System and Method of Automatic Image View Alignment for Camera-Based Road Condition Detection on a Vehicle

    公开(公告)号:US20240046491A1

    公开(公告)日:2024-02-08

    申请号:US17815760

    申请日:2022-07-28

    IPC分类号: G06T7/33 G06V20/56

    摘要: A system and method of automatic image view alignment for a camera-based road condition detection on a vehicle. The method includes transforming a fisheye image into a non-distorted subject image, comparing the subject image with a reference image, aligning the subject image with the reference image, and analyzing the aligned subject image to detect and identify road conditions in real-time as the vehicle is in operation. The subject image is aligned with the reference image by determining a distance (d) between predetermined feature points of the subject and reference images, estimating a pitch of a projection center based on the distance d, and generating an aligned subject image by applying a rectification transformation on the fisheye image by relocating a center of projection of the fisheye image by the pitch angle .

    APPARATUS AND METHODOLOGY OF ROAD CONDITION CLASSIFICATION USING SENSOR DATA

    公开(公告)号:US20220032946A1

    公开(公告)日:2022-02-03

    申请号:US16944911

    申请日:2020-07-31

    摘要: Methods and systems are provided for controlling a vehicle action based on a condition of a road on which a vehicle is travelling, including: obtaining first sensor data as to a surface of the road from one or more first sensors onboard the vehicle; obtaining second sensor data from one or more second sensors onboard the vehicle as to a measured parameter pertaining to operation of the vehicle or conditions pertaining thereto; generating a plurality of road surface channel images from the first sensor data, wherein each road surface channel image captures one of a plurality of facets of properties of the first sensor data; classifying, via a processor using a neural network model, the condition of the road on which the vehicle is travelling, based on the measured parameter and the plurality of road surface channel images; and controlling a vehicle action based on the classification of the condition of the road.

    SMART MULTIFUNCTIONAL LENS COATINGS
    3.
    发明申请

    公开(公告)号:US20200064520A1

    公开(公告)日:2020-02-27

    申请号:US16108850

    申请日:2018-08-22

    摘要: Systems, methods and devices to inhibit sensing reduction in imperfect sensing conditions are described. A multifunctional coating superposing a lens includes a self-cleaning layer and a heating layer. The self-cleaning layer defines an external surface configured to be exposed to an exterior environment. The external surface defines three-dimensional surface features thereon. The three-dimensional surface features are adjacently disposed arcuate features that inhibit adhering of solid particles to the external surface and wetting of the external surface. The heating layer is in thermal communication with the external surface. The heating layer is selectively actuated to provide thermal energy to the external surface through resistive heating. Each of the self-cleaning layer and the heating layer is transparent to a predetermined wavelength of light.

    Smart sensor-cover apparatus and methods and computer products for implementing same

    公开(公告)号:US10310298B2

    公开(公告)日:2019-06-04

    申请号:US15334136

    申请日:2016-10-25

    摘要: A smart sensor-cover apparatus for covering a sensor, such as a vehicle sensor, includes controllable layers, responsive to inputs, such as a wavelength-filtering controllable layer to selectively filter out select wavelengths of light; a polarizing layer controllable layer to selectively polarize or allow through light; a concealing controllable layer to change between a visible state and a concealed state; and an outermost, cleaning, layer configured to melt incident ice. The outermost layer in various embodiments has an outer surface positioned generally flush with an outer vehicle surface for operation of the apparatus, to promote the concealing effect when the concealing layer is not activate. The outermost layer may be configured to self-mend when scratched, and in some cases is hydrophobic, hydrophilic, or super hydrophilic outer surface. An insulating component, such as a glass or polycarbonate layer, is positioned between each adjacent controllable layer.

