Adaptive Man-Machine Interface for Automated Driving
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Solution Overview
Problem
The challenge lies in adapting a human-machine interface in motor vehicles to enhance acceptance and safety of automated driving modes, particularly in ensuring clear communication of responsibility shifts between the driver and automation systems, while maintaining user confidence across varying levels of automation.
Innovation Solution
A method that adjusts the human-machine interface based on the driver's confidence level, using display units, voice input/output, and seat/console adjustments to provide appropriate information and interaction prompts, minimizing disturbance for high-trust drivers and aiding low-trust drivers with detailed information and instructions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the human-machine interface provides detailed information and interaction prompts to low-trust drivers, then user confidence and acceptance are enhanced, but device complexity and information overload increase
Solution Approach 1:
The patent applies dynamics by making the human-machine interface adaptive and configurable based on individual driver trust levels. The system dynamically adjusts information density, interaction prompts, and communication styles according to the driver's confidence level in automated driving functions, thereby resolving the contradiction between providing sufficient information and avoiding overload.
Solution Approach 2:
The patent implements local quality by tailoring specific interface elements (information display, prompt frequency, communication tone) to match the individual driver's trust level. Different drivers receive customized interface configurations - high-trust drivers get minimal information while low-trust drivers receive detailed guidance, thus optimizing reliability without uniformly increasing complexity for all users.
2Adaptability or versatility
If the system adapts the interface to individual trust levels, then user acceptance increases, but measurement precision of driver confidence is required
Solution Approach 1:
The patent applies self-service by enabling drivers to manually configure their preferred trust level and interface preferences. Drivers can self-assess their confidence in automated driving and select appropriate interface configurations without requiring complex external measurement systems, thus achieving adaptability while avoiding the measurement precision challenge.
Solution Approach 2:
The system implements feedback mechanisms that monitor driver behavior, attention, and interaction patterns to infer trust levels. By continuously observing how drivers engage with the interface and respond to automated driving functions, the system adapts the interface configuration based on inferred confidence levels, balancing adaptability with practical measurement capabilities.
3Ease of operation
If automated driving functions are implemented with high automation levels, then driver workload is reduced, but responsibility shift communication becomes more challenging
Solution Approach 1:
The patent applies parameter changes by adjusting the information communication parameters (detail level, frequency, type of prompts) based on the automation level and driver trust configuration. In high-automation modes with low-trust drivers, the system increases communication about responsibility transitions, while in low-automation modes or with high-trust drivers, communication is minimized, thus reducing workload without losing critical responsibility information.
Data Source
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AI summary
The invention relates to a method for adapting a man-machine interface (20) in a motor vehicle (100), wherein the motor vehicle (100) can be operated in at least one automated driving mode, wherein a degree of confidence (V) of the driver is detected or determined, and wherein the man-machine interface (20) is adapted as a function of the detected or determined degree of confidence (V). The invention also relates to a motor vehicle (100).