Ultrasonic Sensor Road Wetness Detection for Camera Recognition
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Solution Overview
Problem
Conventional camera-based environment recognition systems for means of transport face challenges in accurately distinguishing between wet and dry road conditions, leading to inadequate object detection due to the limitations of classifiers trained for either dry or wet environments, especially under conditions like tire spray and varying weather.
Innovation Solution
A method utilizing a first ultrasonic sensor to record environmental noise levels, which are compared to predefined thresholds to determine road wetness, allowing for the selection of optimized classifier parameters for environment recognition, thereby enhancing the reliability of object detection in varying conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional camera-based environment recognition uses fixed classifiers trained for either dry or wet environments, then the system structure remains simple, but the measurement precision of object detection deteriorates under varying road conditions
Solution Approach 1:
The system dynamically selects between different classifier sets (dry environment classifiers and wet environment classifiers) based on real-time road condition detection. The classifier configuration changes adaptively according to the detected road state, allowing the system to maintain high detection accuracy across varying environmental conditions without requiring a completely complex reconfiguration mechanism
Solution Approach 2:
The system changes the operational parameters of the environment recognition by selecting different classifier sets based on road wetness detection. When the road is detected as wet, wet-environment-optimized classifiers are activated; when dry, dry-environment classifiers are used. This parameter switching approach enables accurate object detection under different road conditions while keeping the overall system structure manageable
2Measurement precision
If ultrasonic sensors are mounted horizontally for parking assistance, then the sensing of horizontal distances is accurate, but the detection of road wetness information deteriorates
Solution Approach 1:
The ultrasonic sensor system is designed to perform multiple functions: horizontal distance measurement for parking assistance and road wetness detection. By mounting sensors in positions that allow both horizontal emission/detection and downward angle detection, the same sensor infrastructure serves dual purposes, eliminating the need for separate dedicated wetness sensors while maintaining both measurement capabilities
Solution Approach 2:
The system extends the functionality of horizontally-mounted ultrasonic sensors by utilizing signals reflected from the road surface at different angles. By analyzing ultrasonic reflections in addition to the primary horizontal sensing direction, the system extracts road wetness information from the same sensor deployment, effectively adding a new detection dimension without requiring additional sensor mounting complexity
3Reliability
If camera-based environment recognition operates without adaptive classifier selection, then the system operation is simple, but the reliability of object detection deteriorates in adverse weather conditions
Solution Approach 1:
The system performs preliminary detection of road conditions using ultrasonic sensors before executing the main object detection task with the camera. Based on this preliminary road state assessment, the system pre-selects the appropriate classifier set (dry or wet environment classifiers) to ensure optimal detection reliability from the start, rather than attempting to adapt during the detection process itself
Solution Approach 2:
The ultrasonic sensor acts as an intermediary that provides road condition information to the environment recognition system. This intermediary component enables the camera-based recognition system to adapt its classifier selection based on external environmental conditions, improving reliability without requiring the camera system itself to become more complex
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
The method improves the reliability and accuracy of environment recognition by adapting classifier parameters based on real-time road wetness information, reducing errors caused by wet conditions and enhancing the system's ability to detect objects, even when partially concealed by spray or in adverse weather.
Implementation Method 1
a first signal representing an environment of the means of transport is recorded by a first ultrasonic sensor of the means of transport
Data Source
AI summary
A method and an apparatus for supporting a camera-based environment recognition by a means of transport using road wetness information from a first ultrasonic sensor. The method includes: recording a first signal representing an environment of the means of transport by the first ultrasonic sensor of the means of transport; recording a second signal representing the environment of the means of transport by a camera of the means of transport; obtaining road wetness information on the basis of the first signal; selecting a predefined set of parameters from a plurality of predefined sets of parameters as a function of the road wetness information; and performing an environment recognition on the basis of the second signal in conjunction with the predefined set of parameters.