SYSTEM AND METHOD FOR PROVIDING MULTIPLE AGENTS FOR DECISION MAKING, TRAJECTORY PLANNING, AND CONTROL FOR AUTONOMOUS VEHICLES

    公开(公告)号:US20200371521A1

    公开(公告)日:2020-11-26

    申请号:US16991599

    申请日:2020-08-12

    Applicant: TUSIMPLE, INC.

    Abstract: A system and method for providing multiple agents for decision making, trajectory planning, and control for autonomous vehicles are disclosed. A particular embodiment includes: partitioning a multiple agent autonomous vehicle control module for an autonomous vehicle into a plurality of subsystem agents, the plurality of subsystem agents including a deep computing vehicle control subsystem and a fast response vehicle control subsystem; receiving a task request from a vehicle subsystem; dispatching the task request to the deep computing vehicle control subsystem or the fast response vehicle control subsystem based on the content of the task request or a context of the autonomous vehicle; causing execution of the deep computing vehicle control subsystem or the fast response vehicle control subsystem by use of a data processor to produce a vehicle control output; and providing the vehicle control output to a vehicle control subsystem of the autonomous vehicle.

    Systems and methods for dynamic predictive control of autonomous vehicles

    公开(公告)号:US12164297B2

    公开(公告)日:2024-12-10

    申请号:US18469466

    申请日:2023-09-18

    Applicant: TuSimple, Inc.

    Abstract: Systems and methods for dynamic predictive control of autonomous vehicles are disclosed. In one aspect, an in-vehicle control system for a semi-truck includes one or more control mechanisms configured to control movement of the semi-truck and a processor. The system further includes computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the processor to receive a desired trajectory and a vehicle status of the semi-truck, determine a dynamic model of the semi-truck based on the desired trajectory and the vehicle status, determine at least one quadratic program (QP) problem based on the dynamic model, generate at least one control command for controlling the semi-truck by solving the at least one QP problem, and provide the at least one control command to the one or more control mechanisms.

    System and method for autonomous vehicle control to minimize energy cost

    公开(公告)号:US11886183B2

    公开(公告)日:2024-01-30

    申请号:US17807709

    申请日:2022-06-17

    Applicant: TUSIMPLE, INC.

    CPC classification number: G05D1/0005 B60R16/0236 G01C21/3469 G05D1/0088

    Abstract: A system and method for autonomous vehicle control to minimize energy cost are disclosed. A particular embodiment includes: generating a plurality of potential routings and related vehicle motion control operations for an autonomous vehicle to cause the autonomous vehicle to transit from a current position to a desired destination; generating predicted energy consumption rates for each of the potential routings and related vehicle motion control operations using a vehicle energy consumption model; scoring each of the plurality of potential routings and related vehicle motion control operations based on the corresponding predicted energy consumption rates; selecting one of the plurality of potential routings and related vehicle motion control operations having a score within an acceptable range; and outputting a vehicle motion control output representing the selected one of the plurality of potential routings and related vehicle motion control operations.

    Prediction-based system and method for trajectory planning of autonomous vehicles

    公开(公告)号:US10782694B2

    公开(公告)日:2020-09-22

    申请号:US15806013

    申请日:2017-11-07

    Applicant: TuSimple, Inc.

    Abstract: A prediction-based system and method for trajectory planning of autonomous vehicles are disclosed. A particular embodiment is configured to: receive training data and ground truth data from a training data collection system, the training data including perception data and context data corresponding to human driving behaviors; perform a training phase for training a trajectory prediction module using the training data; receive perception data associated with a host vehicle; and perform an operational phase for extracting host vehicle feature data and proximate vehicle context data from the perception data, generating a proposed trajectory for the host vehicle, using the trained trajectory prediction module to generate predicted trajectories for each of one or more proximate vehicles near the host vehicle based on the proposed host vehicle trajectory, determining if the proposed trajectory for the host vehicle will conflict with any of the predicted trajectories of the proximate vehicles, and modifying the proposed trajectory for the host vehicle until conflicts are eliminated.

    System and method for using human driving patterns to manage speed control for autonomous vehicles

    公开(公告)号:US10656644B2

    公开(公告)日:2020-05-19

    申请号:US15698375

    申请日:2017-09-07

    Applicant: TuSimple, Inc.

    Abstract: A system and method for using human driving patterns to manage speed control for autonomous vehicles are disclosed. A particular embodiment includes: generating data corresponding to desired human driving behaviors; training a human driving model module using a reinforcement learning process and the desired human driving behaviors; receiving a proposed vehicle speed control command; determining if the proposed vehicle speed control command conforms to the desired human driving behaviors by use of the human driving model module; and validating or modifying the proposed vehicle speed control command based on the determination.

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