Driver Emotion Recognition Using Environment Context
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Solution Overview
Problem
Current driver emotion classification systems lack the ability to accurately recognize detailed emotions in real-time, using primarily classified emotions and driving environment information, which limits their effectiveness in providing personalized and safe driving experiences.
Innovation Solution
A method and system that determine driver emotions by simultaneously receiving real-time basic emotion and driving environment information, using a preset matching table to classify emotions, and activating a basic emotion recognition system for specific events, allowing for detailed emotion classification and personalized vehicle services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a conventional driver emotion classification system is used, then the system can provide basic emotion recognition services, but the emotion recognition detail and accuracy are insufficient
Solution Approach 1:
The system segments emotion recognition into multiple levels: basic emotion classification (joy, anger, sadness, fear, disgust, surprise) and detailed emotion classification (subdividing basic emotions into multiple detailed emotions). This segmentation allows the system to achieve high recognition accuracy by progressively refining emotion categories without overwhelming complexity at each stage.
Solution Approach 2:
The system adds a new dimension to emotion recognition by integrating driving environment information (vehicle speed, acceleration, GPS, passenger info, voice utterance, device manipulation) with basic emotion data. This multi-dimensional approach enables detailed emotion classification that considers both physiological emotional states and contextual driving conditions, significantly improving recognition accuracy.
2Productivity
If real-time emotion recognition is implemented, then the system can provide immediate personalized services, but the processing time and computational load increase
Solution Approach 1:
The system performs preliminary classification of basic emotions first, then selectively conducts detailed emotion classification only when needed. The preset matching table pre-organizes relationships between basic emotions, driving environment information, and detailed emotions, enabling rapid lookup and classification without extensive real-time computation, thus reducing processing time while maintaining service responsiveness.
Solution Approach 2:
The system implements periodic emotion recognition at different granularity levels. Basic emotion recognition operates continuously at a lower computational level, while detailed emotion classification is performed periodically or trigger-based when driving environment changes occur or when basic emotion detection reaches certain thresholds, optimizing the balance between real-time service capability and processing efficiency.
Data Source
AI summary
A method of determining driver emotions in conjunction with a driving environment includes determining a basic emotion of a driver, acquiring driving environment information, determining the driver emotion based on the driving environment information and the basic emotion, and providing a service of displaying the driver emotion or a driver-emotion-based service.