The present application discloses a method and apparatus for identifying an updated road, a device and a computer storage medium, and relates to the field of big data technologies. A specific implementation solution is as follows: comparing a road area extracted based on the latest satellite image with a road area extracted based on a historical satellite image, to obtain a candidate updated road; mapping the candidate updated road into road network data according to a coordinate position of the candidate updated road; acquiring a user trajectory set corresponding to the candidate updated road within a recent preset period; and identifying, based on a matching result between the user trajectory set and the road network data, whether the candidate updated road is an actual updated road. Updated roads can be more accurately identified through the method according to the present application.

An apparatus for generating a map identifies a lane line and a feature other than a lane line on a road from a first image of a predetermined location of the road taken downward from the sky; identifies the lane line and the feature from a second image representing the predetermined location of the road and made based on images taken by a camera provided for a vehicle; aligning the first images with the second images, based on the predetermined location; deforms the second image so that the feature in the second image best fits the feature in the first image; further deforms the second image in a direction perpendicular to the front-back direction of the road so that the position of the feature remains unchanged and that the positions of the lane lines in the first and second images match; and combines the first and deformed second images.

System includes a controller configured to obtain one or more of a route parameter or a vehicle parameter from discrete examinations of one or more of a route or a vehicle system. The route parameter is indicative of a health of the route over which the vehicle system travels. The vehicle parameter is indicative of a health of the vehicle system. The discrete examinations of the one or more of the route or the vehicle system separated from each other by one or more of location or time. The controller is configured to examine the one or more of the route parameter or the vehicle parameter to determine whether the one or more of the route or the vehicle system is damaged. The system also includes examination equipment configured to continually monitor the one or more of the route or the vehicle system responsive to determining that the one or more of the route or the vehicle is damaged.

Systems and methods for automated detection of changes in extent of structures using imagery are disclosed, including a non-transitory computer readable medium storing computer executable code that when executed by a processor cause the processor to: align, with an image classifier model, a structure shape of a structure at a first instance of time to pixels within an aerial image depicting the structure captured at a second instance of time; assess a degree of alignment between the structure shape and the pixels, so as to classify similarities between the structure depicted within the pixels and the structure shape using a machine learning model to generate an alignment confidence score; and determine an existence of a change in the structure based upon the alignment confidence score indicating a level of confidence below a predetermined threshold level of confidence that the structure shape and the pixels within the aerial image are aligned.

The present application discloses a traffic monitoring method, an apparatus, a device, and a storage medium, relates to fields of autonomous driving, intelligent transportation, big data. The specific implementation is: acquiring road condition information and/or vehicle state information collected by a terminal device, where the terminal device is at least one of an unmanned vehicle and an unmanned aerial vehicle; performing a data analysis on the road condition information and/or the vehicle state information, and identifying a traffic event. Through the above procedure, monitoring efficiency of the traffic state is improved.

In one embodiment, a method is provided. The method comprises determining a first value of a coefficient of an edge-determining algorithm in response to a spatial resolution of a first image acquired with an image capture device onboard a vehicle, a spatial resolution of a second image, and a second value of the coefficient in response to which the edge-determining algorithm generated a second edge map corresponding to the second image. The method further comprises determining, with the edge-determining algorithm in response to the coefficient having the first value, at least one edge of at least one object in the first image. The method further comprises generating, in response to the determined at least one edge, a first edge map corresponding to the first image. The method further comprises determining at least one navigation parameter of the vehicle in response to the first and second edge maps.

A method includes confirming when a vehicle accesses a region of interest, obtaining data associated within the region of interest, and determining, based on analytics performed on the data obtained of the region of interest, whether one or more anomalies are present at the region of interest. Obtaining data includes at least one of collecting, with an imaging sensor associated with the vehicle, image data of a given point of interest within the region of interest or collecting, with a motion sensor associated with the vehicle, motion data of the vehicle in a given fragment of interest within the region of interest. The confirming, obtaining and determining steps are performed by at least one processing device comprising a processor operatively coupled to a memory.

The method for determining a geographic identifier including: determining a location description; determining parcel data; determining a georeferenced image based on the location description; generating a set of image features using the georeferenced image; optionally determining a built structure class; identifying a location of interest within the georeferenced image based on the set of features; determining a geographic identifier associated with the location of interest based on the image georeference; associating the geographic identifier with the location description; optionally returning the geographic identifier in response to the location description comprising an address; and optionally returning an address in response to the location description comprising a geographic coordinates.

An apparatus for correcting a road region includes a processor configured to segment a road region extracted from an aerial image and representing a road into a plurality of partial road regions; associate, for each of the partial road regions, the partial road region with a road section existing at the location of the partial road region, the road section being indicated by map information indicating locations of respective road sections; and correct the road region so as to cover, for each of the partial road regions, the road section corresponding to the partial road region.

Embodiments of a method and system described herein enable capture of video data streams from multiple, different video data source devices and the processing of the video data streams. The video data streams are merged such that various data protocols can all be processed with the same worker processors on different types of operating systems, which are typically distributed. In an embodiment the multiple video data sources comprises at least one mobile device executing a video sensing application that produces a video data stream for processing by video analysis worker processes. The processes include automatically detecting moving objects in a video data stream, and further tracking and analyzing the moving objects.