Audio Sensor Siren Detection via Frequency Analysis
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Solution Overview
Problem
Current audio sensor systems in vehicles face challenges in detecting emergency vehicle sirens due to insulation in modern cars, varying sound frequencies, and the Doppler Effect, making it difficult for drivers and autonomous vehicles to yield appropriately.
Innovation Solution
A method and system using audio sensors to digitize sound signals, compare them to digital templates, and determine the degree of similarity, with features like logarithmic amplification and multiple sensors for direction detection, enabling effective detection of sirens across different frequencies and environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If audio sensors are used to detect siren sounds, then the system can detect emergency vehicles, but the system cannot distinguish faint distant noises from loud close noises effectively
Solution Approach 1:
The patent applies parameter changes by transforming the audio signal from time-domain to frequency-domain using Fourier transform, and then analyzing the spectral characteristics to distinguish siren sounds from other noises. This parameter transformation enables the system to identify sirens based on their unique frequency modulation patterns rather than just amplitude levels.
Solution Approach 2:
The patent implements preliminary action by pre-processing the audio signal through filtering and spectral analysis before detection. The system prepares frequency spectra and identifies characteristic siren patterns in advance, which allows for faster and more accurate detection when a siren is actually present, reducing the impact of noise interference.
2Object-affected harmful factors
If the cabin is well insulated from outside noise, then passenger comfort is improved, but drivers cannot detect siren sounds produced by emergency vehicles
Solution Approach 1:
The patent introduces an intermediary approach by using audio sensors positioned strategically to capture external sounds while the cabin remains insulated. The system processes these captured sounds through spectral analysis to identify sirens, effectively mediating between the insulated cabin environment and the need for external sound detection.
Solution Approach 2:
The patent replaces the mechanical approach of opening windows or removing insulation with an electronic solution. Audio sensors and signal processing algorithms substitute for physical sound transmission paths, enabling siren detection while maintaining cabin insulation and passenger comfort.
3Object-generated harmful factors
If siren volume is limited to prevent noise pollution, then environmental quality is improved, but detection of siren sounds becomes more difficult
Solution Approach 1:
The patent transitions from one-dimensional amplitude-based detection to multi-dimensional frequency-domain analysis. By examining spectral characteristics, frequency modulation patterns, and temporal evolution of the sound signal, the system can detect low-volume sirens that would be imperceptible through simple amplitude thresholding, thus enabling detection despite volume limitations for noise pollution control.
4Reliability
If semi or fully autonomous vehicles are equipped to detect emergency vehicles, then safety is improved, but the system must operate within legal requirements to yield
Solution Approach 1:
The patent implements feedback by continuously monitoring the audio environment and providing real-time detection information to the vehicle's control system. When a siren is detected, the system provides feedback that triggers appropriate yielding actions, ensuring autonomous vehicles can detect emergency vehicles and comply with legal requirements to yield while maintaining operational safety.
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 system accurately detects emergency vehicle sirens in real-time, providing direction and velocity information, enhancing safety for both human and autonomous drivers by overcoming noise insulation and frequency variations.
Implementation Method 1
at least one audio sensor for generating a sound signal in response to a sound wave
Implementation Method 2
the method further comprises the step of logarithmically amplifying the sound signal before being digitized
Implementation Method 3
the perceived pitch of the siren may be significantly higher or lower as a result of the Doppler Effect caused by relative motion between the emergency vehicle and the sensing automobile
Data Source
AI summary
A system for detection of a target sound in an environment of a vehicle, includes an audio sensor, a computer processor, and a memory storing a digital target sound template produced by converting a sample of the target sound in accordance with conversion parameters. The computer processor receives a sound signal from the audio sensor, digitizes the sound signal in accordance with the conversion parameters, and determines a degree of similarity between the digitized signal and the digital target sound template. The sound signal may be logarithmically amplified before being digitized. The sound signal may be received from two audio sensors, and the direction of the target sound may be determined based on a difference between time indices for detection of the target sound for each audio sensor.