Headlight Control Data Generation Device Autonomous Threshold Learning
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Solution Overview
Problem
Existing headlight control systems require user intervention to learn switching thresholds, limiting automatic mode functionality and preventing learning during inappropriate conditions like vehicle stoppages or tunnel passages.
Innovation Solution
A headlight control data generation device that autonomously learns switching probabilities based on illuminance data, independent of user operations, using an electronic control unit to set ON and OFF switching threshold values and adjust parameters to suppress inappropriate learning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a learning switch different from the normal switch is used to learn the threshold value, then the threshold value can be learned, but learning cannot be performed unless a state appropriate for the operation of the learning switch occurs
Solution Approach 1:
The system automatically learns switching threshold values by analyzing illuminance data and headlight state data during normal vehicle operation, eliminating the need for users to perform special learning operations. The electronic control unit autonomously processes data to determine threshold values, making the learning process self-service rather than user-dependent.
Solution Approach 2:
The patent replaces the mechanical approach of using a physical learning switch with an electronic data analysis system. Instead of requiring user interaction with a switch, the system electronically collects and analyzes illuminance and headlight state data to automatically determine threshold values, substituting mechanical operation with electronic processing.
2Productivity
If the electronic control unit learns switching threshold values during all vehicle operations, then learning can occur continuously, but inappropriate learning occurs during vehicle stoppages or tunnel passages
Solution Approach 1:
The electronic control unit pre-establishes criteria for appropriate learning conditions by storing vehicle state data (such as vehicle speed) before performing learning operations. This preliminary preparation allows the system to filter out inappropriate learning scenarios and ensures that learning only occurs under suitable conditions, preventing inaccurate threshold value acquisition.
Solution Approach 2:
The system incorporates feedback mechanisms by monitoring vehicle state data and using this information to determine whether current conditions are appropriate for learning. The electronic control unit continuously receives feedback about vehicle operation status and adjusts its learning behavior accordingly, stopping learning when inappropriate conditions are detected and resuming when suitable conditions return.
Data Source
AI summary
A headlight control data generation device that generates headlight control data of a vehicle including a headlight includes an electronic control unit. The electronic control unit sequentially acquires, when a manual mode is selected, set data including a detection value of an illuminance around the vehicle, and ON and OFF data indicating that the headlight is in an ON state or in an OFF state at the time of sampling of the detection value, and generates the headlight control data based on the acquired set data. The headlight control data includes data regarding information on a probability of the headlight being in an ON state.