    Vision-based wet road surface detection using texture analysis
    6.
    发明授权
    Vision-based wet road surface detection using texture analysis 有权
    基于视觉的湿路面检测采用纹理分析

    公开(公告)号:US09594964B2

    公开(公告)日:2017-03-14

    申请号:US14302622

    申请日:2014-06-12

    IPC分类号: G06K9/00

    CPC分类号: G06K9/00791

    摘要: A method for determining a wet road surface condition for a vehicle driving on a road. A first image exterior of the vehicle is captured by an image capture device. A second image exterior of the vehicle is captured by the image capture device. A section of the road is identified in the first and second captured images. A texture of the road in the first and second images captured by a processor are compared. A determination is made whether the texture of the road in the first image is different from the texture of the road in the second image. A wet driving surface indicating signal is generated in response to the determination that the texture of the road in the first image is different than the texture of the road in the second image.

    摘要翻译: 一种用于确定在道路上行驶的车辆的湿路面状况的方法。 车辆的第一图像外部由图像捕获装置捕获。 车辆的第二图像外部由图像捕获装置捕获。 在第一和第二拍摄图像中识别道路的一部分。 比较由处理器捕获的第一和第二图像中的道路纹理。 确定第一图像中的道路的纹理是否不同于第二图像中的道路的纹理。 响应于第一图像中的道路的纹理与第二图像中的道路的纹理不同的确定,产生湿驱动表面指示信号。

    MACHINE LEARNING-BASED TRACTIVE LIMIT AND WHEEL STABILITY STATUS ESTIMATION

    公开(公告)号:US20240166192A1

    公开(公告)日:2024-05-23

    申请号:US18057281

    申请日:2022-11-21

    IPC分类号: B60W30/02 B60W40/06

    摘要: A method of estimating a performance characteristic of a wheel of a vehicle, includes selecting relevant input features based on wheel dynamics and tire behavior, and collecting experimental data for each of the relevant input features at each of a plurality of vehicle operating conditions. The method further includes manually identifying and labeling wheel stability status over time from the experimental data and calculating tractive limit over time from the experimental data. The method also includes training a tractive limit model and training a wheel stability status model. The method further includes receiving a plurality of testing inputs, wherein each of the plurality of testing inputs is received from a sensor on-board the vehicle or from a controller on-board the vehicle and, processing the received testing inputs in a predetermined machine learning process to calculate in one or more data processors a prediction of the performance characteristic.

    System and method for adapting parameters used in target slip estimation

    公开(公告)号:US11027776B2

    公开(公告)日:2021-06-08

    申请号:US16508754

    申请日:2019-07-11

    摘要: Systems and methods are provided for generating adapted tuning parameters for target slip estimation, the parameters being adapted to real-time road surface conditions. The method includes, receiving, from a road surface detection module, a road surface condition, Sn, from among N road surface conditions S, range of friction, mu, and a confidence level, Ci. The method receives sensor system data from a sensor system, and determines, as a function of Sn, range of mu, and Ci, initial estimator values including an estimated initial frictional force {circumflex over (Θ)}(0), an initial gain, P0, and an initial projected range of signal bounds, (Pu) and (Pl). The method tunes (i.e., adapts) the initial estimator values to generate therefrom adapted tuning parameters based on received inputs. The method outputs adapted tuning parameters.

    Fusion-based wet road surface detection

    公开(公告)号:US10339391B2

    公开(公告)日:2019-07-02

    申请号:US15245536

    申请日:2016-08-24

    摘要: A method for determining wetness on a path of travel. A surface of the path of travel is captured by at least one image capture device. A plurality of wet surface detection techniques is applied to the at least one image. An analysis for each wet surface detection technique is determined in real-time of whether the surface of the path of travel is wet. Each analysis independently determines whether the path of travel is wet. Each analysis by each wet surface detection technique is input to a fusion and decision making module. Each analysis determined by each wet surface detection technique is weighted within the fusion and decision making module by comprehensive analysis of weather information, geology information, and vehicle motions. A wet surface detection signal is provided to a control device. The control device applies the wet surface detection signal to mitigate the wet surface condition.