Vehicle Microphone Layout for Road Wetness Detection
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Solution Overview
Problem
Existing systems face challenges in accurately detecting road conditions, particularly wetness, due to microphone fouling and interference from unwanted noise sources like wind, engine noise, and other noise, which can confound the prediction of environmental conditions, especially in autonomous vehicles.
Innovation Solution
Positioning microphones between and behind rear wheels to capture relevant road noise signals, applying filters and deep learning models to process these signals, and integrating them with other sensor data for precise road wetness prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If microphones are positioned on the vehicle to detect road noise signals, then road condition detection capability is improved, but microphone fouling and unwanted noise interference increase
Solution Approach 1:
The patent introduces an intermediary processing system that includes noise identification and removal modules. This intermediary layer sits between the microphone input and the road condition analysis, filtering out unwanted noise sources (engine noise, wind noise, road grating noise) and isolating the relevant tire-road interaction signals. The system uses reference microphones and signal processing algorithms as mediators to separate useful information from harmful interference.
Solution Approach 2:
The patent extracts only the relevant components from the complex audio signal. The noise removal module specifically identifies and extracts unwanted noise sources (engine noise, wind noise, road grating noise) from the total audio signal, separating them from the tire-road interaction signals. This extraction process isolates the useful information needed for road condition detection while discarding harmful interference.
2Measurement precision
If multiple sensors and processing systems are integrated to improve detection accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent implements a multi-functional processing system where the same audio processing pipeline handles multiple road conditions (wetness, ice, snow) and multiple noise sources (engine noise, wind noise, road grating noise). The noise removal module and road condition analysis module serve universal purposes across different operating conditions, reducing the need for separate specialized systems for each function.
Solution Approach 2:
The patent combines multiple sensors (microphones, reference sensors) and multiple processing functions (noise identification, noise removal, road condition analysis) into an integrated system. The audio processing module merges signal processing tasks and the system combines data from multiple sources to achieve accurate road condition detection, reducing overall system complexity through consolidation.
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 solution effectively reduces unwanted noise interference and enhances the accuracy of road wetness detection, enabling better autonomous vehicle operation by altering driving actions, modifying routes, and activating cleaning systems.
Implementation Method 1
one or more microphones of the vehicle...configured to detect one or more road noise signals
Implementation Method 2
use the stored model to generate information associated with the discrete classification or continuous regression/estimation of road wetness based on the one or more road noise signals
Data Source
Figure 1A
Figure 1B
Figure 1C~1D
AI summary
It is advantageous for a vehicle to detect road wetness or related environmental conditions. This is particularly true for self-driving vehicles, which can then adjust the manner of automated operation of the vehicle to increase safety by reducing speed, braking earlier, adjusting internal estimates of road traction parameters, or adjusting autonomous operation in some other manner. It is difficult to directly measure road wetness (e.g., using spectroscopy or other methods directed at the road surface), however, it is possible to indirectly estimate road wetness based on road noise audio signals detected via one or more microphones (1540A, 1540B) disposed on the vehicle. The location of the microphones, the type of post-processing applied to the audio signals, or other factors can be adapted to increase the useful road wetness-related content of such audio signals while reducing the presence of engine noise, road noise, or other confounding signals.