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11.发明公开公开(公告)号：US20240288868A1
公开(公告)日：2024-08-29
申请号：US18507038
申请日：2023-11-11
Applicant: TUSIMPLE, INC.
Inventor： Xing SUN , Wutu LIN , Liu LIU , Kai-Chieh MA , Zijie XUAN , Yufei ZHAO
CPC classification number: G05D1/0221 , B62D15/0255 , B62D15/026 , B62D15/0265
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.
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12.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：US20190071093A1
公开(公告)日：2019-03-07
申请号：US15946195
申请日：2018-04-05
Applicant: TuSimple
Inventor： Kai-Chieh MA , Xing SUN
Abstract: A system and method for automated lane change control for autonomous vehicles are disclosed. A particular embodiment is configured to: receive perception data associated with a host vehicle; use the perception data to determine a state of the host vehicle and a state of proximate vehicles detected near to the host vehicle; determine a first target position within a safety zone between proximate vehicles detected in a roadway lane adjacent to a lane in which the host vehicle is positioned; determine a second target position in the lane in which the host vehicle is positioned; and generate a lane change trajectory to direct the host vehicle toward the first target position in the adjacent lane after directing the host vehicle toward the second target position in the lane in which the host vehicle is positioned.
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Patent Agency Ranking
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：US20200257281A1
公开(公告)日：2020-08-13
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 , G01C21/34 , 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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18.发明申请公开(公告)号：US20200241533A1
公开(公告)日：2020-07-30
申请号：US16849916
申请日：2020-04-15
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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公开(公告)号：US20190129436A1
公开(公告)日：2019-05-02
申请号：US15796765
申请日：2017-10-28
Applicant: TuSimple
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 are disclosed. A particular embodiment includes: receiving training data from a real world 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, the vicinal scenarios corresponding to different locations, traffic patterns, or environmental conditions being simulated, provide vehicle intention data corresponding to a data representation of various types of simulated vehicle or driver intentions, generate a trajectory corresponding to perception data and the vehicle intention data, execute at least one of the plurality of trained trajectory prediction models to generate a distribution of predicted vehicle trajectories for each of a plurality of simulated vehicles of the simulation based on the vicinal scenario and the vehicle intention data, select at least one vehicle trajectory from the distribution based on pre-defined criteria, and update a state and trajectory of each of the plurality of simulated vehicles based on the selected vehicle trajectory from the distribution.
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20.发明申请公开(公告)号：US20190072973A1
公开(公告)日：2019-03-07
申请号：US15698607
申请日：2017-09-07
Applicant: TuSimple
Inventor： Xing SUN , Wutu LIN , Liu LIU , Kai-Chieh MA , Zijie XUAN , Yufei ZHAO
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.
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