Laser Radar Fusion for Wet Surface Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous vehicles face challenges in detecting wet surfaces using existing sensors, which can impact safe operation, especially when radar sensors fail to detect rain or water kicked up by vehicle movement, necessitating a more effective method to identify wet road conditions.
Innovation Solution
The use of laser data analysis by a computing device to identify unassociated laser data points, which indicates a wet surface, combined with additional information from radar, camera, and weather data, to determine the wetness of the road and adjust vehicle behavior accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radar sensors are used to detect weather conditions, then the detection range is extended, but the ability to detect wet surfaces and kicked-up water is insufficient
Solution Approach 1:
The patent combines laser sensor data with radar sensor data to detect wet surfaces. The laser sensor detects water droplets and kicked-up water with high precision, while radar provides broader weather context. By merging these complementary sensor inputs, the system achieves both accurate wet surface detection and reliable weather condition monitoring.
Solution Approach 2:
The laser sensor, originally designed for object detection, is repurposed to detect wet surfaces and weather conditions. This multi-functional use of the laser sensor allows it to contribute to both navigation safety and weather condition monitoring, improving overall system reliability without adding dedicated wet surface detection hardware.
2Reliability
If existing sensors are used for autonomous vehicle operation, then the system complexity is reduced, but the ability to safely detect adverse weather conditions is compromised
Solution Approach 1:
The existing laser sensor used for object detection is repurposed to also detect wet surfaces and weather conditions. This multi-functional approach improves safety in adverse weather without requiring additional dedicated sensors, thereby limiting the increase in system complexity.
Solution Approach 2:
The system processes laser data points to identify patterns indicating wet surfaces, such as unassociated data points from kicked-up water. This feedback mechanism allows the vehicle to adapt its operation based on detected weather conditions, improving safety without proportionally increasing system complexity.
3Measurement precision
If laser data points are analyzed to identify wet surfaces, then the detection accuracy is improved, but the data processing complexity increases
Solution Approach 1:
The system uses feedback from laser data point analysis to identify wet surface conditions. By continuously monitoring and comparing laser data patterns against known wet surface signatures, the system achieves high detection precision while managing processing complexity through iterative refinement rather than complex one-time analysis.
Solution Approach 2:
The laser sensor data serves multiple purposes: primary object detection and secondary wet surface detection. This self-service approach allows the same data to be reused for multiple functions, improving detection precision without proportionally increasing processing complexity.
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
This approach enhances the ability of autonomous vehicles to safely navigate by accurately detecting wet surfaces, reducing the risk of accidents and improving driving performance in adverse weather conditions.
Implementation Method 1
receiving laser data collected for an environment of a vehicle... determining laser data points... identifying an indication that a surface on which the vehicle travels is wet
Data Source
AI summary
Example methods and systems for detecting weather conditions including wet surfaces using vehicle onboard sensors are provided. An example method includes receiving laser data collected for an environment of a vehicle. The method also includes determining laser data points that are associated with one or more objects in the environment, and based on laser data points being unassociated with the one or more objects in the environment, identifying an indication that a surface on which the vehicle travels is wet. The method may further include receiving radar data collected for the environment of the vehicle that is indicative of a presence of the one or more objects in the environment of the vehicle, and identifying the indication that the surface on which the vehicle travels is wet further based on laser data points being unassociated with the one or more objects in the environment indicated by the radar data.