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31.发明公开公开(公告)号：US20240255948A1
公开(公告)日：2024-08-01
申请号：US18631700
申请日：2024-04-10
Applicant: TuSimple, Inc.
Inventor： Wutu LIN , Liu LIU , Xing SUN , Kai-Chieh MA , Zijie XUAN , Yufei ZHAO
CPC classification number: G05D1/0088 , B60W40/09 , B60W2720/103
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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公开(公告)号：US20240168478A1
公开(公告)日：2024-05-23
申请号：US18431194
申请日：2024-02-02
Applicant: TuSimple, Inc.
Inventor： Xiaomin ZHANG , Yilun CHEN , Guangyu LI , Xing SUN , Wutu LIN , Liu LIU , Kai-Chieh MA , Zijie XUAN , Yufei ZHAO
Abstract: A prediction-based system and method for trajectory planning of autonomous vehicles is configured to: receive 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.
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公开(公告)号：US20230004165A1
公开(公告)日：2023-01-05
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
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：US20220242371A1
公开(公告)日：2022-08-04
申请号：US17660519
申请日：2022-04-25
Applicant: TUSIMPLE, INC.
Inventor： Xiaoling HAN , Charles A. PRICE , Lindong SUN , Liu LIU , Yi WANG , Ruiliang ZHANG
Abstract: Described are devices, systems and methods for real-time remote control of vehicles with high redundancy. In some embodiments, two copies of at least one control command are received using two different wireless communication protocols, and are compared. The at least one control command is executed when the two copies are in agreement, but is rejected when the two copies differ. In other embodiments, additional wireless communication protocols may exist to provide a redundant mode of communication when one of the two different wireless communication protocols are unavailable. In yet other embodiments, redundant GPS units may be used to determine availability of any of the communication protocols, and relevant control commands may be downloaded in advance to circumvent the lack of coverage.
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公开(公告)号：US20210103283A1
公开(公告)日：2021-04-08
申请号：US17126740
申请日：2020-12-18
Applicant: TUSIMPLE, INC.
Inventor： Liu LIU , Yuwei WANG , Xing SUN , Yufei Zhao , Wutu LIN
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.
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Patent Agency Ranking
公开(公告)号：US20210089032A1
公开(公告)日：2021-03-25
申请号：US17111984
申请日：2020-12-04
Applicant: TuSimple, Inc.
Inventor： Xingdong LI , Xing SUN , Wutu LIN , Liu LIU
Abstract: A system and method for generating simulated vehicles with configured behaviors for analyzing autonomous vehicle motion planners are disclosed. A particular embodiment includes: receiving perception data from a plurality of perception data sensors; obtaining configuration instructions and data including pre-defined parameters and executables defining a specific driving behavior for each of a plurality of simulated dynamic vehicles; generating a target position and target speed for each of the plurality of simulated dynamic vehicles, the generated target positions and target speeds being based on the perception data and the configuration instructions and data; and generating a plurality of trajectories and acceleration profiles to transition each of the plurality of simulated dynamic vehicles from a current position and speed to the corresponding target position and target speed.
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公开(公告)号：US20190064793A1
公开(公告)日：2019-02-28
申请号：US15685715
申请日：2017-08-24
Applicant: TuSimple
Inventor： Xing SUN , Wutu LIN , Liu LIU , Kai-Chieh MA , Zijie XUAN , Yufei ZHAO
IPC: G05D1/00 , B60R16/023
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：US20190049980A1
公开(公告)日：2019-02-14
申请号：US15672207
申请日：2017-08-08
Applicant: TuSimple
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：US20190001976A1
公开(公告)日：2019-01-03
申请号：US15640516
申请日：2017-07-01
Applicant: TuSimple
Abstract: A system and method for adaptive cruise control for low speed following are disclosed. A particular embodiment includes: receiving input object data from a subsystem of an autonomous vehicle, the input object data including distance data and velocity data relative to a lead vehicle; generating a weighted distance differential corresponding to a weighted difference between an actual distance between the autonomous vehicle and the lead vehicle and a desired distance between the autonomous vehicle and the lead vehicle; generating a weighted velocity differential corresponding to a weighted difference between a velocity of the autonomous vehicle and a velocity of the lead vehicle; combining the weighted distance differential and the weighted velocity differential with the velocity of the lead vehicle to produce a velocity command for the autonomous vehicle; adjusting the velocity command using a dynamic gain; and controlling the autonomous vehicle to conform to the adjusted velocity command.
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公开(公告)号：US20190001975A1
公开(公告)日：2019-01-03
申请号：US15640514
申请日：2017-07-01
Applicant: TuSimple
Abstract: A system and method for adaptive cruise control for defensive driving are disclosed. A particular embodiment includes: receiving input object data from a subsystem of an autonomous vehicle, the input object data including distance data and velocity data relative to a lead vehicle; generating a weighted distance differential corresponding to a weighted difference between an actual distance between the autonomous vehicle and the lead vehicle and a desired distance between the autonomous vehicle and the lead vehicle; generating a weighted velocity differential corresponding to a weighted difference between a velocity of the autonomous vehicle and a velocity of the lead vehicle; combining the weighted distance differential and the weighted velocity differential with the velocity of the lead vehicle to produce a velocity command for the autonomous vehicle; and controlling the autonomous vehicle to conform to the velocity command.
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