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：US20240004386A1

公开(公告)日：2024-01-04

申请号：US18469466

申请日：2023-09-18

Applicant: TuSimple, Inc.

Inventor： Aaron Havens ,  Jun Chen ,  Yujia Wu ,  Haoming Sun ,  Zijie Xuan ,  Arda Kurt

IPC: G05D1/00 ,  G06F17/11 ,  G05B19/4155 ,  G05D1/02

CPC classification number: G05D1/0088 ,  G06F17/11 ,  G05B19/4155 ,  G05D1/0212 ,  G05B2219/42033 ,  G05D2201/0213 ,  B60W10/20

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.

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：US11809193B2

公开(公告)日：2023-11-07

申请号：US16934989

申请日：2020-07-21

Applicant: TUSIMPLE, INC.

Inventor： Yujia Wu ,  Zijie Xuan ,  Arda Kurt

IPC: G05D1/02

CPC classification number: G05D1/0221 ,  G05D1/0219 ,  G05D1/0246

Abstract: Techniques are described to determine parameters and/or values for a control model that can be used to operate an autonomous vehicle, such as an autonomous semi-trailer truck. For example, a method of obtaining a data-driven model for autonomous driving may include obtaining data associated with a first set of variables that characterize movements of an autonomous vehicle over time and commands provided to the autonomous vehicle over time, determining, using at least the first set of data, non-zero values and an associated second set of variables that describe a control model used to perform an autonomous driving operation of the autonomous vehicle, and calculating values for a feedback controller that describes a transfer function used to perform the autonomous driving operation of the autonomous vehicle driven on a road.

公开(公告)号：US11809185B2

公开(公告)日：2023-11-07

申请号：US17805219

申请日：2022-06-02

Applicant: TuSimple, Inc.

Inventor： Aaron Havens ,  Jun Chen ,  Yujia Wu ,  Haoming Sun ,  Zijie Xuan ,  Arda Kurt

IPC: G05D1/00 ,  G06F17/11 ,  G05B19/4155 ,  G05D1/02 ,  B60W10/20 ,  B60W10/18 ,  B60W50/00

CPC classification number: G05D1/0088 ,  G05B19/4155 ,  G05D1/0212 ,  G06F17/11 ,  B60W10/18 ,  B60W10/20 ,  B60W50/00 ,  B60W2050/0011 ,  B60W2050/0028 ,  B60W2050/0083 ,  B60W2300/145 ,  B60W2400/00 ,  B60W2520/22 ,  B60W2530/10 ,  B60W2710/18 ,  B60W2710/20 ,  G05B2219/42033 ,  G05D2201/0213

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.

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.

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

IPC: G05D1/02 ,  G05D1/00 ,  G05B13/04 ,  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：US10752246B2

公开(公告)日：2020-08-25

申请号：US15806127

申请日：2017-11-07

Applicant: TuSimple, Inc.

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

IPC: B60W30/16 ,  B60W30/14

Abstract: A system and method for adaptive cruise control with proximate vehicle detection are disclosed. The example embodiment can be configured for: receiving input object data from a subsystem of a host vehicle, the input object data including distance data and velocity data relative to detected target vehicles; detecting the presence of any target vehicles within a sensitive zone in front of the host vehicle, to the left of the host vehicle, and to the right of the host vehicle; determining a relative speed and a separation distance between each of the detected target vehicles relative to the host vehicle; and generating a velocity command to adjust a speed of the host vehicle based on the relative speeds and separation distances between the host vehicle and the detected target vehicles to maintain a safe separation between the host vehicle and the target vehicles.

公开(公告)号：US12242274B2

公开(公告)日：2025-03-04

申请号：US18536635

申请日：2023-12-12

Applicant: TuSimple, Inc.

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

IPC: G05D1/00 ,  G05B13/04 ,  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：US12122419B2

公开(公告)日：2024-10-22

申请号：US16912444

申请日：2020-06-25

Applicant: TUSIMPLE, INC.

Inventor： Junbo Jing ,  Arda Kurt ,  Yujia Wu ,  Tianqu Shao ,  Xing Sun ,  Zijie Xuan ,  Haoming Sun ,  Chasen Sherman

IPC: B60W60/00 ,  G05D1/00 ,  H04W4/40

CPC classification number: B60W60/0011 ,  G05D1/0022 ,  G05D1/0274 ,  H04W4/40

Abstract: Described is a two-level optimal path planning process for autonomous tractor-trailer trucks which incorporates offline planning, online planning, and utilizing online estimation and perception results for adapting a planned path to real-world changes in the driving environment. In one aspect, a method of navigating an autonomous vehicle includes determining, by an online server, a current vehicle state of the autonomous vehicle in a mapped driving area. The method includes receiving, by the online server from an offline path library, a path for the autonomous driving vehicle through the mapped driving area from the current vehicle state to a destination vehicle state, and receiving fixed and moving obstacle information. The method includes adjusting the path to generate an optimized path that avoids the fixed and moving obstacles and ends at a targeted final vehicle state, and navigating the autonomous vehicle based on the optimized path.

公开(公告)号：US11366467B2

公开(公告)日：2022-06-21

申请号：US16862132

申请日：2020-04-29

Applicant: TUSIMPLE, INC.

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

IPC: G05D1/00 ,  G01C21/26 ,  B60W20/00 ,  B60R16/023 ,  G01C21/34

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.