ADAPTIVE ILLUMINATION SYSTEM FOR AN AUTONOMOUS VEHICLE

    公开(公告)号:US20230219488A1

    公开(公告)日:2023-07-13

    申请号:US18149901

    申请日:2023-01-04

    Applicant: TuSimple, Inc.

    CPC classification number: B60Q1/143 B60Q2300/054 B60Q2300/42 G06V20/58

    Abstract: A system comprises a headlight mounted on an autonomous vehicle. The headlight is configured to illuminate at least a portion of a road the autonomous vehicle is on. The system further comprises a control device associated with the autonomous vehicle. The processor obtains information about an environment around the autonomous vehicle. The processor determines that at least a portion of the road should be illuminated if the information indicates that an illumination level of the portion of the road is less than a threshold illumination level. The processor adjusts the headlight to illuminate at least the portion of the road in response to determining that at least the portion of the road should be illuminated.

    System and method for determining car to lane distance

    公开(公告)号:US11227500B2

    公开(公告)日:2022-01-18

    申请号:US16781907

    申请日:2020-02-04

    Applicant: TuSimple, Inc.

    Inventor: Panqu Wang

    Abstract: A system and method for determining car to lane distance is provided. In one aspect, the system includes a camera configured to generate an image, a processor, and a computer-readable memory. The processor is configured to receive the image from the camera, generate a wheel segmentation map representative of one or more wheels detected in the image, and generate a lane segmentation map representative of one or more lanes detected in the image. For at least one of the wheels in the wheel segmentation map, the processor is also configured to determine a distance between the wheel and at least one nearby lane in the lane segmentation map. The processor is further configured to determine a distance between a vehicle in the image and the lane based on the distance between the wheel and the lane.

    System and method for semantic segmentation using hybrid dilated convolution (HDC)

    公开(公告)号:US11010616B2

    公开(公告)日:2021-05-18

    申请号:US16867472

    申请日:2020-05-05

    Applicant: TUSIMPLE, INC.

    Abstract: A system and method for semantic segmentation using hybrid dilated convolution (HDC) are disclosed. A particular embodiment includes: receiving an input image; producing a feature map from the input image; performing a convolution operation on the feature map and producing multiple convolution layers; grouping the multiple convolution layers into a plurality of groups; applying different dilation rates for different convolution layers in a single group of the plurality of groups; and applying a same dilation rate setting across all groups of the plurality of groups.

    System and method for semantic segmentation using hybrid dilated convolution (HDC)

    公开(公告)号:US10679074B2

    公开(公告)日:2020-06-09

    申请号:US16209262

    申请日:2018-12-04

    Applicant: TuSimple, Inc.

    Abstract: A system and method for semantic segmentation using hybrid dilated convolution (HDC) are disclosed. A particular embodiment includes: receiving an input image; producing a feature map from the input image; performing a convolution operation on the feature map and producing multiple convolution layers; grouping the multiple convolution layers into a plurality of groups; applying different dilation rates for different convolution layers in a single group of the plurality of groups; and applying a same dilation rate setting across all groups of the plurality of groups.

    System and method for vehicle wheel detection

    公开(公告)号:US10671873B2

    公开(公告)日:2020-06-02

    申请号:US15917331

    申请日:2018-03-09

    Applicant: TuSimple, Inc.

    Abstract: A system and method for vehicle wheel detection is disclosed. A particular embodiment can be configured to: receive training image data from a training image data collection system; obtain ground truth data corresponding to the training image data; perform a training phase to train one or more classifiers for processing images of the training image data to detect vehicle wheel objects in the images of the training image data; receive operational image data from an image data collection system associated with an autonomous vehicle; and perform an operational phase including applying the trained one or more classifiers to extract vehicle wheel objects from the operational image data and produce vehicle wheel object data.

    System and method for three-dimensional (3D) object detection

    公开(公告)号:US12033396B2

    公开(公告)日:2024-07-09

    申请号:US18339961

    申请日:2023-06-22

    Applicant: TUSIMPLE, INC.

    Inventor: Panqu Wang

    CPC classification number: G06V20/58 G06F16/29 G06N20/00 G06T7/62 G06T7/80

    Abstract: A system and method for three-dimensional (3D) object detection is disclosed. A particular embodiment can be configured to: receive image data from a camera associated with a vehicle, the image data representing an image frame; use a machine learning module to determine at least one pixel coordinate of a two-dimensional (2D) bounding box around an object in the image frame; use the machine learning module to determine at least one vertex of a three-dimensional (3D) bounding box around the object; obtain camera calibration information associated with the camera; and determine 3D attributes of the object using the 3D bounding box and the camera calibration information.

    Adaptive illumination system for an autonomous vehicle

    公开(公告)号:US11865967B2

    公开(公告)日:2024-01-09

    申请号:US18149901

    申请日:2023-01-04

    Applicant: TuSimple, Inc.

    CPC classification number: B60Q1/143 B60Q2300/054 B60Q2300/42 G06V20/58

    Abstract: A system comprises a headlight mounted on an autonomous vehicle. The headlight is configured to illuminate at least a portion of a road the autonomous vehicle is on. The system further comprises a control device associated with the autonomous vehicle. The processor obtains information about an environment around the autonomous vehicle. The processor determines that at least a portion of the road should be illuminated if the information indicates that an illumination level of the portion of the road is less than a threshold illumination level. The processor adjusts the headlight to illuminate at least the portion of the road in response to determining that at least the portion of the road should be illuminated.

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