Road surface recognition apparatus, vehicle having the same, and method of controlling vehicle

Patent metadata

Field	Value
Publication number	US-12214775-B2
Application number	US-202117386031-A
Country	US
Kind code	B2
Filing date	Jul 27, 2021
Priority date	Sep 11, 2020
Publication date	Feb 4, 2025
Grant date	Feb 4, 2025

Abstract

A vehicle having a road surface recognition apparatus, may perform obtaining, by a controller, sound data for a sound detected by a sound detector while driving; obtaining, by the controller, driving data for driving information detected by a driving information detector; recognizing, by the controller, a type of road surface based on the obtained sound data and the obtained driving data; and controlling, by the controller, a traction control system based on information related to the recognized type of the road surface.

First claim

What is claimed is:

1. A road surface recognition apparatus comprising:
a memory configured to store one or more instructions; and
a processor configured to execute the one or more instructions stored in the memory,
wherein the instructions, when executed by the processor, cause the processor to:
obtain sound data for a sound detected by a sound detecting sensor;
obtain driving data of a vehicle for driving information detected by a driving information detecting sensor; and
recognize a type of road surface according to the sound data and the driving data, and
wherein the processor is further configured to:
transform the obtained sound data into sound data in a frequency domain;
obtain a first feature vector using longitudinal acceleration data and driving speed data among the driving data, and the sound data in the frequency domain;
classify a first type of the road surface in a first order using the first feature vector and a first classifier model;
obtain a second feature vector according to a plurality of wheel speed data, the longitudinal acceleration data, steering angle data, lateral acceleration data, and yaw rate data among the driving data;
classify a second type of the road surface in a second order using the second feature vector and a second classifier model; and
determine the type of the road surface by selecting at least one of the first type of the road surface and the second type of the road surface based on the longitudinal acceleration data and reference longitudinal acceleration data.

2. The road surface recognition apparatus according to claim 1 , wherein the processor is configured to:
according to the longitudinal acceleration data and the reference longitudinal acceleration data, in a response to the longitudinal acceleration being less than the reference longitudinal acceleration, select the first type of the road surface, and
in a response to the longitudinal acceleration being greater than or equal to the reference longitudinal acceleration, select the second type of the road surface.

3. The road surface recognition apparatus according to claim 1 , the processor is configured to:
recognize the type of the road surface according to the selected type of the road surface and state transition information for a remaining type of the road surface.

4. The road surface recognition apparatus according to claim 1 ,
wherein the first classifier model includes a support vector machine; and
wherein the second classifier model includes a deep neural network.

5. The road surface recognition apparatus according to claim 1 , wherein the processor is configured to receive the sound data through an Electronic Stability Control (ESC) system.

6. A vehicle comprising:
a sound detecting sensor;
a driving information detecting sensor; and
a controller electrically connected to the sound detecting sensor and the driving information detecting sensor and configured to:
obtain sound data for a sound detected by the sound detecting sensor,
obtain driving data for driving information detected by the driving information detecting sensor,
recognize a type of road surface according to the obtained sound data and the obtained driving data, and
control a driving force of a vehicle according to information related to the recognized type of the road surface,
wherein the controller is configured to:
transform the obtained sound data into sound data in a frequency domain;
obtain a first feature vector using longitudinal acceleration data and driving speed data among the driving data, and the sound data in the frequency domain;
classify a first type of the road surface in a first order using the first feature vector and a first classifier model;
obtain a second feature vector according to a plurality of wheel speed data, the longitudinal acceleration data, steering angle data, lateral acceleration data, and yaw rate data among the driving data;
classify a second type of the road surface in a second order using the second feature vector and a second classifier model; and
determine the type of the road surface by selecting at least one of the first type of the road surface and the second type of the road surface based on the longitudinal acceleration data and reference longitudinal acceleration data.

7. The vehicle according to claim 6 , wherein the controller is configured to:
according to the longitudinal acceleration data and the reference longitudinal acceleration data, in a response to the longitudinal acceleration being less than the reference longitudinal acceleration, select the first type of the road surface, and
in a response to the longitudinal acceleration being greater than or equal to the reference longitudinal acceleration, select the second type of the road surface.

8. The vehicle according to claim 6 , wherein the controller is configured to:
recognize the type of the road surface according to the selected type of the road surface and state transition information for a remaining type of the road surface.

9. The vehicle according to claim 6 ,
wherein the first classifier model includes a support vector machine; and
wherein the second classifier model includes a deep neural network.

10. The vehicle according to claim 6 , wherein the sound detecting sensor is mounted on a right rear side of a vehicle body.

11. The vehicle according to claim 6 , further including:
a traction control system configured to control the driving force in a response to a control command of the controller.

12. The vehicle according to claim 6 , wherein the controller is configured to:
obtain a friction coefficient corresponding to the information related to the recognized type of the road surface, and
control an operation of at least one of a brake and an engine based on the obtained friction coefficient.

13. A method of controlling a vehicle, the method comprising:
obtaining, by a controller, sound data for a sound detected by a sound detecting sensor while driving;
obtaining, by the controller, driving data of the vehicle for driving information detected by a driving information detecting sensor;
recognizing, by the controller, a type of road surface according to the obtained sound data and the obtained driving data; and
controlling, by the controller, a traction control system according to information related to the recognized type of the road surface,
wherein the controller is further configured to:
transform the obtained sound data into sound data in a frequency domain;
obtain a first feature vector using longitudinal acceleration data and driving speed data among the driving data, and the sound data in the frequency domain;
classify a first type of the road surface in a first order using the first feature vector and a first classifier model;
obtain a second feature vector according to a plurality of wheel speed data, the longitudinal acceleration data, steering angle data, lateral acceleration data, and yaw rate data among the driving data;
classify a second type of the road surface in a second order using the second feature vector and a second classifier model; and

determine the type of the road surface by selecting at least one of the first type of the road surface and the second type of the road surface based on the longitudinal acceleration data and reference longitudinal acceleration data.

Assignees

• Hyundai Motor Co Ltd
• Kia Corp
• Industry Univ Cooperation Foundation Hanyang Univ Iucf Hyu

Inventors

• Um Ik Jin
• Kang Jun Han
• Park Jungho
• Kim Man Dong
• Chung Chung Choo
• Lee Seung-Hi
• Kim Dae Jung
• Kim Jin Sung

Classifications

• B60W30/18172

  Preventing, or responsive to skidding of wheels · CPC title

• B60W2555/20

  Ambient conditions, e.g. wind or rain · CPC title

• B60W2710/18

  Braking system · CPC title

• B60W2710/06

  Combustion engines, Gas turbines · CPC title

• B60W2520/10

  Longitudinal speed · CPC title