical data into actionable insights, while the sound signal processing unit intermediates between raw user utterances and POI selection criteria. These intermediaries integrate multiple data sources accurately while managing processing complexity through specialized processing pipelines
3Loss of information
If the system processes sound signals in real-time to extract user needs, then current user information is captured, but processing time increases
Solution Approach 1:
The sound signal processing unit performs preliminary processing on user utterances by continuously monitoring and pre-analyzing sound signals even before POI selection is triggered. This preliminary action prepares user need information in advance, enabling rapid extraction of current user information when needed without causing significant processing delays during the actual POI selection moment
Data Source
AI summary
A control apparatus includes: a user action estimation unit that estimates an expected passage route of a user based on a current position and an action history of the user; a sound signal input unit to which a sound signal based on the utterance of the user is input; a storage unit that stores a keyword and a POI related to the keyword; a keyword extraction unit that extracts the keyword from the sound signal; and a POI selection unit that selects a candidate POI as a candidate for a destination based on the expected passage route estimated by the user action estimation unit and the keyword extracted by the keyword extraction unit.