Automated Headlight Cut-Off Control for Road Crest Prediction
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Solution Overview
Problem
Existing automated headlight systems fail to accurately adjust the low beam to account for significant road inclines, such as mountain peaks, due to limitations in sensor field of view, reliance on optical data, and lack of predictive adjustment capabilities.
Innovation Solution
Utilizing a digital elevation model to calculate the elevation gradient and determine turning points ahead, allowing for predictive adjustment of the low beam cut-off line based on the vehicle's tipping motion around the y-axis, independent of weather and sensor calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If sensor-supported headlight systems (camera, radar, lidar) are used to adjust the low beam to the incline of the road, then the headlight system can adapt to road topography, but the sensors cannot detect driving over a mountain peak due to their limited field of view
Solution Approach 1:
The patent applies preliminary action by using a digital elevation model to pre-calculate the elevation gradient and determine turning points ahead of the vehicle. This allows the headlight system to be adjusted in advance before the vehicle reaches the incline, overcoming the limitation of sensors that cannot detect mountain peaks due to their field of view constraints.
2Adaptability or versatility
If steering sensor-supported headlight systems are used to evaluate road incline, then the headlight can be situationally adjusted, but predictive adjustment is not enabled as steering angle sensor input is necessary
Solution Approach 1:
The system performs preliminary action by calculating the elevation gradient and determining turning points from the digital elevation model before the vehicle reaches them. This enables predictive adjustment of the headlights based on upcoming road geometry rather than waiting for steering sensor input, eliminating the time loss associated with reactive adjustment.
3Reliability
If optical sensors (camera, radar, lidar) are used for headlight adjustment, then the system can detect the environment, but the sensors cannot detect driving over a mountain peak due to FOV limitations
Solution Approach 1:
The patent introduces an intermediary approach by using a digital elevation model as a mediator between the vehicle and the road topography. Instead of relying on optical sensors to directly detect mountain peaks, the system queries the digital elevation model using GPS coordinates to obtain elevation data, which is then processed to determine the appropriate headlight adjustment.
4Loss of time
If digital elevation model data is used for predictive headlight adjustment, then timely and precise adjustment is achieved, but additional processing of elevation data is required
Solution Approach 1:
The system applies the extraction principle by isolating and processing only the critical elements from the digital elevation model data - specifically the elevation gradient and turning points. This selective extraction approach enables timely headlight adjustment while minimizing the complexity of data processing by focusing only on the essential geometric features needed for prediction.
Data Source
AI summary
A method for adjusting an automated headlight system of a motor vehicle, the headlight system having headlights for generating a low beam and a control device for adjusting a lower cut-off line of the low beam, involves calculating an elevation gradient from an extract from a digital elevation model, determining, from the elevation gradient, two turning points which are nearest ahead, determining and characterizing a mean path position on the basis of the turning points, and adjusting the lower cut-off line to a central point of the mean path position at least when the first turning point is reached.