Adaptive Vehicle Control Menu System for Driver Workload Reduction
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Solution Overview
Problem
Drivers face difficulty in navigating and utilizing the various settings of vehicle control systems due to the complexity and layout of the operating menus, leading to potential distraction while driving.
Innovation Solution
A method and device that compile statistics on user interactions with the vehicle's control systems, adapting the menu layout to prioritize frequently used settings and move less frequently used options to less accessible locations, with the ability to automatically apply these settings in relevant driving situations through software updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the vehicle control system provides comprehensive settings and functions, then the system's functionality and versatility are improved, but the menu complexity and difficulty of operation increase
Solution Approach 1:
The patent segments the comprehensive vehicle control system settings into multiple hierarchical menu levels. Frequently accessed functions are placed in the main menu, while less frequently used functions are nested in sub-menus. This segmentation allows the system to maintain comprehensive functionality while reducing the operational complexity by organizing settings in a structured, multi-level hierarchy that guides users to commonly used functions first.
Solution Approach 2:
The patent implements dynamic menu adaptation based on user behavior patterns. The system monitors which settings and functions the driver accesses most frequently and automatically reorganizes the menu structure to prioritize these frequently used items in more accessible positions. This dynamic reconfiguration allows the menu to adapt to individual driver preferences and driving patterns, improving ease of operation while preserving all system functions.
2Adaptability or versatility
If the menu layout is designed to accommodate all vehicle functions, then complete control access is achieved, but the time required to locate and access desired settings increases
Solution Approach 1:
The patent applies preliminary action by pre-organizing the menu structure based on statistical analysis of driver behavior patterns. Before the driver needs to access a setting, the system has already positioned frequently accessed functions in optimal locations within the menu hierarchy. This preliminary organization, based on aggregated data from multiple users, reduces the time required to locate settings by anticipating common access patterns and pre-configuring the menu accordingly.
Solution Approach 2:
The patent replaces the static, mechanically fixed menu structure with a dynamic, software-based adaptive system. Instead of requiring physical reconfiguration or manual navigation through fixed hierarchical levels, the menu structure can be dynamically reorganized through software based on real-time or historical usage data. This substitution of mechanical menu design with adaptive software control significantly reduces the time to locate settings while maintaining complete access to all vehicle functions.
3Adaptability or versatility
If the driver manually adjusts multiple vehicle settings, then personalized preferences are achieved, but the driver workload and potential for distraction increase
Solution Approach 1:
The patent implements self-service by enabling the vehicle's control system to automatically adjust settings based on monitored driver preferences and behavior patterns. The system observes which settings the driver manually changes and under what conditions, then automatically applies these preferred settings without requiring further manual intervention. This self-service capability achieves personalized configuration while reducing driver workload, as the system autonomously manages the personalization process based on its observations of driver behavior.
Solution Approach 2:
The patent employs feedback mechanisms where the system continuously monitors driver interactions with the vehicle's control systems. By analyzing this feedback data regarding which settings are adjusted and under what driving conditions, the system learns driver preferences and automatically configures optimal settings. This feedback-driven approach achieves personalized vehicle operation while minimizing driver workload, as the system uses observed feedback to autonomously optimize settings rather than requiring continuous manual adjustment.
Data Source
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AI summary
The proposal concerns a method for adapting the operation of a vehicle control system (182, 184), wherein the operation is effected by one or more operating menus of a user interface, which are displayed on a display unit (20). The proposal further concerns the compilation of statistics (61) on which menu settings the user has made for the vehicle control system (182, 184) at least within a certain period of time. The statistics (61) are stored in a memory unit (60) of the vehicle (10). The statistics (61) are transferred to an administrative unit (18). The statistics (61) are evaluated in the administrative unit (18), and based on this, a software update for a program of the vehicle control system (182, 184) is created, individually adapted to the needs of the driver, and transferred to and installed in the vehicle (10).