Adaptive ADAS Control for Driver Type and Condition
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Solution Overview
Problem
Conventional Advanced Driver Assistance Systems (ADAS) do not consider driver type, driver state, or traveling environment, leading to inappropriate or unnecessary application of assistance functions.
Innovation Solution
A vehicle driving assistance method that selects the driver type and senses the driver's condition to control ADAS functions in stages or selectively, adapting to the driver type, driver state, and surrounding environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If ADAS functions are applied universally without considering driver type or environment, then system complexity is reduced and ease of operation is improved, but adaptability and driving safety deteriorate
Solution Approach 1:
The system dynamically adjusts ADAS function application based on real-time detection of driver type, driver state, and traveling environment. The controller selectively activates or deactivates specific ADAS functions according to the detected conditions, making the system adaptable without requiring manual configuration by the user.
Solution Approach 2:
The system automatically detects driver characteristics and environmental conditions, then self-configures the appropriate ADAS functions without user intervention. This self-service approach maintains ease of operation while achieving high adaptability through automated parameter adjustment.
2Adaptability or versatility
If ADAS functions are selectively controlled based on driver type and condition, then adaptability and driving safety are improved, but device complexity increases
Solution Approach 1:
The system segments the driver population into different types (e.g., elderly, disabled, pregnant women, normal drivers) and applies specific ADAS function sets to each segment. This segmentation allows tailored assistance while managing complexity through categorized control rules.
Solution Approach 2:
Different ADAS functions are selectively applied to different driver segments based on their specific needs. For example, elderly drivers receive enhanced assistance functions while normal drivers receive standard functions, optimizing adaptability without uniformly increasing complexity across all users.
3Adaptability or versatility
If ADAS functions are tailored to specific driver types and conditions, then adaptability and driving safety are improved, but loss of information increases due to multiple sensing requirements
Solution Approach 1:
The sensing system uses multi-functional sensors that can detect multiple types of information simultaneously. For example, the sensing unit detects both driver type characteristics and driver state conditions using integrated sensing capabilities, reducing information loss through comprehensive multi-purpose detection.
Solution Approach 2:
The system merges the detection of driver type, driver state, and environmental conditions into a unified control process. The controller integrates multiple information streams to make comprehensive ADAS function decisions, minimizing information loss through consolidated processing.
Data Source
AI summary
The present invention relates to a vehicle driving assistance method comprising the steps of: selecting a driver type; detecting the driver's condition; and controlling, in phases, at least one vehicle driving assistance function or selectively controlling a plurality of vehicle driving assistance functions, according to the selected driver type and the detected driver's condition.