公开(公告)号：US20210182604A1

公开(公告)日：2021-06-17

申请号：US17190619

申请日：2021-03-03

Applicant: Perceptive Automata, Inc.

Inventor： Samuel English Anthony ,  Kshitij Misra ,  Avery Wagner Faller

IPC: G06K9/62 ,  G06N3/08 ,  G06N3/04 ,  G06K9/00 ,  G08G1/16 ,  G08G1/04 ,  G05D1/00 ,  B60W30/00

Abstract: Systems and methods for predicting user interaction with vehicles. A computing device receives an image and a video segment of a road scene, the first at least one of an image and a video segment being taken from a perspective of a participant in the road scene and then generates stimulus data based on the image and the video segment. Stimulus data is transmitted to a user interface and response data is received, which includes at least one of an action and a likelihood of the action corresponding to another participant in the road scene. The computing device aggregates a subset of the plurality of response data to form statistical data and a model is created based on the statistical data. The model is applied to another image or video segment and a prediction of user behavior in the another image or video segment is generated.

公开(公告)号：US20200247432A1

公开(公告)日：2020-08-06

申请号：US16709788

申请日：2019-12-10

Applicant: Perceptive Automata, Inc.

Inventor： Kshitij Misra ,  Samuel English Anthony

IPC: B60W60/00 ,  G06K9/00 ,  G08G1/01 ,  G06N3/08

Abstract: A system performs modeling and simulation of non-stationary traffic entities for testing and development of modules used in an autonomous vehicle system. The system uses a machine learning based model that predicts hidden context attributes for traffic entities that may be encountered by a vehicle in traffic. The system generates simulation data for testing and development of modules that help navigate autonomous vehicles. The generated simulation data may be image or video data including representations of traffic entities, for example, pedestrians, bicyclists, and other vehicles. The system may generate simulation data using generative adversarial neural networks.

公开(公告)号：US20190340465A1

公开(公告)日：2019-11-07

申请号：US16512560

申请日：2019-07-16

Applicant: Perceptive Automata, Inc.

Inventor： Samuel English Anthony ,  Kshitij Misra ,  Avery Wagner Faller

IPC: G06K9/62 ,  G06N3/04 ,  G06N3/08 ,  G06K9/00 ,  G05D1/00 ,  G08G1/04 ,  G08G1/16 ,  B60W30/00

Abstract: Systems and methods for predicting user interaction with vehicles. A computing device receives an image and a video segment of a road scene, the first at least one of an image and a video segment being taken from a perspective of a participant in the road scene and then generates stimulus data based on the image and the video segment. Stimulus data is transmitted to a user interface and response data is received, which includes at least one of an action and a likelihood of the action corresponding to another participant in the road scene. The computing device aggregates a subset of the plurality of response data to form statistical data and a model is created based on the statistical data. The model is applied to another image or video segment and a prediction of user behavior in the another image or video segment is generated.

公开(公告)号：US11840261B2

公开(公告)日：2023-12-12

申请号：US17321297

申请日：2021-05-14

Applicant: Perceptive Automata, Inc.

Inventor： Till S. Hartmann ,  Jeffrey D. Zaremba ,  Samuel English Anthony

IPC: G05D1/02 ,  G06N20/00 ,  G06N5/04 ,  G06N3/08 ,  G06V20/40 ,  G06V20/56 ,  G06F18/40 ,  G06F18/214 ,  G06F18/21 ,  G06F18/2113 ,  G06V10/764 ,  G06V10/82 ,  G06V20/58 ,  G06V40/20 ,  B60W60/00

CPC classification number: B60W60/00272 ,  B60W60/001 ,  G05D1/0221 ,  G05D1/0246 ,  G06F18/214 ,  G06F18/217 ,  G06F18/2113 ,  G06F18/40 ,  G06N3/08 ,  G06N5/04 ,  G06N20/00 ,  G06V10/764 ,  G06V10/82 ,  G06V20/41 ,  G06V20/56 ,  G06V20/58 ,  G06V40/23 ,  B60W2420/42 ,  B60W2420/52 ,  B60W2552/05 ,  B60W2554/408 ,  B60W2554/4029 ,  B60W2554/4041 ,  B60W2554/4044 ,  B60W2554/4045 ,  B60W2554/4046 ,  B60W2554/801 ,  G05D2201/0213

Abstract: A system uses a machine learning based model to determine attributes describing states of mind and behavior of traffic entities in video frames captured by an autonomous vehicle. The system classifies video frames according to traffic scenarios depicted, where each scenario is associated with a filter based on vehicle attributes, traffic attributes, and road attributes. The system identifies a set of video frames associated with ground truth scenarios for validating the accuracy of the machine learning based model and predicts attributes of traffic entities in the video frames. The system analyzes video frames captured after the set of video frames to determine actual attributes of the traffic entities. Based on a comparison of the predicted attributes and actual attributes, the system determines a likelihood of the machine learning based model making accurate predictions and uses the likelihood to generate a navigation action table for controlling the autonomous vehicle.

