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公开(公告)号：US11829275B2
公开(公告)日：2023-11-28
申请号：US16570654
申请日：2019-09-13
申请人： TOYOTA RESEARCH INSTITUTE, INC. , THE BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY
IPC分类号： G06F11/34
CPC分类号： G06F11/3461
摘要： Systems and methods for generating and evaluating driving scenarios with varying difficulty levels is provided. The disclosed systems and methods may be used to develop a suite of regression tests that track the progress of an autonomous driving stack. A robustness trace of a temporal logic formula may be computed from an always-eventually fragment using a computation graph. The robustness trace may be approximated by a smoothly differentiable computation graph, which can be implemented in existing machine learning programming frameworks. The systems and methods provided herein may be useful in automatic test case generation for autonomous or semi-autonomous vehicles.
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公开(公告)号：US11256611B2
公开(公告)日：2022-02-22
申请号：US16425723
申请日：2019-05-29
摘要： A method for synthesizing parameters for control of a closed loop system based on a differentiable simulation model of the closed loop system includes determining requirements/specifications for the closed loop system in signal temporal logic (STL). The method also includes selecting a parametric control law having a differentiable parameter control function. The method also includes converting the requirements in signal temporal logic into differentiable computational graph. The method further includes building the differentiable simulation model as a differentiable computational graph. Furthermore, the method includes automatically learning values of parameters for the differentiable parameter control function of the closed loop system by backpropagating an error.
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3.发明公开公开(公告)号：US20230177114A1
公开(公告)日：2023-06-08
申请号：US17732647
申请日：2022-04-29
发明人： Nikos Arechiga Gonzalez , Rumen Iliev , Francine Chen , Yin-ying Chen , Kent Lyons , Yanxia Zhang , Heishiro Toyoda
CPC分类号： G06K9/6256 , G06N3/0481 , G06K9/00503
摘要： System, methods, and other embodiments described herein relate to a manner of determining an interpretable model from experimental data using tokenization in a prediction model. In one embodiment, a method includes outputting a bit pattern of probable tokens generated from raw data using a model. The method also includes converting, using the model, the bit pattern into output tokens and parsing the output tokens into a symbolic expression. The method also includes fitting symbolic parameters from the symbolic expression into an interpretable model for accuracy. The method also includes estimating an operational behavior and signal output of a vehicle system according to the interpretable model.
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公开(公告)号：US20220363286A1
公开(公告)日：2022-11-17
申请号：US17321004
申请日：2021-05-14
发明人： Daniel Jackson , Soon Ho Kong , Nikos Arechiga Gonzalez , Anna G. Bryan , Uriel Guajardo , Jeff Chow , Geoffrey Litt , Joshua Maxwell Pollock , Sergio Vale Aguiar Campos
IPC分类号： B60W60/00 , G01S13/931 , G06K9/00
摘要： An object recognition determination produced by a perception system from data received from a ranging sensor system can be verified. A certificate can be produced that includes data for points of readings from the ranging sensor system. The points can have been segmented, by the perception system, into point sets that correspond to objects in an environment of a cyber-physical system. The certificate can also include lists of pairs of points in a point set and a velocity of the point set. A test of information in the certificate can be performed. Based on a result of the test: a rectification can be made to the perception system or the ranging sensor system or a communication can be transmitted to a control signal production module configured to produce, in response to the communication, a control signal to be transmitted to an actuator system configured to control the cyber-physical system.
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公开(公告)号：US20230409880A1
公开(公告)日：2023-12-21
申请号：US18113937
申请日：2023-02-24
发明人： Yanxia Zhang , Francine R. Chen , Rumen Iliev , Totte Harinen , Alexandre L.S. Filipowicz , Yin-Ying Chen , Nikos Arechiga Gonzalez , Shabnam Hakimi , Kenton Michael Lyons , Charlene C. Wu , Matthew E. Klenk
IPC分类号： G06N3/0455 , G06N3/048
CPC分类号： G06N3/0455 , G06N3/048
摘要： Systems and methods for generating predicted preferences are disclosed. The method includes implementing, with a computing device having a processor and a non-transitory computer-readable memory, a conjoint architecture comprising: an autoencoder trained to transform input data including one or more choices and one or more features into a latent representation, and a choice classification network trained to predict one or more predicted preferences from the latent representation extracted by the autoencoder. The method further includes outputting, from the choice classification network, the one or more predicted preferences.
