Vehicle Control Personalization Using Operator Preference Grouping
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Solution Overview
Problem
Existing vehicle systems lack the ability to customize the actuation of components based on the preferences and personality of individual operators, leading to suboptimal user experiences.
Innovation Solution
A vehicle computer system that assesses operator input through questionnaires, identifies preference groupings based on personality types, and adjusts vehicle settings accordingly, including display density, audible statements, climate control, and interior lighting, using machine-learning algorithms to cluster personality types and map them to specific vehicle settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If vehicle systems use standardized controls for all operators, then device complexity is reduced and ease of manufacture is improved, but adaptability to individual operator preferences deteriorates
Solution Approach 1:
The system performs preliminary assessment of operator preferences through questionnaires before actual vehicle operation. This allows the system to pre-configure personalized settings for display density, audible statements, climate control, and interior lighting based on assessed personality types, thereby achieving adaptability without adding complexity during actual operation
Solution Approach 2:
The system changes multiple vehicle parameters simultaneously based on assessed personality types, including display content density, frequency of audible statements, climate-control settings, and interior lighting. This coordinated parameter adjustment achieves comprehensive adaptability while managing system complexity through integrated control
2Adaptability or versatility
If vehicle systems collect detailed operator input through questionnaires, then adaptability to individual preferences is improved, but loss of time during initial setup increases
Solution Approach 1:
The preference assessment questionnaire is administered during initial vehicle setup or first login, performing the personalization configuration in advance before regular operation begins. This preliminary action ensures accurate personalization while confining time investment to the initial setup phase rather than ongoing operation
Solution Approach 2:
The system enables operators to self-assess their own preferences through the questionnaire interface, eliminating the need for manual configuration by technicians. This self-service approach reduces both setup time and complexity while maintaining high personalization accuracy
3Ease of operation
If vehicle components are customized for individual operators, then user experience and comfort are improved, but ease of operation deteriorates due to additional configuration steps
Solution Approach 1:
All configuration steps are performed in advance through the preference assessment questionnaire, so that during actual vehicle operation, the system automatically applies personalized settings without requiring additional operator intervention. This preliminary configuration eliminates ongoing complexity while delivering enhanced user experience
Solution Approach 2:
The system automatically processes questionnaire responses and configures appropriate settings without requiring operator expertise or manual adjustment. This self-service configuration simplifies the process for operators while achieving comprehensive personalization of vehicle components
Data Source
AI summary
A computer includes a processor and a memory, and the memory stores instructions executable by the processor to receive operator input from an operator in response to an operator assessment questionnaire, identify a preference grouping for the operator based on the operator input, and actuate at least one vehicle component based on the preference grouping.