-
公开(公告)号：US12007778B2
公开(公告)日：2024-06-11
申请号：US18094363
申请日：2023-01-08
Applicant: TuSimple, Inc.
CPC classification number: G05D1/0221 , G05D1/0088 , G05D1/0274 , G05D1/0285 , G06N3/00
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.
-
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.
-
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.
Inventor： Aaron Havens , Jun Chen , Yujia Wu , Haoming Sun , Zijie Xuan , Arda Kurt
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：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.
-
Patent Agency Ranking
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
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：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.
-
公开(公告)号：US20220291687A1
公开(公告)日：2022-09-15
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
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：US11372403B2
公开(公告)日：2022-06-28
申请号：US16181110
申请日：2018-11-05
Applicant: TuSimple, Inc.
Inventor： Aaron Havens , Jun Chen , Yujia Wu , Haoming Sun , Zijie Xuan , Arda Kurt
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：US11029693B2
公开(公告)日：2021-06-08
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.
-
-
-
-
-
-
-
-
Search Results
9
records
(took 0.014 seconds)