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公开(公告)号：US10882522B2
公开(公告)日：2021-01-05
申请号：US16130458
申请日：2018-09-13
发明人： Guy Rosman , Jonathan DeCastro , Nikos Arechiga Gonzalez , John Joseph Leonard , Luke S. Fletcher , Daniel Stonier
IPC分类号： B60W30/095 , B60W30/09 , G06K9/00 , G05D1/00 , G06N7/00
摘要： System, methods, and other embodiments described herein relate to modeling dynamic agents in a surrounding environment of an ego vehicle. In one embodiment, a method includes, in response to receiving sensor data including present observations of a road agent of the dynamic agents in the surrounding environment, identifying previous observations of the road agent from an electronic data store. The method includes estimating a future state of the road agent using at least the present observations and the previous observations of the road agent to compute the future state according to a probabilistic model comprised of a transition model that accounts for dynamic behaviors of the road agent to characterize transitions between states, and an agent model that accounts for actions of the road agent. The method includes controlling one or more vehicle systems of the ego vehicle according to the future state of the road agent.
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公开(公告)号：US11918535B2
公开(公告)日：2024-03-05
申请号：US16847380
申请日：2020-04-13
IPC分类号： A61H3/00
CPC分类号： A61H3/00 , A61H2201/0103 , A61H2201/0173 , A61H2201/165 , A61H2201/1659 , A61H2201/5007 , A61H2230/625
摘要： Systems and methods for a powered, robotic exoskeleton, or exosuit, for a user's limbs and body are provided. The exosuit may be equipped with airbag devices mounted at various locations on the suit. The exosuit may include on-board computing equipment that can sense, compute control commands in real-time, and actuate limbs and airbags to restore stability (fall prevention) and minimize injuries due to falls, should they happen (fall protection).
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公开(公告)号：US11721139B2
公开(公告)日：2023-08-08
申请号：US17715548
申请日：2022-04-07
发明人： Alexandre Filipowicz , David Ayman Shamma , Nikos Arechiga Gonzalez , Matthew L. Lee , Scott Carter
IPC分类号： G07C5/04 , G01C21/36 , B60R16/023 , G06Q30/0601
CPC分类号： G07C5/04 , B60R16/023 , B60R16/0231 , G01C21/3697 , G06Q30/0631
摘要： Systems, methods, and other embodiments described herein relate to informing a user how a hypothetical electric vehicle would perform based on the driving habits of the user in a non-electric vehicle. In one embodiment, a method includes identifying an origin and a destination of a non-electric vehicle after the non-electric vehicle has arrived at the destination. The method includes determining energy information for a hypothetical electric vehicle traveling from the origin to the destination and outputting the energy information to the user.
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公开(公告)号：US11157756B2
公开(公告)日：2021-10-26
申请号：US16745560
申请日：2020-01-17
摘要： An artificial intelligence perception system for detecting one or more objects includes one or more processors, at least one sensor, and a memory device. The memory device includes an image capture module, an object identifying module, and a logical scaffold module. The image capture module and the object identifying module cause the one or more processors to obtain sensor information of a field of view from a sensor, identify an object within the sensor information, and determine at least one property of the object. The logical scaffold module causes the one or more processors to determine, by a logical scaffold, when the at least one property of the object as determined by the object identifying module is one of a true condition or a false condition.
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公开(公告)号：US11745732B2
公开(公告)日：2023-09-05
申请号：US16696546
申请日：2019-11-26
发明人： Daniel Jackson , Jonathan Decastro , Soon Ho Kong , Nikos Arechiga Gonzalez , Dimitrios Koutentakis , Feng Ping Angela Leong , Mike Meichang Wang , Xin Zhang
IPC分类号： B60W30/09 , B60W30/095 , B60W10/20 , B60W10/18 , G05D1/00
CPC分类号： B60W30/09 , B60W10/18 , B60W10/20 , B60W30/0956 , G05D1/0077
摘要： A method for certified control of a self-driving ego vehicle is described. The method includes analyzing a safety situation of the self-driving ego vehicle to determine a proposed vehicle control action using a main controller of the self-driving ego vehicle. The method also includes presenting, by the main controller, the proposed vehicle control action to an interlock controller, including a certificate of the proposed vehicle control action. The method further includes checking a safety certification evidence from the certificate by the interlock controller using a predefined safety argument to verify the safety certification evidence of the certificate. The method also includes directing, by a low-level controller, the self-driving ego vehicle to perform a certified vehicle control action.
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