System and method for autonomous vehicle control to minimize energy cost

    公开(公告)号:US12253850B2

    公开(公告)日:2025-03-18

    申请号:US18510352

    申请日:2023-11-15

    Applicant: TUSIMPLE, INC.

    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.

    Neural network based vehicle dynamics model

    公开(公告)号:US10895877B2

    公开(公告)日:2021-01-19

    申请号:US15672207

    申请日:2017-08-08

    Applicant: TuSimple, Inc.

    Abstract: A system and method for implementing a neural network based vehicle dynamics model are disclosed. A particular embodiment includes: training a machine learning system with a training dataset corresponding to a desired autonomous vehicle simulation environment; receiving vehicle control command data and vehicle status data, the vehicle control command data not including vehicle component types or characteristics of a specific vehicle; by use of the trained machine learning system, the vehicle control command data, and vehicle status data, generating simulated vehicle dynamics data including predicted vehicle acceleration data; providing the simulated vehicle dynamics data to an autonomous vehicle simulation system implementing the autonomous vehicle simulation environment; and using data produced by the autonomous vehicle simulation system to modify the vehicle status data for a subsequent iteration.

    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.

    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.

    Perception simulation for improved autonomous vehicle control

    公开(公告)号:US11885712B2

    公开(公告)日:2024-01-30

    申请号:US17093172

    申请日:2020-11-09

    Applicant: TuSimple, Inc.

    CPC classification number: G01M17/00 B60W30/00

    Abstract: A system and method for real world autonomous vehicle perception simulation are disclosed. A particular embodiment includes: configuring a sensor noise modeling module to produce simulated sensor errors or noise data with a configured degree, extent, and timing of simulated sensor errors or noise based on a set of modifiable parameters; using the simulated sensor errors or noise data to generate simulated perception data by simulating errors related to constraints of one or more of a plurality of sensors, and by simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors; and providing the simulated perception data to a motion planning system for the autonomous vehicle.

    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 path planning of autonomous vehicles based on gradient

    公开(公告)号:US10710592B2

    公开(公告)日:2020-07-14

    申请号:US15481877

    申请日:2017-04-07

    Applicant: TuSimple, Inc.

    Inventor: Wutu Lin Xiaodi Hou

    Abstract: A system and method for path planning of autonomous vehicles based on gradient are disclosed. A particular embodiment includes: generating and scoring a first suggested trajectory for an autonomous vehicle; generating a trajectory gradient based on the first suggested trajectory; generating and scoring a second suggested trajectory for the autonomous vehicle, the second suggested trajectory being based on the first suggested trajectory and a human driving model; and outputting the second suggested trajectory if the score corresponding to the second suggested trajectory is within a score differential threshold relative to the score corresponding to the first suggested trajectory.

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