Adaptive Vehicle Operating Device Menu Structure
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing motor vehicle operating devices do not dynamically adapt to changing user behavior and driving situations, requiring users to manually adjust settings and navigate through complex menus, which can be time-consuming and inefficient.
Innovation Solution
The operating device uses machine learning methods, such as artificial neural networks, to analyze user behavior and adapt the menu structure and function parameters based on observed data, reducing displayed control elements and presetting settings to match predicted user behavior in different driving situations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the menu structure provides comprehensive control elements for all motor vehicle functions, then the device offers high versatility and complete functionality, but the menu complexity increases and navigation time is extended
Solution Approach 1:
The menu structure is segmented into dynamically adjustable subsets based on driving situations. Instead of displaying all control elements simultaneously, the system divides them into context-relevant groups, showing only the most frequently needed controls for the current driving situation while keeping less relevant controls hidden or accessible through additional navigation steps.
Solution Approach 2:
The menu structure transitions from a static hierarchy to a dynamic configuration that automatically adapts to changing driving situations. The system continuously monitors driving context (time of day, weather, traffic conditions) and reconfigures the menu layout and control element visibility accordingly, allowing the most relevant functions to be prominently displayed while reducing clutter for less relevant functions.
2Adaptability or versatility
If the operating device displays all available control elements and menu levels, then complete functionality is accessible, but the navigation time to reach operating goals increases
Solution Approach 1:
The system performs preliminary actions by pre-configuring the menu structure based on predicted user needs for upcoming driving situations. By analyzing historical usage patterns and current context, the system anticipates which control elements will be needed next and positions them for quick access before the user actually needs them, reducing navigation time while maintaining complete functionality.
Solution Approach 2:
Different regions or levels of the menu structure are assigned different qualities of visibility and accessibility based on their relevance to the current driving situation. Frequently used control elements are placed in prominently visible positions with direct access, while less frequently used elements are positioned in less prominent areas or require additional navigation steps, optimizing the balance between completeness and speed of access.
3Device complexity
If the menu structure remains static or requires manual adjustment, then the device configuration is simple and reliable, but it cannot adapt to changing user behavior and driving situations
Solution Approach 1:
The operating device performs self-service by automatically monitoring its own usage patterns and driving context to dynamically reconfigure the menu structure without requiring manual user intervention. The system learns from observed user behavior and automatically adjusts control element visibility, positioning, and menu hierarchy to match changing needs, maintaining configuration simplicity while enabling continuous adaptation.
Solution Approach 2:
The system implements continuous feedback loops where usage data and driving context information are constantly monitored and fed back into the menu configuration system. This feedback mechanism allows the operating device to detect changes in user behavior patterns and driving situations, then automatically adjust the menu structure in response, bridging the gap between simple static configuration and complex adaptive behavior.
Data Source
AI summary
A method for adapting an operating device in a motor vehicle. The operating device is provided for operating at least one vehicle function of the motor vehicle. In at least one driving situation, observation data which describe the current driving situation and usage data which describe which of the vehicle functions is currently activated via the operating device are in each case detected by the operating device, and an assignment rule is generated on the basis of the observation data and the usage data by a procedure of automatic learning.