Vehicle driving control apparatus including sound sensor and vehicle driving control method using the vehicle driving control apparatus
US-2020238981-A1 · Jul 30, 2020 · US
US11768283B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11768283-B2 |
| Application number | US-202117306327-A |
| Country | US |
| Kind code | B2 |
| Filing date | May 3, 2021 |
| Priority date | May 3, 2021 |
| Publication date | Sep 26, 2023 |
| Grant date | Sep 26, 2023 |
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A method of determining a distance between a vehicle and a sound source includes detecting, at a microphone of the vehicle, sounds from a sound source external to the vehicle. The sounds have a first frequency component at a first frequency and a second frequency component at a second frequency. The method also includes determining, at a processor of the vehicle, a classification of the sound source based on audio properties of the sounds. The method further includes determining a first energy level associated with the first frequency component and a second energy level associated with the second frequency component. The method also includes determining a ratio between the first energy level and the second energy level. The method further includes determining the distance between the vehicle and the sound source based on the ratio and the classification of the sound source.
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What is claimed is: 1. A method of determining a distance between a vehicle and a sound source external to the vehicle, the method comprising: detecting, at a microphone of the vehicle, sounds from the sound source, the sounds having a first frequency component at a fundamental frequency and a second frequency component at a first harmonic of the fundamental frequency; determining, at a processor of the vehicle, a first energy level associated with the first frequency component at the fundamental frequency and a second energy level associated with the second frequency component at the first harmonic of the fundamental frequency; determining a ratio between the first energy level and the second energy level; determining atmospheric characteristics associated with the vehicle; and determining, based on an energy level ratio model and the atmospheric characteristics, attenuation data between the different frequency components of the sounds emitted from the sound source; and determining the distance between the vehicle and the sound source based on a comparison of the ratio and the attenuation data. 2. The method of claim 1 , further comprising determining a classification of the sound source based on audio properties of the sounds, wherein the determination of the distance between the vehicle and the sound source is further based on the classification of the sound source. 3. The method of claim 1 , wherein the sounds from the sound source have a third frequency component at a second harmonic of the fundamental frequency, and further comprising: determining a third energy level associated with the third frequency component; and determining an additional ratio between the first energy level and the third energy level, wherein the distance between the vehicle and the sound source is further based on the additional ratio between the first energy level and the third energy level. 4. The method of claim 2 , wherein the classification is further determined based on a comparison of the audio properties of the sounds to audio properties of classified sounds in a database. 5. The method of claim 1 , wherein the sounds correspond to siren sounds, and wherein the sound source comprises an emergency vehicle. 6. The method of claim 1 , wherein the energy level ratio model indicates modeled enemy level ratios for different frequency components of sounds emitted from the sound source. 7. The method of claim 6 , wherein the attenuation data indicates changes, over a distance, of energy level ratios between the different frequency components of the sounds, wherein the energy level ratio model is identified in a sound source library based on a classification of the sound source, and wherein the atmospheric characteristics comprise at least one of an ambient air temperature, an atmospheric pressure, or a relative humidity. 8. The method of claim 7 , wherein the energy level ratio model in the sound source library is built and updated according to a machine-learning algorithm. 9. The method of claim 1 , wherein the second energy level associated with the second frequency component at the first harmonic of the fundamental frequency attenuates at a higher rate than the first energy level associated with the first frequency component at the fundamental frequency. 10. The method of claim 1 , further comprising generating a command to maneuver the vehicle in response to a determination that the distance fails to satisfy a threshold distance. 11. A system comprising: a microphone configured to detect sounds from a sound source external to a vehicle, the sounds having a first frequency component at a fundamental frequency and a second frequency component at a first harmonic of the fundamental frequency; and a processor coupled to the microphone, the processor configured to: determine a first energy level associated with the first energy level associated with the first frequency component at the fundamental frequency and a second energy level associated with the second frequency component at the first harmonic of the fundamental frequency; determine a ratio between the first energy level and the second energy level; determine atmospheric characteristics associated with the vehicle; and determine, based on an energy level ratio model and the atmospheric characteristics, attenuation data between the different frequency components of the sounds emitted from the sound source; and determine a distance between the vehicle and the sound source based on a comparison of the ratio and the attenuation data. 12. The system of claim 11 , further comprising determining a classification of the sound source based on audio properties of the sounds, and wherein the determination of the distance between the vehicle and the sound source is further based on the classification of the sound source. 13. The system of claim 11 , wherein the sounds from the sound source have a third frequency component at a second harmonic of the fundamental frequency, and wherein the processor is further configured to: determine a third energy level associated with the third frequency component; and determine an additional ratio between the first energy level and the third energy level, wherein the distance between the vehicle and the sound source is further based on the additional ratio between the first energy level and the third energy level. 14. The system of claim 13 , wherein the third frequency component corresponds to an additional harmonic of the fundamental frequency. 15. The system of claim 11 , wherein the sounds correspond to siren sounds, and wherein the sound source comprises an emergency vehicle. 16. The system of claim 11 , wherein the energy level ratio model indicates modeled energy level ratios for different frequency components of sounds emitted from the sound source. 17. The system of claim 16 , wherein the attenuation data indicates changes, over a distance, of energy level ratios between the different frequency components of the sounds, wherein the energy level ratio model is identified in a sound source library based on a classification of the sound source, and wherein the atmospheric characteristics comprise at least one of an ambient air temperature, an atmospheric pressure, or a relative humidity. 18. The system of claim 17 , wherein the energy level ratio model in the sound source library is built and updated according to a machine-learning algorithm. 19. A non-transitory computer-readable medium having stored therein instructions executable by a processor to cause the processor to perform functions, the functions comprising: determining a classification of a sound source external to a vehicle based on audio properties of sounds from the sound source that are detected by a microphone, the sounds having a first frequency component at a fundamental frequency and a second frequency component at a first harmonic of the fundamental frequency; determining a first energy level associated with the first energy level associated with the first frequency component at the fundamental frequency and a second energy level associated with the second frequency component at the first harmonic of the fundamental frequency; determining a ratio between the first energy level and the second energy level; determining atmospheric characteristics associated with the vehicle; determining, based on an energy level ratio model and the atmospheric characteristics, attenuation data between the different frequency components of the sounds emitted from the sound source; and determining a dist
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