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公开(公告)号：US20250053171A1
公开(公告)日：2025-02-13
申请号：US18932073
申请日：2024-10-30
Applicant: TUSIMPLE, INC.
Inventor： Liu LIU , Yuwei WANG , Xing SUN , Yufei ZHAO , Wutu LIN
IPC: G05D1/00 , G06F30/15 , G06F30/20 , G06F111/10
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 a real world autonomous vehicle based on the vehicle control messages received from the autonomous vehicle control system.
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公开(公告)号：US20240353839A1
公开(公告)日：2024-10-24
申请号：US18662273
申请日：2024-05-13
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.
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公开(公告)号：US20240085900A1
公开(公告)日：2024-03-14
申请号：US18510352
申请日：2023-11-15
Applicant: TUSIMPLE, INC.
Inventor： Xing SUN , Wutu LIN , Liu LIU , Kai-Chieh MA , Zijie XUAN , Yufei ZHAO
IPC: G05D1/00 , B60R16/023 , G01C21/34
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.
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公开(公告)号：US20230373483A1
公开(公告)日：2023-11-23
申请号：US18228574
申请日：2023-07-31
Applicant: TUSIMPLE, INC.
Inventor： Wutu LIN , Liu LIU , Zijie Xuan , Xing SUN , Kai-Chieh MA , Yufei ZHAO
CPC classification number: B60W30/16 , B60W30/143 , B60W2420/52 , B60W2720/10 , B60W2520/10 , B60W2554/801 , B60W2554/804 , B60W2754/30
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.
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5.发明申请公开(公告)号：US20220197283A1
公开(公告)日：2022-06-23
申请号：US17654224
申请日：2022-03-09
Applicant: TuSimple, Inc.
Inventor： Wutu LIN , Liu LIU , Xing SUN , Kai-Chieh MA , Zijie XUAN , Yufei ZHAO
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.
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Patent Agency Ranking
6.发明公开公开(公告)号：US20240343247A1
公开(公告)日：2024-10-17
申请号：US18635642
申请日：2024-04-15
Applicant: TuSimple, Inc.
CPC classification number: B60W30/02 , G05D1/81 , G06N20/00 , B60W2540/30 , B60W2710/18 , B60W2710/20 , G06N3/08
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 compliant vehicle control command; comparing the compliant vehicle control command with the normal driving behavior safe zone; and issuing a warning alert if the compliant vehicle control command is outside of the normal driving behavior safe zone. Another embodiment includes modifying the compliant vehicle control command to produce a modified and validated vehicle control command if the compliant vehicle control command is outside of the normal driving behavior safe zone.
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公开(公告)号：US20240103523A1
公开(公告)日：2024-03-28
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
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.
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公开(公告)号：US20230063989A1
公开(公告)日：2023-03-02
申请号：US17983974
申请日：2022-11-09
Applicant: TuSimple, Inc.
Inventor： Xing SUN , Yufei ZHAO , Wutu LIN , Zijie XUAN , Liu LIU , Kai-Chieh MA
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; determining if the task request is appropriate for the deep computing vehicle control subsystem or the fast response vehicle control subsystem based on content of the task request or a context of the autonomous vehicle; dispatching the task request to the deep computing vehicle control subsystem or the fast response vehicle control subsystem based on the determination; 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.
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公开(公告)号：US20200298863A1
公开(公告)日：2020-09-24
申请号：US16900611
申请日：2020-06-12
Applicant: TUSIMPLE, INC.
Inventor： Wutu LIN , Xiaodi Hou
IPC: B60W40/04 , G01S13/931 , G01C21/20 , G05D1/02 , G05D1/00 , G01S17/931
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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公开(公告)号：US20230376037A1
公开(公告)日：2023-11-23
申请号：US18364587
申请日：2023-08-03
Applicant: TUSIMPLE, INC.
Inventor： Liu LIU , Yuwei WANG , Xing SUN , Yufei ZHAO , Wutu LIN
CPC classification number: G05D1/0088 , G05D1/0287 , G05D1/0212 , 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 a real world autonomous vehicle based on the vehicle control messages received from the autonomous vehicle control system.
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