Verizon Connect Development Limited

Verizon Connect Ireland Limited

Verizon Patent and Licensing Inc.

Fabio Schoen

Francesco Sambo

Matteo Simoncini

Leonardo Taccari

Douglas Coimbra De Andrade

Leonardo Sarti

Alessandro Lori

Luca Bravi

Samuele Salti

Stefano Caprasecca

Tommaso Bianconcini

Luca Kubin

Aurel Pjetri

Simone Magistri

Peter Mitchell

David Di Lorenzo

Enrico Civitelli

In some implementations, an adverse environment detection system may receive an image of a road scene associated with a vehicle. The adverse environment detection system may determine a set of features associated with the image based on providing the image to an initial portion of a model. The adverse environment detection system may determine a first condition associated with the image based on providing the set of features to a first processing layer of the model, a second condition associated with the image based on providing the set of features to a second processing layer of the model, and a third condition associated with the image based on providing the set of features to a third processing layer of the model. The first processing layer, the second processing layer, and the third processing layer may process the set of features in parallel.

Systems and methods for utilizing machine learning for vehicle detection of adverse conditions

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.

Systems and methods for utilizing a deep learning model to determine vehicle viewpoint estimations

A device may receive vehicle operation data associated with operation of a plurality of vehicles, and may process the vehicle operation data to generate processed vehicle operation data. The device may extract multiple features from the processed vehicle operation data, and may train machine learning models, with the multiple features, to generate trained machine learning models that provide model outputs. The device may process the multiple features, with a feature selection model and based on the model outputs, to select sets of features from the plurality of features, and may process the sets of features, with the trained machine learning models, to generate indications of driving behavior and reliabilities of the indications. The device may select a set of features, from the sets of features, based on the indications and the reliabilities, where the set of features may be calculated by a device associated with a particular vehicle.

Systems and methods for utilizing machine learning and feature selection to classify driving behavior

A maneuver classification platform may obtain video data and telematic data that are associated with a driving event involving a vehicle. The maneuver classification platform may analyze the video data to identify a path of the vehicle along a roadway during the driving event, and based on markings of a plurality of roadways. The maneuver classification platform may analyze the video data to determine a type of a vehicle maneuver performed by the vehicle during the driving event. The maneuver classification platform may determine a maneuver score of the driving event based on the type of the vehicle maneuver, the path of the vehicle, and the telematic data. The maneuver classification platform may send a message associated with the maneuver score and a vehicle identifier of the vehicle to a client device to permit the client device to use the maneuver score.

Systems and methods for detecting and classifying an unsafe maneuver of a vehicle

A method for finding an approximation to the all-pairs shortest travel path between a number of predetermined nodes, comprising clustering nodes of an original road network into a plurality of subgroups so that the number of nodes in each subgroup is no greater than a first predetermined threshold and the maximum distance between any two nodes of a subgroup is no greater than a second predetermined threshold; adding information of intra group shortest paths for all pairs in a same subgroup to a newly created higher level road network; adding information of inter group shortest paths for the plurality of subgroups to the same road network; and searching the same road network for the shortest travel path. In those cases in which the path returned is not exact, the path represents one in the original map, even if not necessarily the best one.

System and method for accelerating route search

Growing community of inventors

Florence, Italy

Fabio Schoen