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公开(公告)号：US11500387B2
公开(公告)日：2022-11-15
申请号：US16991599
申请日：2020-08-12
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; dispatching the task request to the deep computing vehicle control subsystem or the fast response vehicle control subsystem based on the content of the task request or a context of the autonomous vehicle; 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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32.发明授权公开(公告)号：US11294375B2
公开(公告)日：2022-04-05
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：US10739775B2
公开(公告)日：2020-08-11
申请号：US15796765
申请日：2017-10-28
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 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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公开(公告)号：US10678234B2
公开(公告)日：2020-06-09
申请号：US15685715
申请日：2017-08-24
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.
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公开(公告)号：US09952594B1
公开(公告)日：2018-04-24
申请号：US15482038
申请日：2017-04-07
Applicant: TuSimple
Inventor： Yufei Zhao , Xiaodi Hou
CPC classification number: G05D1/0094 , B64C39/024 , B64C2201/12 , B64C2201/127 , B64C2201/141 , B64D47/08 , G06K9/00651 , G06K2209/23 , G08G1/012 , G08G1/0129
Abstract: A system and method for traffic data collection using unmanned aerial vehicles (UAVs) are disclosed. A particular embodiment is configured to: deploy an unmanned aerial vehicle (UAV), equipped with a camera, to an elevated position at a monitored location or to track a specific target vehicle; capture video data of the monitored location or the target vehicle for a pre-determined period of time using the UAV camera; transfer the captured video data to a processing system; at the processing system, process the captured video data on a frame basis to identify vehicles or objects of interest for analysis; group the video data from multiple frames related to a particular vehicle or object of interest into a data group associated with the particular vehicle or object; create a data group for each of the vehicles or objects of interest; and provide the data groups corresponding to each of the vehicles or objects of interest as output data used to configure or train a human driver model for prediction or simulation of human driver behavior.
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Patent Agency Ranking
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
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：US12228472B2
公开(公告)日：2025-02-18
申请号：US18424318
申请日：2024-01-26
Applicant: TuSimple, Inc.
Inventor： Xing Sun , Wutu Lin , Yufei Zhao , Liu Liu
Abstract: A system and method for real world autonomous vehicle perception simulation are disclosed. A particular embodiment includes: configuring a sensor noise modeling module to produce simulated sensor errors or noise data with a configured degree, extent, and timing of simulated sensor errors or noise based on a set of modifiable parameters; using the simulated sensor errors or noise data to generate simulated perception data by simulating errors related to constraints of one or more of a plurality of sensors, and by simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors; and providing the simulated perception data to a motion planning system for the autonomous vehicle.
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公开(公告)号：US12227206B2
公开(公告)日：2025-02-18
申请号：US17965893
申请日：2022-10-14
Applicant: TuSimple, Inc.
Inventor： Scott Douglas Foster , Dishi Li , Hunter Scott Willoughby , Yufei Zhao
IPC: B60W60/00 , B60W30/18 , B60W40/02 , B60W50/00 , B60W50/14 , G01S17/08 , G01S17/58 , G01S17/89 , G01S17/931 , G06F18/2413
Abstract: An autonomous vehicle (AV) includes features that allows the AV to comply with applicable regulations and statutes for performing safe driving operation. An example method includes detecting that a group of motorcycles is operating on a roadway on which the AV is located. The group of motorcycles are each located within a pre-determined distance away from one another. The method further includes determining an aggregate footprint area that surrounds respective locations of the group of motorcycles. The method further includes causing navigation of the autonomous vehicle that avoids penetration of the aggregate footprint area based on transmitting navigation instructions to one or more subsystems of the autonomous vehicle.
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公开(公告)号：US20230139551A1
公开(公告)日：2023-05-04
申请号：US18048882
申请日：2022-10-24
Applicant: TuSimple, Inc.
Inventor： Yufei Zhao , Tianqu Shao , Yujia Wu , Lei Wang
IPC: B60W30/095 , B60W60/00
Abstract: A system for implementing a lane bias maneuver to avoid a vehicle comprises an autonomous vehicle and a control device associated with the autonomous vehicle. The control device detects a presence of a vehicle from sensor data revied from sensors of the autonomous vehicle. The control device determines a lateral distance between the autonomous vehicle and the vehicle. The control device compares the lateral distance with a threshold distance. The control device determines whether to instruct the autonomous vehicle to perform a lane bias maneuver based on the comparison between the lateral distance and the threshold distance. The lane bias maneuver comprises driving the autonomous vehicle off-center in a current lane traveled by the autonomous vehicle toward an opposite direction with respect to the vehicle until the lateral distance between the autonomous vehicle and the vehicle is at least equal to the threshold distance.
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公开(公告)号：US20230093772A9
公开(公告)日：2023-03-23
申请号：US16987175
申请日：2020-08-06
Applicant: TuSimple, Inc.
Inventor： Yufei Zhao , Fan Mo , Xuren Zhou
Abstract: Systems and methods for autonomous lane level navigation are disclosed. In one aspect, a control system for an autonomous vehicle includes a processor and a computer-readable memory configured to cause the processor to receive a partial high-definition (HD) map that defines a plurality of lane segments that together represent one or more lanes of a roadway, the partial HD map including at least a current lane segment. The processor is also configured to generate auxiliary global information for each of the lane segments in the partial HD map. The processor is further configured to generate a subgraph including a plurality of possible routes between the current lane segment and the destination lane segment using the partial HD map and the auxiliary global information, select one of the possible routes for navigation based on the auxiliary global information, and generate lane level navigation information based on the selected route.
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