Vulnerable road user's adversarial behavior recognition

    公开(公告)号:US12280786B2

    公开(公告)日:2025-04-22

    申请号:US18319037

    申请日:2023-05-17

    Abstract: A system for identifying adversarial behavior directed to an autonomous vehicle includes a pedestrian detection system in communication with a vehicle controller adapted to identify a pedestrian within proximity of the autonomous vehicle, track the pedestrian, determine if the pedestrian is intending to cross in front of the autonomous vehicle, and if the pedestrian tracking system determines that the pedestrian is not intending to cross in front of the autonomous vehicle, the pedestrian tracking system is further adapted to continue tracking the pedestrian, and if the pedestrian tracking system determines that the pedestrian is intending to cross in front of the autonomous vehicle, the pedestrian tracking system is further adapted to determine, with an adversarial intent algorithm, if the pedestrian is exhibiting any adversarial behavior.

    VULNERABLE ROAD USER’S ADVERSARIAL BEHAVIOR RECOGNITION

    公开(公告)号:US20240383481A1

    公开(公告)日:2024-11-21

    申请号:US18319037

    申请日:2023-05-17

    Abstract: A system for identifying adversarial behavior directed to an autonomous vehicle includes a pedestrian detection system in communication with a vehicle controller adapted to identify a pedestrian within proximity of the autonomous vehicle, track the pedestrian, determine if the pedestrian is intending to cross in front of the autonomous vehicle, and if the pedestrian tracking system determines that the pedestrian is not intending to cross in front of the autonomous vehicle, the pedestrian tracking system is further adapted to continue tracking the pedestrian, and if the pedestrian tracking system determines that the pedestrian is intending to cross in front of the autonomous vehicle, the pedestrian tracking system is further adapted to determine, with an adversarial intent algorithm, if the pedestrian is exhibiting any adversarial behavior.

    Perception methods and systems for low lighting conditions

    公开(公告)号:US11300974B2

    公开(公告)日:2022-04-12

    申请号:US16515592

    申请日:2019-07-18

    Abstract: Methods and systems are provided for detecting objects within an environment of a vehicle. In one embodiment, a method includes: receiving, by a processor, image data sensed from the environment of the vehicle; determining, by a processor, an area within the image data that object identification is uncertain; controlling, by the processor, a position of a lighting device to illuminate a location in the environment of the vehicle, wherein the location is associated with the area; controlling, by the processor, a position of one or more sensors to obtain sensor data from the location of the environment of the vehicle while the lighting device is illuminating the location; identifying, by the processor, one or more objects from the sensor data; and controlling, by the processor, the vehicle based on the one or more objects.

    Systems and methods for enhanced distance estimation by a mono-camera using radar and motion data

    公开(公告)号:US10861176B2

    公开(公告)日:2020-12-08

    申请号:US16200932

    申请日:2018-11-27

    Abstract: Systems and methods for depth estimation of images from a mono-camera by use of radar data by: receiving, a plurality of input 2-D images from the mono-camera; generating, by the processing unit, an estimated depth image by supervised training of an image estimation model; generating, by the processing unit, a synthetic image from a first input image and a second input image from the mono-camera by applying an estimated transform pose; comparing, by the processing unit, an estimated three-dimensional (3-D) point cloud to radar data by applying another estimated transform pose to a 3-D point cloud wherein the 3-D point cloud is estimated from a depth image by supervised training of the image estimation model to radar distance and radar doppler measurement; correcting a depth estimation of the estimated depth image by losses derived from differences: of the synthetic image and original images; of an estimated depth image and a measured radar distance; and of an estimated doppler information and measured radar doppler information.

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