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公开(公告)号：US20240125610A1
公开(公告)日：2024-04-18
申请号：US18545801
申请日：2023-12-19
Applicant: TUSIMPLE, INC.
Inventor： Mingdong WANG , Chenzhe QIAN , Xue MEI
CPC classification number: G01C21/3602 , G01C21/32 , G01S13/89
Abstract: Various embodiments of the present disclosure provide a system and method for lane marking localization that may be utilized by autonomous or semi-autonomous vehicles traveling within the lane. In the embodiment, the system comprises a locating device adapted to determine the vehicle's geographic location; a database; a region map; a response map; a camera; and a computer connected to the locating device, database, and camera, wherein the computer is adapted to: receive the region map, wherein the region map corresponds to a specified geographic location; generate the response map by receiving information form the camera, the information relating to the environment in which the vehicle is located; identifying lane markers observed by the camera; and plotting identified lane markers on the response map; compare the response map to the region map; and generate a predicted vehicle location based on the comparison of the response map and region map.
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Patent Agency Ranking
公开(公告)号：US20230356734A1
公开(公告)日：2023-11-09
申请号：US18349783
申请日：2023-07-10
Applicant: TUSIMPLE, INC.
Inventor： Shane David GRIFFITH , Chenghao GONG , Chenzhe QIAN
CPC classification number: B60W50/06 , G06T7/85 , G01S19/42 , B60W60/001 , G06V20/588 , B60W2552/53 , G06T2207/30256 , B60W2420/42
Abstract: Techniques for performing a sensor calibration using sequential data is disclosed. An example method includes receiving, from a first camera located on a vehicle, a first image comprising at least a portion of a road comprising lane markers, where the first image is obtained by the camera at a first time; obtaining a calculated value of a position of an inertial measurement (IM) device at the first time; obtaining an optimized first extrinsic matrix of the first camera by adjusting a function of a first actual pixel location of a location of a lane marker in the first image and an expected pixel location of the location of the lane marker; and performing autonomous operation of the vehicle using the optimized first extrinsic matrix of the first camera when the vehicle is operated on another road or at another time.
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公开(公告)号：US20230266759A1
公开(公告)日：2023-08-24
申请号：US18167993
申请日：2023-02-13
Applicant: TuSimple, Inc.
Inventor： Xiaoling HAN , Chenzhe QIAN , Chiyu ZHANG , Charles A. PRICE , Joshua Miguel RODRIGUEZ , Lei NIE , Lingting GE , Panqu WANG , Pengfei CHEN , Shuhan YANG , Xiangchen ZHAO , Xiaodi HOU , Zehua HUANG
IPC: G05D1/00
CPC classification number: G05D1/0088 , G05D2201/0213
Abstract: A system installed in a vehicle includes a first group of sensing devices configured to allow a first level of autonomous operation of the vehicle; a second group of sensing devices configured to allow a second level of autonomous operation of the vehicle, the second group of sensing devices including primary sensing devices and backup sensing devices; a third group of sensing devices configured to allow the vehicle to perform a safe stop maneuver; and a control element communicatively coupled to the first group of sensing devices, the second group of sensing devices, and the third group of sensing devices. The control element is configured to: receive data from at least one of the first group, the second group, or the third group of sensing devices, and provide a control signal to a sensing device based on categorization information indicating a group to which the sensing device belongs.
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公开(公告)号：US20220227380A1
公开(公告)日：2022-07-21
申请号：US17150271
申请日：2021-01-15
Applicant: TUSIMPLE, INC.
Inventor： Shane David GRIFFITH , Chenghao GONG , Chenzhe QIAN
Abstract: Techniques for performing a sensor calibration using sequential data is disclosed. An example method includes receiving, from a first camera located on a vehicle, a first image comprising at least a portion of a road comprising lane markers, where the first image is obtained by the camera at a first time; obtaining a calculated value of a position of an inertial measurement (IM) device at the first time; obtaining an optimized first extrinsic matrix of the first camera by adjusting a function of a first actual pixel location of a location of a lane marker in the first image and an expected pixel location of the location of the lane marker; and performing autonomous operation of the vehicle using the optimized first extrinsic matrix of the first camera when the vehicle is operated on another road or at another time.
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公开(公告)号：US20210407130A1
公开(公告)日：2021-12-30
申请号：US16937508
申请日：2020-07-23
Applicant: TUSIMPLE, INC.
Inventor： Chenzhe QIAN , Ji ZHAO , Zhibei MA
Abstract: Techniques for performing multi-sensor calibration on a vehicle are described. A method includes obtaining, from each of at least two sensors located on a vehicle, sensor data item of a road comprising a lane marker, extracting, from each sensor data item, a location information of the lane marker, and calculating extrinsic parameters of the at least two sensors based on determining a difference between the location information of the lane marker from each sensor data item and a previously stored location information of the lane marker.
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公开(公告)号：US20210278232A1
公开(公告)日：2021-09-09
申请号：US17308803
申请日：2021-05-05
Applicant: TUSIMPLE, INC.
Inventor： Mingdong WANG , Chenzhe QIAN , Xue MEI
Abstract: Various embodiments of the present disclosure provide a system and method for lane marking localization that may be utilized by autonomous or semi-autonomous vehicles traveling within the lane. In the embodiment, the system comprises a locating device adapted to determine the vehicle's geographic location; a database; a region map; a response map; a camera; and a computer connected to the locating device, database, and camera, wherein the computer is adapted to: receive the region map, wherein the region map corresponds to a specified geographic location; generate the response map by receiving information form the camera, the information relating to the environment in which the vehicle is located; identifying lane markers observed by the camera; and plotting identified lane markers on the response map; compare the response map to the region map; and generate a predicted vehicle location based on the comparison of the response map and region map.
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