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公开(公告)号：US11727805B2
公开(公告)日：2023-08-15
申请号：US17446322
申请日：2021-08-30
发明人： Luca Bravi , Tommaso Mugnai , Alessandro Giannini
IPC分类号： G08G1/14 , G05D1/02 , G06N20/00 , G06F16/9537
CPC分类号： G08G1/143 , G05D1/0221 , G06F16/9537 , G06N20/00
摘要： A device may receive geographical data identifying a geographical area, and may receive, from vehicle devices of vehicles, first vehicle data identifying engine off conditions, locations during engine off conditions, and durations of the engine off conditions. The device may divide, based on the geographical data, the geographical area into clusters with particular dimensions, and may process data identifying the clusters and the first vehicle data, with a machine learning model, to determine parking data identifying public parking spaces in the geographical area. The device may receive, from a set of the vehicle devices associated with vehicles parked in the public parking spaces, vehicle data identifying engine on conditions and locations during the engine on conditions, and may identify available public parking spaces based on the second vehicle data and the parking data. The device may perform one or more actions based on data identifying the available public parking spaces.
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公开(公告)号：US11926318B2
公开(公告)日：2024-03-12
申请号：US16949441
申请日：2020-10-29
发明人： Luca Bravi , Luca Kubin , Leonardo Sarti , Leonardo Taccari , Francesco Sambo
CPC分类号： B60W30/0956 , B60W50/14 , G06F18/24 , G06T7/20 , G06T7/60 , G06T7/70 , G06V20/58 , G08G1/166 , B60W2050/146 , B60W2420/42 , B60W2554/4042 , B60W2554/4044 , G06T2207/10016 , G06T2207/30241 , G06T2207/30261
摘要： In some implementations, a device may receive video data associated with video frames that depict an environment of a vehicle. The device may identify an object depicted in the video frames, wherein an object detection model indicates bounding boxes associated with the object. The device may determine, based on the bounding boxes, a configuration of the bounding boxes within the video frames. The device may determine, based on the configuration of the bounding boxes, that the object is a vulnerable road user (VRU) that is in the environment. The device may determine a trajectory of the VRU based on a change in the configuration between video frames of a set of the video frames. The device may determine, based on the trajectory, a probability of a collision between the VRU and the vehicle. The device may perform, based on the probability, an action associated with the vehicle.
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3.发明授权公开(公告)号：US11922651B2
公开(公告)日：2024-03-05
申请号：US18061124
申请日：2022-12-02
发明人： Simone Magistri , Francesco Sambo , Douglas Coimbra De Andrade , Fabio Schoen , Matteo Simoncini , Luca Bravi , Stefano Caprasecca , Luca Kubin , Leonardo Taccari
CPC分类号： G06T7/70 , G06N3/08 , G06V20/56 , G06T2207/20076 , G06T2207/20081 , G06T2207/20084 , G06T2207/30252
摘要： A device may receive a first image. The device may process the first image to identify an object in the first image and a location of the object within the first image. The device may extract a second image from the first image based on the location of the object within the first image. The device may process the second image to determine at least one of a coarse-grained viewpoint estimate or a fine-grained viewpoint estimate associated with the object. The device may determine an object viewpoint associated with the second vehicle based on the at least one of the coarse-grained viewpoint estimate or the fine-grained viewpoint estimate. The device may perform one or more actions based on the object viewpoint.
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公开(公告)号：US11501538B2
公开(公告)日：2022-11-15
申请号：US17001139
申请日：2020-08-24
发明人： Tommaso Bianconcini , Stefano Caprasecca , Tommaso Mugnai , Luca Bravi , Francesco Sambo , Leonardo Taccari
摘要： A device may obtain video data associated with a driving event involving a first vehicle. The device may determine a vanishing point associated with the video data and may construct a cone of impact of the first vehicle based on the vanishing point. The device may detect a second vehicle within the cone of impact and may analyze the subset of video frames to determine a distance between the first vehicle and the second vehicle. The device may determine a speed of the first vehicle during a time period associated with a subset of video frames. The device may determine a headway score, representative of a severity associated with the first vehicle being within a proximity threshold of the second vehicle during the time period, based on the distance and the speed. The device may determine an occurrence of a tailgating event based on the headway score.
