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公开(公告)号：US20240034341A1
公开(公告)日：2024-02-01
申请号：US18355678
申请日：2023-07-20
Applicant: TUSIMPLE, INC.
Inventor： Shen QU , Liu LIU , Junbo JING , Haoming SUN
CPC classification number: B60W50/06 , G07C5/02 , B60W60/00 , G05B17/02 , B60W2520/16 , B60W2520/18 , B60W2520/14 , B60W2552/15 , B60W2520/105 , B60W2520/125 , B60W2050/0056
Abstract: Vehicle dynamics related parameter(s) of an autonomous vehicle model can be calibrated so that the autonomous vehicle model can more accurately determine the driving related behaviors of the autonomous vehicle. An example method comprises obtaining, from sensor data, vehicle related parameters; performing a first determination of a slope of a road and a banking angle of the road based on a pitch angle of the vehicle and a roll angle of the vehicle, respectively; performing a second determination of a set of parameters that describe a driving-related operation of the vehicle; performing a third determination that at least one difference between at least one value from the set of parameters and a corresponding parameter from the plurality of vehicle related parameters exceeds at least one threshold value; and obtaining, in response to the third determination, a calibrated longitudinal dynamic-related parameter or a calibrated lateral dynamic-related parameter.
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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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公开(公告)号：US20220242425A1
公开(公告)日：2022-08-04
申请号：US17722110
申请日：2022-04-15
Applicant: TUSIMPLE, INC.
Inventor： Lindong SUN , Liu LIU , Xiaoling HAN , Yi WANG , Ruiliang ZHANG
Abstract: Disclosed are devices, systems and methods for a monitoring system for autonomous vehicle operation. In some embodiments, a vehicle may perform self-tests, generate a report based on the results, and transmit it to a remote monitor center over one or both of a high-speed channel for regular data transfers or a reliable channel for emergency situations. In other embodiments, the remote monitor center may determine that immediate intervention is required, and may transmit a control command with high priority, which when received by the vehicle, is implemented and overrides any local commands being processed. In yet other embodiments, the control command with high priority is selected from a small group of predetermined control commands the remote monitor center may issue.
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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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45.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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Patent Agency Ranking
公开(公告)号：US20200086884A1
公开(公告)日：2020-03-19
申请号：US16569640
申请日：2019-09-12
Applicant: TuSimple
Inventor： Yi WANG , Lindong SUN , Liu LIU , Xiaoling HAN , Ruiliang ZHANG
Abstract: Disclosed are devices, systems and methods for remote safe driving. One exemplary method includes detecting an emergency situation, and in response to the detecting the emergency situation, switching operation of the vehicle to a low-power operation mode that comprises shutting down a subset of vehicular components, and periodically transmitting a location of the vehicle to a remote monitoring center. Another exemplary method includes selecting at least one of a set of vehicular driving actions, and transmitting, over a secure connection, the at least one of the set of vehicular driving actions to the vehicle, wherein the set of vehicular driving actions is generated based on a classification of driver behavior.
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47.发明申请公开(公告)号：US20190270445A1
公开(公告)日：2019-09-05
申请号：US16416244
申请日：2019-05-19
Applicant: TuSimple
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 proposed vehicle control command; comparing the proposed vehicle control command with the normal driving behavior safe zone; and issuing a warning alert if the proposed vehicle control command is outside of the normal driving behavior safe zone. Another embodiment includes modifying the proposed vehicle control command to produce a modified and validated vehicle control command if the proposed vehicle control command is outside of the normal driving behavior safe zone.
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公开(公告)号：US20190210613A1
公开(公告)日：2019-07-11
申请号：US16245621
申请日：2019-01-11
Applicant: TuSimple
Inventor： Lindong SUN , Liu LIU , Xiaoling HAN , Yi WANG , Ruiliang ZHANG
CPC classification number: B60W50/0205 , G05D1/0011 , G05D1/0055 , G05D1/0088 , G05D2201/0213 , G07C5/008 , G07C5/0808
Abstract: Disclosed are devices, systems and methods for a monitoring system for autonomous vehicle operation. In some embodiments, a vehicle may perform self-tests, generate a report based on the results, and transmit it to a remote monitor center over one or both of a high-speed channel for regular data transfers or a reliable channel for emergency situations. In other embodiments, the remote monitor center may determine that immediate intervention is required, and may transmit a control command with high priority, which when received by the vehicle, is implemented and overrides any local commands being processed. In yet other embodiments, the control command with high priority is selected from a small group of predetermined control commands the remote monitor center may issue.
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公开(公告)号：US20190164007A1
公开(公告)日：2019-05-30
申请号：US16120247
申请日：2018-09-01
Applicant: TuSimple
Inventor： Liu LIU , Yiqian GAN
Abstract: A human driving behavior modeling system using machine learning is disclosed. A particular embodiment can be configured to: obtain training image data from a plurality of real world image sources and perform object extraction on the training image data to detect a plurality of vehicle objects in the training image data; categorize the detected plurality of vehicle objects into behavior categories based on vehicle objects performing similar maneuvers at similar locations of interest; train a machine learning module to model particular human driving behaviors based on use of the training image data from one or more corresponding behavior categories; and generate a plurality of simulated dynamic vehicles that each model one or more of the particular human driving behaviors trained into the machine learning module based on the training image data.
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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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