Vehicle Ultrasonic Roadway Detection Using Ground Echo Variance
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Solution Overview
Problem
Existing roadway recognition systems in vehicles rely heavily on additional sensors like cameras, which are not always necessary for accurately determining the condition of the roadway, and ultrasonic systems struggle to differentiate between ground reflections and object reflections effectively.
Innovation Solution
An ultrasonic system with a calculation apparatus that evaluates the variance of ground echo distribution using predefined classifiers, determining roadway conditions based on statistical features like frequency, amplitude, and clutter level, eliminating the need for additional sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If additional sensors like cameras are used for roadway recognition, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The ultrasonic sensor system is designed to perform multiple functions: traditional distance measurement to objects and simultaneously roadway condition assessment. By analyzing ground echo characteristics (amplitude, frequency, time-of-flight patterns), the same sensor determines road surface properties like wetness, ice, or gravel without requiring separate specialized sensors.
Solution Approach 2:
The system uses the existing ultrasonic sensor infrastructure and its inherent ground echo signals for roadway recognition. Instead of adding external cameras or other sensors, the system repurposes the self-generated echo data that would otherwise be filtered out as interference, making the system self-sufficient for dual purposes.
2Reliability
If ground echo signals are filtered out as interference, then distance measurement reliability is improved, but loss of information occurs
Solution Approach 1:
The system converts the previously harmful ground echo interference into a beneficial information source. By analyzing characteristics of these echoes (amplitude variations, frequency content, temporal patterns), the system extracts valuable roadway condition data such as detecting wet roads, ice, or gravel surfaces while maintaining reliable object distance measurement through separate signal processing channels.
Solution Approach 2:
The calculation apparatus acts as an intermediary that separates and processes different signal components. It distinguishes between object echo signals (for distance measurement) and ground echo signals (for roadway condition assessment) using statistical analysis and pattern recognition, allowing both functions to coexist without mutual interference.
3Device complexity
If ultrasonic sensors are used for roadway condition assessment, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The system performs preliminary characterization of ground echo patterns under various roadway conditions during a learning phase. Statistical parameters (mean, variance, skewness, kurtosis) and classifiers are pre-computed and stored for different road surfaces (dry, wet, icy, gravel). During operation, measured echo patterns are compared against these pre-established references, enabling accurate roadway condition identification without real-time complex analysis.
Solution Approach 2:
The system analyzes multiple statistical parameters (mean, variance, skewness, kurtosis) and multiple echo characteristics (amplitude, frequency, time-of-flight) beyond what a simple ultrasonic measurement would require. This excessive analysis of available signal features compensates for the single-sensor limitation, achieving precision comparable to multi-sensor systems through comprehensive signal characterization.
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 reliable and efficient roadway condition assessment using ultrasonic sensors alone, allowing adaptive driver assistance and autonomous driving functions by accurately identifying road surface conditions and coefficients of friction.
Implementation Method 1
an acoustic signal is emitted and the reception of an echo is evaluated. A distance to the object that is reflecting the emitted signal in the echo can be ascertained therefrom
Implementation Method 2
Ultrasonic systems in vehicles are generally available. They usually serve to ascertain a distance of objects from the sensor
Implementation Method 3
the calculation apparatus is configured to determine a variance of a ground echo distribution within a roadway portion on which the vehicle is moving
Implementation Method 4
In the case of ultrasonic sensors that are mounted on vehicles, a reflection from the substrate is usually also present in addition to a reflection from objects, so that echoes can be received from the ground
Data Source
AI summary
An ultrasonic system of a vehicle. The ultrasonic system includes: at least one ultrasonic sensor for ascertaining a distance of objects from the vehicle by comparing an emitted signal and a reflected echo, and a calculation apparatus for evaluating a measured signal of the ultrasonic sensor. The calculation apparatus is configured to determine a variance of a ground echo distribution within a roadway portion on which the vehicle is moving, and to ascertain the condition of the roadway portion on the basis of at least one predefined classifier that associates individual values of the variance with a roadway condition.