Vehicle Function Control Using Driver Cognitive State Feedback
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Solution Overview
Problem
Current vehicle systems lack the ability to automatically adjust functions based on the cognitive state of the user, such as stress, boredom, or comfort, which can lead to a less relaxing and less safe driving experience, especially in autonomous vehicles where manual control is reduced.
Innovation Solution
A driver assistance system that determines the cognitive state of the user by receiving data from various monitoring means, including biometric, physical, and psychological attributes, and uses inference modules to aggregate this data to control vehicle functions like temperature, lighting, and audio settings, allowing the vehicle to adapt to the user's state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If vehicle systems manually control functions, then user control and customization are improved, but user burden and complexity increase
Solution Approach 1:
The system automatically monitors user cognitive state through biometric sensors and inference modules, then autonomously adjusts vehicle functions without requiring manual user input. The system serves itself by detecting user needs and implementing adjustments independently, eliminating the burden of manual control while maintaining customization.
Solution Approach 2:
The system continuously monitors user cognitive state through biometric feedback (heart rate, skin conductance, temperature) and uses this feedback to dynamically adjust vehicle functions. This closed-loop feedback mechanism enables automatic adaptation to user needs without increasing operational complexity for the user.
2Reliability
If vehicle systems automatically adjust functions based on cognitive state, then user comfort and safety are improved, but system complexity and data processing requirements increase
Solution Approach 1:
The system divides cognitive state determination into separate inference modules, each specializing in specific cognitive attributes (e.g., stress, boredom, comfort). Each module processes specific biometric data types independently, then results are aggregated to form the overall cognitive state assessment. This segmentation reduces the complexity of any single module while maintaining comprehensive analysis.
Solution Approach 2:
The system uses a unified platform that handles multiple functions: biometric data acquisition, cognitive state inference, preference learning, and vehicle function control. This multi-functional approach consolidates complexity into a single system rather than requiring separate systems for each function, improving reliability while managing complexity efficiently.
3Measurement precision
If multiple inference modules are used to determine cognitive state, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system implements multiple specialized inference modules, each focused on detecting specific cognitive states (stress, boredom, comfort) using relevant biometric parameters. This segmentation allows each module to optimize its detection algorithms for specific cognitive attributes, improving overall measurement precision while keeping individual module complexity manageable through specialization.
Data Source
AI summary
A system for controlling one or more functions of a vehicle responsive to a cognitive state of a vehicle user comprises one or more controllers configured to receive cognitive state data indicative of a cognitive state of the user of the vehicle and context data indicative of a context of one or both of the user and the vehicle. The one or more controllers are configured to control the one or more functions of the vehicle in dependence on the received indication of the cognitive state of the user and the context data. The controllers are configured to output control data for controlling the one of more functions of the vehicle.