Autonomous Vehicle Headlight Brightness Control for Object Recognition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous driving systems face challenges in accurately recognizing objects in varying environments due to low recognition accuracy when current and learned environment information differ, requiring extensive learning data and time, and existing headlight illumination methods are insufficient to improve recognition accuracy.
Innovation Solution
A method and apparatus for controlling vehicle headlights to adjust brightness based on external illumination and recognition errors, using a processor to output light corresponding to a first brightness value and then a second value, and communicating with a server for assistance when recognition errors exceed a predetermined range, to enhance object recognition accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the vehicle uses fixed brightness headlight illumination, then the device complexity is low, but the object recognition accuracy deteriorates in varying environments
Solution Approach 1:
The headlight brightness is made dynamic rather than fixed. The processor adjusts the headlight brightness value based on recognition errors and external illumination conditions, allowing the system to adapt to varying environments. This dynamic adjustment resolves the contradiction by enabling accurate object recognition across different lighting conditions without requiring overly complex pre-configured systems.
Solution Approach 2:
The system implements a feedback mechanism where recognition errors are continuously monitored and fed back to adjust headlight brightness. When recognition errors exceed a threshold, the system adjusts the brightness and re-evaluates, creating a closed-loop control system that improves recognition accuracy while maintaining manageable complexity through iterative optimization.
2Measurement precision
If the vehicle collects extensive learning data to improve recognition accuracy, then the object recognition accuracy improves, but the loss of time increases due to extended learning requirements
Solution Approach 1:
The system performs preliminary actions by adjusting headlight brightness based on current recognition errors before extensive re-learning is required. By proactively modifying illumination conditions, the system can improve recognition accuracy in real-time without waiting for lengthy learning processes to complete, thus reducing time loss while maintaining accuracy improvements.
Solution Approach 2:
Instead of collecting extensive new learning data, the system changes operational parameters (headlight brightness) to improve recognition accuracy. This parameter adjustment allows the existing learning model to perform better in current conditions, achieving accuracy improvement without the time cost of extensive data collection and model retraining.
3Measurement precision
If the vehicle increases headlight brightness to improve object recognition, then the object recognition accuracy improves, but the use of energy increases
Solution Approach 1:
The system optimizes the headlight brightness parameter rather than simply increasing it. By adjusting brightness based on recognition errors and external illumination conditions, the system uses the minimum necessary energy to achieve improved recognition accuracy, avoiding wasteful energy consumption while maintaining effectiveness.
Solution Approach 2:
The feedback mechanism ensures that headlight brightness is increased only when recognition errors indicate a problem and only to the extent necessary to resolve the issue. This controlled adjustment based on actual performance needs prevents unnecessary energy consumption while still achieving the goal of improved object recognition accuracy.
Data Source
AI summary
A method and apparatus for controlling a vehicle in an autonomous driving system. The method for controlling a vehicle in an autonomous driving system can improve recognition accuracy of an object by outputting light corresponding to a first brightness value changed in correspondence to detection of an object having a recognition error larger than a predetermined range during driving while outputting light corresponding to a first brightness value that is determined of the basis of information about external illumination. An autonomous vehicle of the present disclosure may be associated with an artificial intelligence module, a drone ((Unmanned Aerial Vehicle, UAV), a robot, an AR (Augmented Reality) device, a VR (Virtual Reality) device, a device associated with 5G services, etc.