ROAD FRICTION ESTIMATION TECHNIQUES

    公开(公告)号:US20210086777A1

    公开(公告)日:2021-03-25

    申请号:US17022875

    申请日:2020-09-16

    Applicant: TUSIMPLE, INC.

    Abstract: Techniques are described for estimating road friction between a road and tires of a vehicle. A method includes receiving, from a temperature sensor on a vehicle, a temperature value that indicates a temperature of an environment in which a vehicle is operated, determining a first range of friction values that quantify a friction between a road and tires of a vehicle based on a function of the temperature value and an extent of precipitation in a region that indicate a hazardous driving condition, obtaining, from the first range of friction values, a value that quantifies the friction between the road and the tires of the vehicle, where the value is obtained based on a driving related behavior of the vehicle, and causing the vehicle to operate on the road based on the value obtained from the first range of friction values.

    SYSTEM AND METHOD FOR SEMANTIC SEGMENTATION USING HYBRID DILATED CONVOLUTION (HDC)

    公开(公告)号:US20200265244A1

    公开(公告)日:2020-08-20

    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 IMAGE LOCALIZATION BASED ON SEMANTIC SEGMENTATION

    公开(公告)号:US20200160067A1

    公开(公告)日:2020-05-21

    申请号:US16752632

    申请日:2020-01-25

    Applicant: TuSimple, Inc.

    Abstract: A system and method for image localization based on semantic segmentation are disclosed. A particular embodiment includes: receiving image data from an image generating device mounted on an autonomous vehicle; performing semantic segmentation or other object detection on the received image data to identify and label objects in the image data and produce semantic label image data; identifying extraneous objects in the semantic label image data; removing the extraneous objects from the semantic label image data; comparing the semantic label image data to a baseline semantic label map; and determining a vehicle location of the autonomous vehicle based on information in a matching baseline semantic label map.

    SYSTEM AND METHOD FOR ACTIVELY SELECTING AND LABELING IMAGES FOR SEMANTIC SEGMENTATION

    公开(公告)号:US20180365835A1

    公开(公告)日:2018-12-20

    申请号:US15623323

    申请日:2017-06-14

    Applicant: TuSimple

    Abstract: A system and method for actively selecting and labeling images for semantic segmentation are disclosed. A particular embodiment includes: receiving image data from an image generating device; performing semantic segmentation or other object detection on the received image data to identify and label objects in the image data and produce semantic label image data; determining the quality of the semantic label image data based on prediction probabilities associated with regions or portions of the image; and identifying a region or portion of the image for manual labeling if an associated prediction probability is below a pre-determined threshold.

    OPERATIONAL TESTING OF AUTONOMOUS VEHICLES

    公开(公告)号:US20240427322A1

    公开(公告)日:2024-12-26

    申请号:US18824389

    申请日:2024-09-04

    Applicant: TUSIMPLE, INC.

    Abstract: Disclosed are devices, systems and methods for the operational testing on autonomous vehicles. One exemplary method includes configuring a primary vehicular model with an algorithm, calculating one or more trajectories for each of one or more secondary vehicular models that exclude the algorithm, configuring the one or more secondary vehicular models with a corresponding trajectory of the one or more trajectories, generating an updated algorithm based on running a simulation of the primary vehicular model interacting with the one or more secondary vehicular models that conform to the corresponding trajectory in the simulation, and integrating the updated algorithm into an algorithmic unit of the autonomous vehicle.

    OPERATIONAL TESTING OF AUTONOMOUS VEHICLES
    39.
    发明公开

    公开(公告)号:US20230350399A1

    公开(公告)日:2023-11-02

    申请号:US18350691

    申请日:2023-07-11

    Applicant: TUSIMPLE, INC.

    CPC classification number: G05B23/0254 G05D1/0088

    Abstract: Disclosed are devices, systems and methods for the operational testing on autonomous vehicles. One exemplary method includes configuring a primary vehicular model with an algorithm, calculating one or more trajectories for each of one or more secondary vehicular models that exclude the algorithm, configuring the one or more secondary vehicular models with a corresponding trajectory of the one or more trajectories, generating an updated algorithm based on running a simulation of the primary vehicular model interacting with the one or more secondary vehicular models that conform to the corresponding trajectory in the simulation, and integrating the updated algorithm into an algorithmic unit of the autonomous vehicle.

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