Verizon Patent and Licensing Inc.

Joshua D Eno

Kevin Brackney

Lindy Williams

Bergen Davell

Wesley Boyer

Khoa Truong Pham

Daniel Austin Kopyc

John Chipouras

John Patrick O'Dwyer

Rajat Agrawal

Tristan Storz

Zeehasham Rasheed

A device receives re-routing event data identifying a deviation from a proposed route at a particular location. The device determines, based on the re-routing event data, whether the deviation from the proposed route is a problem deviation or a planned deviation, and associates, based on determining that the deviation from the proposed route is a problem deviation, the particular location with an problematic location tag. The device determines that a route, corresponding to a request for routing information received from a navigation device, includes the particular location, and determines, based on a user profile and the problematic location tag, a particular alert level, of a plurality of alert levels, to associate with the particular location. The device detects a proximity of the navigation device to the particular location, and causes a particular alert corresponding to the particular alert level to be provided via the navigation device.

Automated identification of problematic locations for navigation and route guidance modification for dynamic alerting

An exemplary geospatial image processing system generates, based on multiple detections of an object of interest detected by a computer vision model in multiple, correlated images of a geospatial location captured from different camera viewpoints, user interface content that includes a visual indication of the detected object of interest superimposed at an object position on a view of the geospatial location. The system provides the user interface content for display in a graphical user interface view of a user interface and provides, by way of the user interface, a user interface tool configured to facilitate user validation of one or more of the multiple detections of the object of interest. The system may receive, a user validation of one or more of the multiple detections of the object of interest and may train the computer vision model based on the user validation. Corresponding methods and systems are also disclosed.

Systems and methods for training and validating a computer vision model for geospatial imagery

Exemplary systems and methods perform post-processing operations on computer vision model detections of objects of interest in geospatial imagery to detect and assign attributes to the detected objects of interest. For example, an exemplary post-processing system correlates multiple detections, made by a computer vision model, of an object of interest depicted within a set of images of a geospatial location, determines, based on the correlated detections, an attribute of the object of interest depicted within the set of images of the geospatial location, and selects the attribute for inclusion in a dataset for the object of interest. Corresponding methods and systems are also disclosed.

Methods and systems for detecting and assigning attributes to objects of interest in geospatial imagery

A device can determine route information associated with a route of a vehicle. The device can identify, based on the route information, feature data associated with the route of the vehicle. The device can determine, based on the feature data, notification information associated with a feature on the route of the vehicle. The feature can include at least one of: a passing zone on the route of the vehicle, a school zone on the route of the vehicle, a potential roadway hazard on the route of the vehicle, a segment of the route with a speed limit that is different from a speed limit of another segment of the route, or a segment of the route with a number of lanes that is different from a speed limit of another segment of the route. The device can provide the notification information associated with the feature.

Driver notification of roadway features on a vehicle route

A device can obtain geographic map metadata associated with a set of locations. The device can generate a data structure that associates the geographic map metadata for each location, of the set of locations. The device can receive, from a user device, a request for a set of navigational directions to a first location with multiple entrances, where the first location is one of the set of locations. The request can include information identifying the first location and information identifying a current location of the user device. The device can select an entrance, of the multiple entrances associated with the first location based on the request. The device can determine the set of navigational directions using geographic map metadata associated with the first location. The device can provide the set of navigational directions to the user device to direct the user device to the selected entrance.

Routing to locations with multiple entrances

A device can receive a data model that has been trained on base map data and summary statistics data associated with a first geographic region. The device can obtain additional base map data associated with a second geographic region and additional summary statistics data for a set of junctions within the second geographic region. The device can determine traffic control mechanisms associated with the set of junctions by providing the additional base map data and the additional summary statistics data as input for the data model. The device can generate, using output of the data model, a base map that includes information indicating whether the set of junctions include traffic control mechanisms. The device can, after generating the base map, perform one or more actions associated with improving vehicle navigation or traffic management.

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Denver, CO, United States of America

Joshua D Eno