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公开(公告)号：US20210064890A1
公开(公告)日：2021-03-04
申请号：US16557246
申请日：2019-08-30
Applicant: Waymo LLC
Inventor： Hyman Murveit , Abhijit Ogale , Yu-Han Chen , Alper Ayvaci
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a future occupancy prediction for a region of an environment. In one aspect, a method comprises: receiving sensor data generated by a sensor system of a vehicle that characterizes an environment in a vicinity of the vehicle as of a current time point, wherein the sensor data comprises a plurality of sensor samples characterizing the environment that were each captured at different time points; processing a network input comprising the sensor data using a neural network to generate an occupancy prediction output for a region of the environment, wherein: the occupancy prediction output characterizes, for one or more future intervals of time after the current time point, a respective likelihood that the region of the environment will be occupied by an agent in the environment during the future interval of time.
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公开(公告)号：US10710579B2
公开(公告)日：2020-07-14
申请号：US15611397
申请日：2017-06-01
Applicant: Waymo LLC
Inventor： Wan-Yen Lo , Abhijit Ogale , David Ferguson
Abstract: In some implementations, an autonomous or semi-autonomous vehicle is capable of using a collision prediction system to determine a confidence that any objects detected within a vicinity of the vehicle are on a trajectory that will collide with the vehicle. Laser obstacle points derived from recent sensor readings of one or more sensors of a vehicle are initially obtained. The laser obstacle points are projected into a pose coordinate system to generate an occupancy grid of a vicinity of the vehicle. A confidence that any objects represented by the laser obstacle points are on a trajectory that will collide with the vehicle is determined by applying a particle filter to the occupancy grid.
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公开(公告)号：US20190033085A1
公开(公告)日：2019-01-31
申请号：US15662007
申请日：2017-07-27
Applicant: Waymo LLC
Inventor： Abhijit Ogale , Mayank Bansal , Alexander Krizhevsky
Abstract: Systems, methods, devices, and other techniques for planning a trajectory of a vehicle. A computing system can implement a trajectory planning neural network configured to, at each time step of multiple time steps: obtain a first neural network input and a second neural network input. The first neural network input can characterize a set of waypoints indicated by the waypoint data, and the second neural network input can characterize (a) environmental data that represents a current state of an environment of the vehicle and (b) navigation data that represents a planned navigation route for the vehicle. The trajectory planning neural network may process the first neural network input and the second neural network input to generate a set of output scores, where each output score in the set of output scores corresponds to a different location of a set of possible locations in a vicinity of the vehicle.
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公开(公告)号：US20180373963A1
公开(公告)日：2018-12-27
申请号：US15630275
申请日：2017-06-22
Applicant: Waymo LLC
Inventor： Wan-Yen Lo , Abhijit Ogale , Yang Gao
CPC classification number: G06K9/6267 , G05D1/0088 , G05D1/0246 , G06K9/00805 , G06K9/00818 , G06K9/6273 , G06N3/0454 , G06N3/08 , G06N3/084
Abstract: In some implementations, an image classification system of an autonomous or semi-autonomous vehicle is capable of improving multi-object classification by reducing repeated incorrect classification of objects that are considered rarely occurring objects. The system can include a common instance classifier that is trained to identify and recognize general objects (e.g., commonly occurring objects and rarely occurring objects) as belonging to specified object categories, and a rare instance classifier that is trained to compute one or more rarity scores representing likelihoods that an input image is correctly classified by the common instance classifier. The output of the rare instance classifier can be used to adjust the classification output of the common instance classifier such that the likelihood of input images being incorrectly classified is reduced.
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公开(公告)号：US20180129886A1
公开(公告)日：2018-05-10
申请号：US15862291
申请日：2018-01-04
Applicant: Waymo LLC
Inventor： Abhijit Ogale , Dave Ferguson
CPC classification number: G06K9/00791 , B60R1/00 , B60R2300/80 , G05D1/0088 , G05D1/0246 , G06K9/00825 , G06K9/4604 , G06K9/4652 , G06K9/4661 , H04N5/2353
Abstract: An autonomous vehicle is configured to detect an active turn signal indicator on another vehicle. An image-capture device of the autonomous vehicle captures an image of a field of view of the autonomous vehicle. The autonomous vehicle captures the image with a short exposure to emphasize objects having brightness above a threshold. Additionally, a bounding area for a second vehicle located within the image is determined. The autonomous vehicle identifies a group of pixels within the bounding area based on a first color of the group of pixels. The autonomous vehicle also calculates an oscillation of an intensity of the group of pixels. Based on the oscillation of the intensity, the autonomous vehicle determines a likelihood that the second vehicle has a first active turn signal. Additionally, the autonomous vehicle is controlled based at least on the likelihood that the second vehicle has a first active turn signal.
