In-Vehicle Emotion Control Using Pre-Boarding State Estimation
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Solution Overview
Problem
Existing emotion-based vehicle control systems fail to consider the occupant's emotional state before driving, leading to uncomfortable interactions with in-vehicle systems, especially when the driver is already irritated, as they remain in default settings and may exacerbate the negative emotion.
Innovation Solution
A vehicle system comprising an estimator and control processor that assesses the occupant's emotion since before boarding using various data sources like imaging, audio, portable devices, and external information, allowing for comprehensive evaluation and adaptive control of in-vehicle devices to alleviate negative emotions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the vehicle control system uses default settings for in-vehicle devices, then the system operation is simple and reliable, but the occupant's negative emotions are exacerbated and comfort is reduced
Solution Approach 1:
The system performs preliminary emotion estimation before the occupant boards the vehicle using data from portable devices and external information sources. This advance emotion assessment allows the control system to proactively adjust in-vehicle device settings before the occupant experiences potential negative emotions, thereby preventing emotional deterioration rather than reacting to it afterward
Solution Approach 2:
The system continuously monitors multiple data sources including imaging devices, audio inputs, portable device data, and external information to create a feedback loop for real-time emotion estimation. This comprehensive feedback mechanism enables the control system to dynamically adjust device operation modes based on the occupant's emotional state, transforming the default static operation into an adaptive responsive system
2Measurement precision
If the system comprehensively estimates emotion since before boarding using multiple data sources, then the emotion determination accuracy is improved, but the device complexity and data processing requirements increase
Solution Approach 1:
The emotion estimation system is segmented into distinct functional modules: an acquisition unit that collects data from multiple sources (imaging devices, audio inputs, portable devices, external information), an estimation unit that processes the collected data, and a control unit that adjusts device settings. This segmentation allows each module to handle specific tasks independently, managing complexity through modular design while achieving comprehensive emotion assessment
Solution Approach 2:
The control system is designed with multi-functionality to handle diverse data types from various sources including imaging data, audio signals, portable device information, and external data. The unified control processor integrates these different data streams and performs comprehensive emotion estimation and device control functions, reducing the need for separate specialized systems and managing overall system complexity
Data Source
AI summary
A vehicle includes an estimator and a control processor. The estimator is configured to perform estimation of an emotion that an occupant has had since before boarding the vehicle. The control processor is configured to make a comprehensive evaluation of a result of the estimation performed by the estimator to determine the emotion, and perform control of an operation mode of an in-vehicle device based on the emotion.