SYSTEMS AND METHODS FOR ENHANCED DISTANCE ESTIMATION BY A MONO-CAMERA USING RADAR AND MOTION DATA

    公开(公告)号:US20200167941A1

    公开(公告)日:2020-05-28

    申请号:US16200932

    申请日:2018-11-27

    Abstract: Systems and methods for depth estimation of images from a mono-camera by use of radar data by: receiving, a plurality of input 2-D images from the mono-camera; generating, by the processing unit, an estimated depth image by supervised training of an image estimation model; generating, by the processing unit, a synthetic image from a first input image and a second input image from the mono-camera by applying an estimated transform pose; comparing, by the processing unit, an estimated three-dimensional (3-D) point cloud to radar data by applying another estimated transform pose to a 3-D point cloud wherein the 3-D point cloud is estimated from a depth image by supervised training of the image estimation model to radar distance and radar doppler measurement; correcting a depth estimation of the estimated depth image by losses derived from differences: of the synthetic image and original images; of an estimated depth image and a measured radar distance; and of an estimated doppler information and measured radar doppler information.

    VEHICLE PERCEPTION SYSTEM ON-LINE DIANOSTICS AND PROGNOSTICS

    公开(公告)号:US20200094848A1

    公开(公告)日:2020-03-26

    申请号:US16139782

    申请日:2018-09-24

    Abstract: A method of on-line diagnostic and prognostic assessment of an autonomous vehicle perception system includes detecting, via a sensor, a physical parameter of an object external to the vehicle. The method also includes communicating data representing the physical parameter via the sensor to an electronic controller. The method additionally includes comparing the data from the sensor to data representing the physical parameter generated by a geo-source model. The method also includes comparing results generated by a perception software during analysis of the data from the sensor to labels representing the physical parameter from the geo-source model. Furthermore, the method includes generating a prognostic assessment of a ground truth for the physical parameter of the object using the comparisons of the sensor data to the geo-source model data and of the software results to the geo-source model labels. A system for on-line assessment of the vehicle perception system is also disclosed.

    High Precision Low Bit Convolutional Neural Network

    公开(公告)号:US20200065661A1

    公开(公告)日:2020-02-27

    申请号:US16107315

    申请日:2018-08-21

    Abstract: Described herein are systems, methods, and computer-readable media for generating and training a high precision low bit convolutional neural network (CNN). A filter of each convolutional layer of the CNN is approximated using one or more binary filters and a real-valued activation function is approximated using a linear combination of binary activations. More specifically, a non-1×1 filter (e.g., a k×k filter, where k>1) is approximated using a scaled binary filter and a 1×1 filter is approximated using a linear combination of binary filters. Thus, a different strategy is employed for approximating different weights (e.g., 1×1 filter vs. a non-1×1 filter). In this manner, convolutions performed in convolutional layer(s) of the high precision low bit CNN become binary convolutions that yield a lower computational cost while still maintaining a high performance (e.g., a high accuracy).

    Autonomous vehicle adaptive parallel image processing system

    公开(公告)号:US10572748B2

    公开(公告)日:2020-02-25

    申请号:US15833382

    申请日:2017-12-06

    Abstract: An adaptive parallel imaging processing system in a vehicle is provided. The system may include, but is not limited to, a plurality of processors and a resource management system including, but not limited to, an execution monitor, the execution monitor configured to calculate an average utilization of each of the plurality of processors over a moving window, and a service scheduler controlling a request queue for each of the plurality of processors, the service scheduler scheduling image processing tasks in the respective request queue for the each of the plurality of processors based upon the average utilization of each of the plurality of processors, the capabilities of each of the plurality of processors, and a priority associated with each image processing task, wherein an autonomous vehicle control system is configured to generate the instructions to control the at least one vehicle system based upon the processed image processing tasks.

    MANAGING AUTOMATED DRIVING COMPLEXITY OF THE FORWARD PATH USING PERCEPTION SYSTEM MEASURES

    公开(公告)号:US20190232955A1

    公开(公告)日:2019-08-01

    申请号:US15886492

    申请日:2018-02-01

    Abstract: Technical solutions are described for controlling an automated driving system of a vehicle. An example method includes computing a complexity metric of an upcoming region along a route that the vehicle is traveling along. The method further includes, in response to the complexity metric being below a predetermined low-complexity threshold, determining a trajectory for the vehicle to travel in the upcoming region using a computing system of the vehicle. Further, the method includes in response to the complexity metric being above a predetermined high-complexity threshold, instructing an external computing system to determine the trajectory for the vehicle to travel in the upcoming region. If the trajectory cannot be determined by the external computing system a minimal risk condition maneuver of the vehicle is performed.

    CROSS TRAFFIC DETECTION USING CAMERAS
    77.
    发明申请

    公开(公告)号:US20190064841A1

    公开(公告)日:2019-02-28

    申请号:US15690966

    申请日:2017-08-30

    Abstract: A vehicle, system and method of driving of an autonomous vehicle. The vehicle includes a camera for obtaining an image of a surrounding region of the vehicle, an actuation device for controlling a parameter of motion of the vehicle, and a processor. The processor selects a context region within the image, wherein the context region including a detection region therein. The processor further estimates a confidence level indicative of the presence of at least a portion of the target object in the detection region and a bounding box associated with the target object, determines a proposal region from the bounding box when the confidence level is greater than a selected threshold, determines a parameter of the target object within the proposal region, and controls the actuation device to alter a parameter of motion of the vehicle based on the parameter of the target object.

    FUSION METHOD FOR CROSS TRAFFIC APPLICATION USING RADARS AND CAMERA
    79.
    发明申请
    FUSION METHOD FOR CROSS TRAFFIC APPLICATION USING RADARS AND CAMERA 有权
    用RADARS和CAMERA进行交叉交通应用的融合方法

    公开(公告)号:US20160291149A1

    公开(公告)日:2016-10-06

    申请号:US14679995

    申请日:2015-04-06

    Abstract: A method and system are disclosed for tracking objects which are crossing behind a host vehicle. Target data from a vision system and two radar sensors are provided to an object detection fusion system. Salient points on the target object are identified and tracked using the vision system data. The salient vision points are associated with corresponding radar points, where the radar points provide Doppler radial velocity data. A fusion calculation is performed on the salient vision points and the radar points, yielding an accurate estimate of the velocity of the target object, including its lateral component which is difficult to obtain using radar points only or traditional vision system methods. The position and velocity of the target object are used to trigger warnings or automatic braking in a Rear Cross Traffic Avoidance (RCTA) system.

    Abstract translation: 公开了用于跟踪在主车辆后方穿过的物体的方法和系统。 来自视觉系统和两个雷达传感器的目标数据被提供给物体检测融合系统。 使用视觉系统数据识别和跟踪目标对象上的突出点。 显着的视点与相应的雷达点相关联,雷达点提供多普勒径向速度数据。 对显着视点和雷达点进行融合计算,产生目标物体的速度的准确估计,包括其仅使用雷达点或传统视觉系统方法难以获得的侧向分量。 目标对象的位置和速度用于在后方交通交通避免(RCTA)系统中触发警告或自动制动。

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