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Patent Agency Ranking
公开(公告)号：US09766628B1
公开(公告)日：2017-09-19
申请号：US14244988
申请日：2014-04-04
Applicant: Waymo LLC
Inventor： Wan-Yen Lo , David Ian Franklin Ferguson , Abhijit Ogale
CPC classification number: G05D1/0246 , G05D2201/0212 , G06K9/00825 , G06K9/4652 , G06K9/4661 , G06K9/50
Abstract: A computing device of a first vehicle may receive a first image and a second image of a second vehicle having flashing light signals. The computing device may determine, in the first image and the second image, an image region that bounds the second vehicle such that the image region substantially encompasses the second vehicle. The computing device may determine a polar grid that partitions the image region in the first image and the second image into polar bins, and identify portions of image data exhibiting a change in color and a change in brightness between the first image and the second image. The computing device may determine a type of the flashing light signals and a type of the second vehicle; and accordingly provide instructions to control the first vehicle.
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公开(公告)号：US20240005671A1
公开(公告)日：2024-01-04
申请号：US18469955
申请日：2023-09-19
Applicant: Waymo LLC
Inventor： Abhijit Ogale , David Ian Franklin Ferguson
CPC classification number: G06V20/584 , G06V20/56 , H04N23/73 , B60R1/00 , G05D1/0088 , G05D1/0246 , B60R2300/80
Abstract: An autonomous vehicle is configured to detect an active turn signal indicator on another vehicle. An image-capture device of the autonomous vehicle captures an image of a field of view of the autonomous vehicle. The autonomous vehicle captures the image with a short exposure to emphasize objects having brightness above a threshold. Additionally, a bounding area for a second vehicle located within the image is determined. The autonomous vehicle identifies a group of pixels within the bounding area based on a first color of the group of pixels. The autonomous vehicle also calculates an oscillation of an intensity of the group of pixels. Based on the oscillation of the intensity, the autonomous vehicle determines a likelihood that the second vehicle has a first active turn signal. Additionally, the autonomous vehicle is controlled based at least on the likelihood that the second vehicle has a first active turn signal.
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公开(公告)号：US11772654B2
公开(公告)日：2023-10-03
申请号：US17862499
申请日：2022-07-12
Applicant: Waymo LLC
Inventor： Hyman Murveit , Abhijit Ogale , Yu-Han Chen , Alper Ayvaci
IPC: B60W30/18 , G06T7/174 , G05D1/00 , G05D1/02 , G01S13/931 , G01S7/41 , G06V20/58 , G06F18/214 , G06V10/25 , G06V10/774 , G06V10/80
CPC classification number: B60W30/18159 , G01S7/417 , G01S13/931 , G05D1/0088 , G05D1/0212 , G05D1/0231 , G05D1/0257 , G06F18/2155 , G06T7/174 , G06V10/25 , G06V10/7753 , G06V10/811 , G06V20/58 , G01S2013/9323 , G05D2201/0213 , G06T2207/20084 , G06T2207/20132
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a future occupancy prediction for a region of an environment. In one aspect, a method comprises: receiving sensor data generated by a sensor system of a vehicle that characterizes an environment in a vicinity of the vehicle as of a current time point, wherein the sensor data comprises a plurality of sensor samples characterizing the environment that were each captured at different time points; processing a network input comprising the sensor data using a neural network to generate an occupancy prediction output for a region of the environment, wherein: the occupancy prediction output characterizes, for one or more future intervals of time after the current time point, a respective likelihood that the region of the environment will be occupied by an agent in the environment during the future interval of time.
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公开(公告)号：US11281230B2
公开(公告)日：2022-03-22
申请号：US16837017
申请日：2020-04-01
Applicant: Waymo LLC
Inventor： Wan-Yen Lo , David Ian Franklin Ferguson , Abhijit Ogale
Abstract: A computing device of a first vehicle may receive a first image and a second image of a second vehicle having flashing light signals. The computing device may determine, in the first image and the second image, an image region that bounds the second vehicle such that the image region substantially encompasses the second vehicle. The computing device may determine a polar grid that partitions the image region in the first image and the second image into polar bins, and identify portions of image data exhibiting a change in color and a change in brightness between the first image and the second image. The computing device may determine a type of the flashing light signals and a type of the second vehicle; and accordingly provide instructions to control the first vehicle.
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公开(公告)号：US11256983B2
公开(公告)日：2022-02-22
申请号：US15662031
申请日：2017-07-27
Applicant: Waymo LLC
Inventor： Abhijit Ogale , Mayank Bansal , Alexander Krizhevsky
IPC: G06N3/08 , G05D1/02 , G06N3/04 , G06N3/00 , G01C21/34 , G01S17/931 , G01S17/42 , G01S13/86 , G01S17/86 , G01S13/931
Abstract: Systems, methods, devices, and other techniques for training a trajectory planning neural network system to determine waypoints for trajectories of vehicles. A neural network training system can train the trajectory planning neural network system on the multiple training data sets. Each training data set can include: (i) a first training input that characterizes a set of waypoints that represent respective locations of a vehicle at each of a series of first time steps, (ii) a second training input that characterizes at least one of (a) environmental data that represents a current state of an environment of the vehicle or (b) navigation data that represents a planned navigation route for the vehicle, and (iii) a target output characterizing a waypoint that represents a target location of the vehicle at a second time step that follows the series of first time steps.
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