Vehicle Headlight Control Using Driver Motion Data
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Solution Overview
Problem
Existing vehicle headlight control systems face challenges in accurately determining driver attributes, which affects the adjustment of light distribution for optimal visibility and safety.
Innovation Solution
A control device for vehicle headlights that includes a motion information acquisition part, an attribute decision part, and a light distribution controller, utilizing information from motion, external environment, and past driver data to accurately determine driver attributes and adjust light distribution accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If driver attributes are determined based on driving operation information and captured images, then light distribution can be varied according to driver attributes, but accurate determination of driver attributes becomes difficult when motion is not sufficiently taken into account
Solution Approach 1:
The system transitions from static driver attribute determination (based only on captured images and driving operation information) to dynamic determination by incorporating motion information. The motion information acquisition unit captures real-time motion data of the driver, and the attribute determination unit integrates this dynamic information with static data to accurately determine driver attributes such as attention level and driving state, resolving the contradiction between measurement precision and comprehensive behavior analysis.
Solution Approach 2:
The attribute determination unit is designed to process multiple types of information universally - combining driving operation information, captured images, and motion information into a unified driver attribute determination system. This multi-functional approach enables accurate determination of various driver attributes (attention, fatigue, emotion) using a single integrated system, rather than separate systems for each attribute type.
2Measurement precision
If multiple information sources are integrated for driver attribute determination, then accuracy improves, but system complexity increases
Solution Approach 1:
The system merges multiple information sources (driving operation information, captured images, and motion information) into a single attribute determination unit. This consolidation integrates previously separate functions into one unified component, reducing overall system complexity while maintaining accurate driver attribute determination through comprehensive data fusion.
Solution Approach 2:
The attribute determination unit serves as a universal processor that handles multiple information types and determines various driver attributes through a single multi-functional component. This approach avoids the need for separate determination systems for each attribute type, thereby reducing system complexity while preserving measurement precision.
Data Source
AI summary
A control device for a vehicle headlight includes a motion information acquisition part that acquires information of a motion of at least a part of a driver in the vehicle, an attribute decision part that determines attribute of the driver based on the information acquired by the motion information acquisition part, and a light distribution controller that controls a light distribution of the vehicle headlight based on the attribute determined by the attribute decision part.