Dynamic Headlight Leveling Using Road Geometry and Vehicle Orientation
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating due to the vast volume of data requiring analysis, storage, and updating of maps, which can limit or adversely affect navigation accuracy and safety.
Innovation Solution
A system and method for autonomous vehicle navigation using a camera to generate a road geometry model, determine vehicle orientation, and adjust movable headlights based on image analysis, enabling precise navigation and obstacle avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional mapping technology is used for autonomous vehicle navigation, then comprehensive navigation data can be obtained, but the system complexity and data processing burden increase significantly
Solution Approach 1:
The patent extracts and utilizes natural road geometry features (curves, hills, gradients) directly from the environment as navigation references, removing the need for complex pre-stored mapping data. The vehicle determines its position and orientation by analyzing these extracted geometric features in real-time, significantly reducing data processing complexity while maintaining navigation reliability.
Solution Approach 2:
The system enables the vehicle to self-determine its navigation state by autonomously analyzing road geometry features captured by onboard sensors. The vehicle serves its own navigation needs by processing real-time visual data of road curves, gradients, and elevation changes, eliminating dependence on external mapping systems and reducing overall system complexity.
2Measurement precision
If real-time image analysis is performed for navigation, then navigation accuracy is improved, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary identification of key road geometry features (curves, hills, gradients) in advance during normal operation. By pre-processing and storing essential geometric characteristics as the vehicle traverses the road, the system reduces the computational burden during critical navigation decisions, thereby reducing processing time while maintaining high measurement precision.
Solution Approach 2:
The patent applies partial action by focusing image analysis only on specific, pre-identified road geometry features rather than processing all visual data. The system selectively analyzes curves, gradients, and elevation changes that are most relevant for navigation, reducing overall processing time while maintaining sufficient orientation determination accuracy.
3Illumination intensity
If movable headlights are adjusted based on road geometry, then illumination accuracy is improved, but system complexity increases
Solution Approach 1:
The patent merges the road geometry analysis function with the headlight control function into a single integrated process. The same sensor data and geometric feature detection used for navigation are simultaneously utilized to control headlight orientation, eliminating the need for separate control systems and reducing overall system complexity while improving headlight pointing accuracy.
Solution Approach 2:
The system implements multi-functionality by using the road geometry model for multiple purposes: both navigation/orientation determination and headlight control. This universal approach allows a single processing pipeline to serve dual functions, reducing system complexity while achieving precise illumination aligned with the road geometry.
Data Source
AI summary
A system for navigating a host vehicle may include memory and at least one processor configured to receive a plurality of images acquired by a camera onboard the host vehicle; generate, based on analysis of the plurality of images, a road geometry model for a segment of road forward of the host vehicle; determine, based on analysis of at least one of the plurality of images, one or more indicators of an orientation of the host vehicle; and generate, based on the one or more indicators of orientation of the host vehicle and the road geometry model for the segment of road forward of the host vehicle, one or more output signals configured to cause a change in a pointing direction of a movable headlight onboard the host vehicle.