Road Moisture Detection via Acoustic Signal Shape Factor
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Solution Overview
Problem
Existing methods for detecting moisture on a road surface struggle to reliably detect minor degrees of wetting due to interference from environmental noise, which reduces the accuracy of aquaplaning risk assessment and vehicle safety system triggering.
Innovation Solution
A method that calculates energy values and shape factors from captured sound signals using average absolute deviation and effective values, forming quotients to differentiate between moisture-induced signals and noise, allowing for improved signal-to-noise ratio and resolution in detecting road surface wetness, while accounting for vehicle velocity and filtering out interfering frequencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If frequency filters are used to remove environmental sound signals, then interference from objects impacting the vehicle is reduced, but the energy of the signal is reduced making it more difficult to detect low degrees of wetting
Solution Approach 1:
The patent changes the evaluation parameters from frequency-based filtering to energy and shape factor analysis. By calculating the effective value (RMS) and average absolute deviation to derive a shape factor, the system evaluates signals in the time domain rather than frequency domain, allowing detection of moisture signals without filtering out low-energy wetting signals
Solution Approach 2:
The patent replaces the mechanical frequency filtering approach with a mathematical signal characterization approach using effective value and average absolute deviation calculations. This substitution allows the system to distinguish moisture signals from interference based on their temporal patterns rather than frequency content
2Ease of manufacture
If frequency filters are used to remove environmental sound signals, then the signal processing is simplified, but the frequencies of moisture signals do not inevitably lie in different frequency ranges than interference signals
Solution Approach 1:
The patent transitions from frequency-domain parameter analysis to time-domain parameter analysis by using effective value and average absolute deviation to calculate shape factor. This parameter change allows differentiation of moisture signals from interference signals based on their temporal characteristics rather than frequency separation
Solution Approach 2:
The patent introduces shape factor as an intermediary parameter that mediates between the raw sound signal and the final wetting detection. The shape factor, derived from the ratio of effective value to average absolute deviation, serves as a characteristic descriptor that enables reliable signal differentiation without requiring frequency filtering
3Object-affected harmful factors
If the energy of the signal is reduced by filtering, then environmental noise is removed, but it becomes more difficult to detect low degrees of wetting of the road surface
Solution Approach 1:
The patent changes from energy-reducing frequency filtering to energy-preserving time-domain analysis. By calculating the shape factor from effective value and average absolute deviation, the system maintains signal energy while achieving noise rejection through characteristic pattern recognition rather than energy suppression
Solution Approach 2:
The patent converts the low energy characteristic of small spray volumes from a disadvantage into a detectable feature. By using shape factor analysis based on temporal patterns rather than absolute energy levels, the system can detect even minor wetting signals that would be filtered out by traditional energy-based frequency filtering methods
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
Enhances the detection of minor degrees of road surface wetting by suppressing noise and improving resolution, enabling more accurate assessment of road conditions and reducing false triggers in vehicle safety systems.
Implementation Method 1
at least one sound signal caused by the moisture on a road surface is captured by at least one sensor device
Implementation Method 2
at least one energy value of at least one signal portion of the captured sound signal is calculated for the analysis, that the effective value of the at least one signal portion is calculated
Data Source
AI summary
In a method for detecting moisture on a road surface used by a vehicle, wherein at least one acoustic signal resulting from the moisture on the road surface is captured by at least one sensor device arranged on said vehicle, and wherein the captured acoustic signal is analysed via at least one analyser associated with said vehicle, it is provided according to the invention that at least one energy value of at least one signal portion of the captured acoustic signal is calculated for the analysis, that the effective value of the at least one signal portion is calculated, that a shape factor of the at least one signal portion is calculated from the quotient of the effective value and the energy value, that the minimum of the energy value in the at least one signal portion is calculated, that the maximum of the shape factor in the at least one signal portion is determined, that a quotient of the minimum of the energy value and the maximum of the shape factor is created and that said quotient is associated with a degree of wetness of the road surface.