Method and device for controlling terrain mode by using road condition judgment model based on deep learning
A technology of deep learning and learning models, applied in control devices, neural learning methods, road vehicle drive control systems, etc.
Active Publication Date: 2022-03-18
HYUNDAI MOBIS CO LTD
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- Claims
- Application Information
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[0008] However, the conventional terrain mode control technology requires the driver to manually determine the road surface condition by using the naked eye, requires additional manipulation by the driver to change the terrain mode, and needs to provide a dedicated device in the vehicle, such as a physical button or a software button, which leads to series of restrictions
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[0022] The present disclosure seeks, in at least one embodiment, to provide a technique for allowing a vehicle to automatically determine road conditions and respond to various road conditions without driver intervention by using a deep learning-based learning model trained in advance. Circumstances change the driving state of the vehicle.
[0023] The present invention, in another embodiment, seeks to assist a vehicle in performing terrain mode control by determining road surface conditions even in ordinary and non-critical driving situations that do not constitute electronic stability control (ESC) intervention, and Determines which terrain mode is optimized for the road surface, then provides the terrain mode information to the driver.
[0024] The present disclosure seeks, in another embodiment, to provide a means for controlling terrain modes to enable vehicle manufactures to eliminate the need to install a separate physical button on the vehicle to assist the driver in m...
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The present disclosure provides, in some embodiments, a method and apparatus that enables a vehicle to autonomously estimate a road surface condition by using a deep learning-based learning model, determine a topographic pattern optimized for a road surface on which the vehicle is traveling, and control a corresponding on-board module to enable the vehicle to autonomously estimate the road surface condition by using the deep learning-based learning model. Therefore, the terrain mode is automatically controlled. By enabling the vehicle to automatically determine the road surface condition and providing the terrain mode information corresponding to the road surface condition to the driver, the driver does not need to manually check the road surface condition with naked eyes, so that the convenience of the driver is improved.
Description
[0001] Cross References to Related Applications [0002] This application is based on and claims priority from Korean Patent Application No. 10-2020-0107699 filed on August 26, 2020, the disclosure of which is incorporated herein by reference in its entirety. technical field [0003] The present disclosure relates, in some embodiments, to a method and apparatus for controlling a terrain mode by using a deep learning-based road condition judgment model. More specifically, the present disclosure relates to a method and apparatus for controlling a terrain mode by using a pre-trained road situation judgment model based on deep learning and road surface data obtained from a camera. Background technique [0004] The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art. [0005] The drivability of the vehicle will vary with various conditions of the road surface, such as wet roads, unpaved o...
Claims
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IPC IPC(8): B60W40/068B60W40/06B60W50/00B60W60/00
CPCB60W40/068B60W40/06B60W50/00B60W60/001B60W2050/0019B60W2520/28B60W2520/30B60W30/182B60W10/10B60W10/06G06V20/588B60W2420/403B60W50/14B60W30/14B60R11/04B60R11/0229G01S13/865B60W30/09B60W2552/40B60W2050/0002B60W2050/146B60W2050/143B60R2021/0004B60Y2300/14B60Y2300/182B60W2420/408B60K35/22B60K35/26G06N3/09G06T2207/20081B60W30/02G05B13/027B60W2710/06B60W2710/1005G06V20/56
Inventor 朴信基李权熙
Owner HYUNDAI MOBIS CO LTD