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.

Inventor： Xing Sun ,  Wutu Lin ,  Yufei Zhao ,  Liu Liu

IPC: G01M17/00 ,  B60W30/00

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.

公开(公告)号：US11853071B2

公开(公告)日：2023-12-26

申请号：US16848809

申请日：2020-04-14

Applicant: TUSIMPLE, INC.

Inventor： Xing Sun ,  Wutu Lin ,  Liu Liu ,  Kai-Chieh Ma ,  Zijie Xuan ,  Yufei Zhao

IPC: G05D1/02 ,  G05D1/00 ,  B62D15/02

CPC classification number: G05D1/0221 ,  B62D15/026 ,  B62D15/0255 ,  B62D15/0265 ,  G05D1/0088

Abstract: A data-driven prediction-based system and method for trajectory planning of autonomous vehicles are disclosed. A particular embodiment includes: generating a first suggested trajectory for an autonomous vehicle; generating predicted resulting trajectories of proximate agents using a prediction module; scoring the first suggested trajectory based on the predicted resulting trajectories of the proximate agents; generating a second suggested trajectory for the autonomous vehicle and generating corresponding predicted resulting trajectories of proximate agents, if the score of the first suggested trajectory is below a minimum acceptable threshold; and outputting a suggested trajectory for the autonomous vehicle wherein the score corresponding to the suggested trajectory is at or above the minimum acceptable threshold.

公开(公告)号：US11292480B2

公开(公告)日：2022-04-05

申请号：US16569640

申请日：2019-09-12

Applicant: TuSimple, Inc.

Inventor： Yi Wang ,  Lindong Sun ,  Liu Liu ,  Xiaoling Han ,  Ruiliang Zhang

IPC: B60W50/02 ,  B60W30/08 ,  B60W30/18 ,  G05D1/00 ,  G07C5/08

Abstract: Disclosed are devices, systems and methods for remote safe driving. One exemplary method includes detecting an emergency situation, and in response to the detecting the emergency situation, switching operation of the vehicle to a low-power operation mode that comprises shutting down a subset of vehicular components, and periodically transmitting a location of the vehicle to a remote monitoring center. Another exemplary method includes selecting at least one of a set of vehicular driving actions, and transmitting, over a secure connection, the at least one of the set of vehicular driving actions to the vehicle, wherein the set of vehicular driving actions is generated based on a classification of driver behavior.

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.

Inventor： Xiaomin Zhang ,  Yilun Chen ,  Guangyu Li ,  Xing Sun ,  Wutu Lin ,  Liu Liu ,  Kai-Chieh Ma ,  Zijie Xuan ,  Yufei Zhao

IPC: G05D1/02 ,  G05D1/00 ,  G08G1/16

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.

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.

Inventor： Wutu Lin ,  Liu Liu ,  Xing Sun ,  Kai-Chieh Ma ,  Zijie Xuan ,  Yufei Zhao

IPC: G05D1/00 ,  B60W40/09

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.

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

Inventor： Xing Sun ,  Wutu Lin ,  Yufei Zhao ,  Liu Liu

IPC: G05D1/00 ,  G01M17/00 ,  B60W30/00

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.

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

Inventor： Xing Sun ,  Wutu Lin ,  Yufei Zhao ,  Liu Liu

IPC: G06F17/50 ,  G06N5/04

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.

公开(公告)号：US20190196468A1

公开(公告)日：2019-06-27

申请号：US15853496

申请日：2017-12-22

Applicant: TuSimple

Inventor： Liu Liu ,  Che Kun Law ,  Ke Quan

IPC: G05D1/00 ,  G01C21/36 ,  G05D1/02 ,  G06T17/05

CPC classification number: G05D1/0088 ,  G01C21/3635 ,  G05D1/0212 ,  G05D2201/0212 ,  G05D2201/0213 ,  G06T17/05

Abstract: A Method and System for Modeling Autonomous Vehicle Behavior. The system and method makes it feasible to develop an autonomous vehicle control system for complex vehicles, such as for cargo trucks and other large payload vehicles. The method and system commences by first obtaining 3-dimensional data for one or more sections of roadway. Once the 3-dimensional roadway data is obtained, that data is used to run computer simulations of a computer model of a specific vehicle being controlled by a generic vehicle control algorithm or system. The generic vehicle control algorithm is optimized by running the simulations utilizing the 3-dimensional roadway data until an acceptable performance result is acheived. Once an acceptable simulation is executed using the generic vehicle control algorithm, the control algorithm/system is used to run one or more real-world driving tests on the roadway for which the 3-dimensional data was obtained. Finally, the computer model for the vehicle is modified, if necessary (without modifying the control algorithm), until the real-world driving performance is acceptable.

公开(公告)号：US11853072B2

公开(公告)日：2023-12-26

申请号：US17901736

申请日：2022-09-01

Applicant: TuSimple, Inc.

Inventor： Xing Sun ,  Wutu Lin ,  Liu Liu ,  Kai-Chieh Ma ,  Zijie Xuan ,  Yufei Zhao

IPC: G05D1/02 ,  G05D1/00 ,  G05B13/04 ,  G06N20/00

CPC classification number: G05D1/0221 ,  G05B13/048 ,  G05D1/0088 ,  G06N20/00

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.

公开(公告)号：US11782440B2

公开(公告)日：2023-10-10

申请号：US17126740

申请日：2020-12-18

Applicant: TUSIMPLE, INC.

Inventor： Liu Liu ,  Yuwei Wang ,  Xing Sun ,  Yufei Zhao ,  Wutu Lin

IPC: G05D1/00 ,  G05D1/02 ,  G06F30/15 ,  G06F30/20 ,  G06F111/10

CPC classification number: G05D1/0088 ,  G05D1/0212 ,  G05D1/0287 ,  G06F30/15 ,  G06F30/20 ,  G05D2201/0213 ,  G06F2111/10

Abstract: An autonomous vehicle simulation system for analyzing motion planners is disclosed. A particular embodiment includes: receiving map data corresponding to a real world driving environment; obtaining perception data and configuration data including pre-defined parameters and executables defining a specific driving behavior for each of a plurality of simulated dynamic vehicles; generating simulated perception data for each of the plurality of simulated dynamic vehicles based on the map data, the perception data, and the configuration data; receiving vehicle control messages from an autonomous vehicle control system; and simulating the operation and behavior of areal world autonomous vehicle based on the vehicle control messages received from the autonomous vehicle control system.