公开(公告)号：US11520346B2

公开(公告)日：2022-12-06

申请号：US16777673

申请日：2020-01-30

Applicant: Perceptive Automata, Inc.

Inventor： Samuel English Anthony

IPC: G05D1/02 ,  B60W30/095 ,  G05D1/00 ,  B60W40/09 ,  G06N20/00 ,  B60W30/09 ,  B60W60/00

Abstract: An autonomous vehicle uses machine learning based models to predict hidden context attributes associated with traffic entities. The system uses the hidden context to predict behavior of people near a vehicle in a way that more closely resembles how human drivers would judge the behavior. The system determines an activation threshold value for a braking system of the autonomous vehicle based on the hidden context. The system modifies a world model based on the hidden context predicted by the machine learning based model. The autonomous vehicle is safely navigated, such that the vehicle stays at least a threshold distance away from traffic entities.

公开(公告)号：US11518413B2

公开(公告)日：2022-12-06

申请号：US17321253

申请日：2021-05-14

Applicant: Perceptive Automata, Inc.

Inventor： Samuel English Anthony ,  Till S. Hartmann ,  Jacob Reinier Maat ,  Dylan James Rose ,  Kevin W. Sylvestre

IPC: B60W60/00 ,  B60W40/04 ,  G06N3/08 ,  G06V20/56

Abstract: An autonomous vehicle collects sensor data of an environment surrounding the autonomous vehicle including traffic entities such as pedestrians, bicyclists, or other vehicles. The sensor data is provided to a machine learning based model along with an expected turn direction of the autonomous vehicle to determine a hidden context attribute of a traffic entity given the expected turn direction of the autonomous vehicle. The hidden context attribute of the traffic entity represents factors that affect the behavior of the traffic entity, and the hidden context attribute is used to predict future behavior of the traffic entity. Instructions to control the autonomous vehicle are generated based on the hidden context attribute.

公开(公告)号：US20210357662A1

公开(公告)日：2021-11-18

申请号：US17321297

申请日：2021-05-14

Applicant: Perceptive Automata, Inc.

Inventor： Till S. Hartmann ,  Jeffrey D. Zaremba ,  Samuel English Anthony

IPC: G06K9/00 ,  B60W60/00 ,  G06N3/08

Abstract: A system uses a machine learning based model to determine attributes describing states of mind and behavior of traffic entities in video frames captured by an autonomous vehicle. The system classifies video frames according to traffic scenarios depicted, where each scenario is associated with a filter based on vehicle attributes, traffic attributes, and road attributes. The system identifies a set of video frames associated with ground truth scenarios for validating the accuracy of the machine learning based model and predicts attributes of traffic entities in the video frames. The system analyzes video frames captured after the set of video frames to determine actual attributes of the traffic entities. Based on a comparison of the predicted attributes and actual attributes, the system determines a likelihood of the machine learning based model making accurate predictions and uses the likelihood to generate a navigation action table for controlling the autonomous vehicle.

公开(公告)号：USD928804S1

公开(公告)日：2021-08-24

申请号：US29694709

申请日：2019-06-12

Applicant: Perceptive Automata, Inc.

Designer： Avery Wagner Faller ,  Samuel English Anthony

公开(公告)号：USD928803S1

公开(公告)日：2021-08-24

申请号：US29694706

申请日：2019-06-12

Applicant: Perceptive Automata, Inc.

Designer： Avery Wagner Faller ,  Samuel English Anthony

公开(公告)号：US20200293822A1

公开(公告)日：2020-09-17

申请号：US16828823

申请日：2020-03-24

Applicant: Perceptive Automata Inc.

Inventor： Samuel English Anthony ,  Kshitij Misra ,  Avery Wagner Faller

IPC: G06K9/62 ,  G06N3/08 ,  G06N3/04 ,  G06K9/00 ,  G08G1/16 ,  G08G1/04 ,  G05D1/00 ,  B60W30/00

Abstract: Systems and methods for predicting user interaction with vehicles. A computing device receives an image and a video segment of a road scene, the first at least one of an image and a video segment being taken from a perspective of a participant in the road scene and then generates stimulus data based on the image and the video segment. Stimulus data is transmitted to a user interface and response data is received, which includes at least one of an action and a likelihood of the action corresponding to another participant in the road scene. The computing device aggregates a subset of the plurality of response data to form statistical data and a model is created based on the statistical data. The model is applied to another image or video segment and a prediction of user behavior in the another image or video segment is generated.