LiDAR Rain Detection Using Region-Based Point Density
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Solution Overview
Problem
Existing methods for detecting precipitation using vehicle-mounted sensors are complex and require extensive processing of point cloud data, making them inefficient.
Innovation Solution
A method that involves monitoring specific regions within the environmental sensor's field of view to detect precipitation by identifying points not associated with any object, allowing for efficient detection with minimal effort, using LiDAR, radar, or optical camera sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all points in the point cloud are processed to detect precipitation, then detection reliability is improved, but processing complexity and time consumption increase significantly
Solution Approach 1:
The patent divides the environmental sensor's field of view into multiple predefined regions. Instead of processing all points in the entire point cloud, the system only evaluates points within these specific regions for precipitation detection. This segmentation approach maintains detection reliability by focusing on areas where precipitation is most likely to appear, while significantly reducing processing complexity by excluding irrelevant areas from analysis.
Solution Approach 2:
The patent extracts and evaluates only the relevant portion of the point cloud data - specifically points located within the predefined regions of interest. By taking out only the necessary data subset for precipitation analysis rather than processing the complete point cloud, the system achieves efficient detection with minimal processing effort while maintaining adequate detection capability.
2Reliability
If all points in the point cloud are processed to detect precipitation, then detection completeness is improved, but processing time increases
Solution Approach 1:
The field of view is segmented into multiple regions, and precipitation detection is performed only within these predefined areas. This allows the system to achieve sufficient detection completeness by monitoring specific zones where precipitation is most relevant, while dramatically reducing processing time by avoiding evaluation of points outside these regions.
Solution Approach 2:
The patent applies partial action by evaluating only a subset of the total point cloud - specifically points within predefined regions - rather than processing all points. This partial evaluation approach provides adequate detection performance for practical applications while minimizing processing time consumption.
3Productivity
If region-based monitoring is used for precipitation detection, then processing efficiency is improved, but detection coverage may be reduced
Solution Approach 1:
The environment is divided into multiple predefined regions that collectively cover the areas most relevant for precipitation detection. This segmentation enables efficient processing by limiting analysis to these regions, while the strategic placement and configuration of regions maintain adequate detection coverage for safety-critical applications.
Solution Approach 2:
Different regions within the field of view are monitored with focused attention, applying local quality assessment to specific zones where precipitation detection is most valuable. This approach optimizes processing efficiency by concentrating computational resources on regions with highest detection priority, while maintaining sufficient overall coverage through strategic region selection.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables efficient and reliable precipitation detection by simplifying the processing of sensor data, allowing for real-time adjustments to driving parameters based on precipitation levels, thereby enhancing vehicle safety.
Implementation Method 1
laser data collected for a vehicle's environment
Implementation Method 2
in particular by means of a lidar-based environment sensor
Data Source
Figure 1~2
Figure 3~5
AI summary
The invention relates to a method for detecting precipitation by means of an environment sensor (14) for capturing the environment of a vehicle (10) point by point, comprising the steps of capturing environment points by means of the environment sensor (14) within the field of view (20) of the environment sensor, selecting at least one region (22, 24) within the field of view (20) of the environment sensor (14), determining a point density of environment points captured by means of the environment sensor (14) in the at least one region (22, 24), and detecting precipitation by comparing the point density in the at least one region (22, 24) with a predefined limit value. The invention further relates to a driving assistance system (12) for a vehicle (10), comprising an environment sensor (14) for capturing the environment of the vehicle (10) point by point and a computing device (16), which are connected to one another by means of a data transmission connection (18), the driving assistance system (12) being designed to carry out the method described above.