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.

    Perception simulation for improved autonomous vehicle control

    公开(公告)号:US10481044B2

    公开(公告)日:2019-11-19

    申请号:US15598693

    申请日:2017-05-18

    Applicant: TuSimple

    Abstract: A system and method for real world autonomous vehicle perception simulation are disclosed. A particular embodiment includes: receiving perception data from a plurality of sensors of an autonomous vehicle; configuring the perception simulation operation based on a comparison of the perception data against ground truth data; generating simulated perception data by simulating errors related to the physical constraints of one or more of the 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.

    Large scale distributed simulation for realistic multiple-agent interactive environments

    公开(公告)号:US10474790B2

    公开(公告)日:2019-11-12

    申请号:US15612976

    申请日:2017-06-02

    Applicant: TuSimple

    Abstract: A system and method for large scale distributed simulation for realistic multiple-agent interactive environments are disclosed. A particular embodiment includes: generating a vicinal scenario for each simulated vehicle in an iteration of a simulation, the vicinal scenarios corresponding to different locations, traffic patterns, or environmental conditions being simulated; assigning a processing task to at least one of a plurality of distributed computing devices to generate vehicle trajectories for each of a plurality of simulated vehicles of the simulation based on the vicinal scenario; and updating a state and trajectory of each of the plurality of simulated vehicles based on processed data received from the plurality of distributed computing devices.

    Neural network based vehicle dynamics model

    公开(公告)号:US11550329B2

    公开(公告)日:2023-01-10

    申请号:US17147836

    申请日:2021-01-13

    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 real world autonomous vehicle trajectory simulation

    公开(公告)号:US11435748B2

    公开(公告)日:2022-09-06

    申请号:US16929954

    申请日:2020-07-15

    Applicant: TUSIMPLE, INC.

    Abstract: A system and method for real world autonomous vehicle trajectory simulation may include: receiving training data from a data collection system; obtaining ground truth data corresponding to the training data; performing a training phase to train a plurality of trajectory prediction models; and performing a simulation or operational phase to generate a vicinal scenario for each simulated vehicle in an iteration of a simulation. Vicinal scenarios may correspond to different locations, traffic patterns, or environmental conditions being simulated. Vehicle intention data corresponding to a data representation of various types of simulated vehicle or driver intentions.

    System and method for using human driving patterns to detect and correct abnormal driving behaviors of autonomous vehicles

    公开(公告)号:US11040710B2

    公开(公告)日:2021-06-22

    申请号:US16416244

    申请日:2019-05-19

    Applicant: TuSimple, Inc.

    Abstract: A system and method for using human driving patterns to detect and correct abnormal driving behaviors of autonomous vehicles are disclosed. A particular embodiment includes: generating data corresponding to a normal driving behavior safe zone; receiving a proposed vehicle control command; comparing the proposed vehicle control command with the normal driving behavior safe zone; and issuing a warning alert if the proposed vehicle control command is outside of the normal driving behavior safe zone. Another embodiment includes modifying the proposed vehicle control command to produce a modified and validated vehicle control command if the proposed vehicle control command is outside of the normal driving behavior safe zone.

Patent Agency Ranking