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公开(公告)号：US11900657B2
公开(公告)日：2024-02-13
申请号：US17001161
申请日：2020-08-24
发明人： Luca Bravi , Luca Kubin , Leonardo Taccari , Francesco Sambo , Matteo Simoncini , Douglas Coimbra De Andrade , Stefano Caprasecca
IPC分类号： G06V20/58 , G06V10/764 , G06T7/70 , G06N20/00 , B60Q9/00 , G08G1/052 , G06F18/21 , G06F18/24 , G06N7/01 , B60R11/04 , G05D1/00
CPC分类号： G06V10/764 , B60Q9/00 , G06F18/21 , G06F18/24 , G06N7/01 , G06N20/00 , G06T7/70 , G06V20/582 , G08G1/052 , B60R11/04 , G05D1/0061 , G06T2207/20084 , G06T2207/30252
摘要： A violation detection platform may obtain image data, location data, and sensor data associated with a vehicle. The violation detection platform may determine a probability that a frame of the image data includes an image of a stop sign. The violation detection platform may determine that the probability satisfies a probability threshold. The violation detection platform may identify location data and sensor data associated with the frame of the image data based on the probability satisfying the probability threshold. The violation detection platform may determine an occurrence of a type of a stop sign violation based on the probability, the location data, and the sensor data. The violation detection platform may perform one or more actions based on determining the occurrence of the type of the stop sign violation.
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公开(公告)号：US11651599B2
公开(公告)日：2023-05-16
申请号：US16947780
申请日：2020-08-17
发明人： Douglas Coimbra De Andrade , Andrea Benericetti , Aurel Pjetri , Leonardo Taccari , Francesco Sambo , Alex Quintero Garcia , Luca Bravi
CPC分类号： G06V20/59 , B60W40/09 , B60W50/14 , G06N20/00 , G06T7/10 , G06V20/40 , G06V40/172 , B60W2540/229 , G06T2207/20081 , G06T2207/20132 , G06T2207/30201
摘要： A device may process the video data, with a first machine learning model, to identify a driver of a vehicle and may process the video data associated with the driver, with a second machine learning model, to detect behavior data identifying a behavior of the driver. The device may process the behavior data, with a third machine learning model, to determine distraction data identifying whether the behavior is classified as a distracted behavior. The device may process the behavior data, with a fourth machine learning model, to determine policy compliance data identifying whether the behavior satisfies one or more policies. The device may calculate a distraction score based on the distraction data and the video data, and may calculate a policy compliance score based on the policy compliance data and vehicle data. The device may perform one or more actions based on the distraction score and the policy compliance score.
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公开(公告)号：US11514276B2
公开(公告)日：2022-11-29
申请号：US17174768
申请日：2021-02-12
摘要： A method and system for identifying recurrent stops of a vehicle fleet having a plurality of vehicles. The method comprises retrieving historical GPS tracks of the vehicle fleet over a period of time; detecting stops made by the vehicle fleet along travelled routes that are associated with the historical GPS tracks; constructing a coverage area that covers the travelled routes; discretizing the coverage area into a plurality of cells; determining whether a cell is a recurrent stop based on a fleet stay period associated with that cell; and classifying a determined recurrent stop into a plurality of categories.
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公开(公告)号：US11639857B2
公开(公告)日：2023-05-02
申请号：US17166403
申请日：2021-02-03
摘要： A rating platform can identify a point of interest (POI) among a first plurality of POIs included in a stop cluster. The rating platform can generate a plurality of unweighted user scores for the POI. Respective unweighted user scores, of the plurality of unweighted user scores is associated, can be associated with respective users of a plurality of users. The rating platform can generate a plurality of weighted user scores for the POI based on the plurality of unweighted user scores and respective weights assigned to respective users of the plurality of users. The rating platform can generate a POI score for the POI based on the plurality of weighted user scores. The rating platform can transmit, based on the POI score, an instruction to display, on the client device, information associated with the POI.
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9.发明授权公开(公告)号：US11532096B2
公开(公告)日：2022-12-20
申请号：US17001166
申请日：2020-08-24
发明人： Simone Magistri , Francesco Sambo , Douglas Coimbra de Andrade , Fabio Schoen , Matteo Simoncini , Luca Bravi , Stefano Caprasecca , Luca Kubin , Leonardo Taccari
摘要： A device may receive a first image. The device may process the first image to identify an object in the first image and a location of the object within the first image. The device may extract a second image from the first image based on the location of the object within the first image. The device may process the second image to determine at least one of a coarse-grained viewpoint estimate or a fine-grained viewpoint estimate associated with the object. The device may determine an object viewpoint associated with the second vehicle based on the at least one of the coarse-grained viewpoint estimate or the fine-grained viewpoint estimate. The device may perform one or more actions based on the object viewpoint.
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公开(公告)号：US11210939B2
公开(公告)日：2021-12-28
申请号：US15518694
申请日：2016-12-02
发明人： Samuele Salti , Francesco Sambo , Leonardo Taccari , Luca Bravi , Matteo Simoncini , Alessandro Lori
摘要： A method and system for classifying a vehicle based on low frequency GPS tracks. The method and system comprise retrieving a low frequency GPS track having a sampling interval of at least 20 seconds; deriving additional data from the low frequency GPS track, the additional data including interval speed and instantaneous acceleration of the vehicle; extracting a plurality of data sets from the low frequency GPS track and the additional data; generating a plurality of features from the extracted data sets; and providing the plurality of generated features to a classifier that classifies the vehicle into a predetermined class.
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