A method of generating a roadway map includes receiving an image of a roadway. The method further includes identifying features in the roadway. The method further includes assigning a feature identification (FID) number to each of the identified features. The method further includes generating a score for each of the identified features based on a comparison between the identified features and a corresponding feature having a same FID number from a previously generated roadway map. The method further includes determining whether each of the identified features have changed based on whether the corresponding score exceeds a predetermined threshold. The method further includes updating the roadway map by changing identified features determined to have changed and maintaining identified features determined to have remain unchanged.

A method of generating a roadway map includes receiving an image of a roadway. The method further includes identifying features in the roadway. The method further includes assigning a feature identification (FID) number to each of the identified features. The method further includes generating a score for each of the identified features based on a comparison between the identified features and a corresponding feature having a same FID number from a previously generated roadway map. The method further includes determining whether each of the identified features have changed based on whether the corresponding score exceeds a predetermined threshold. The method further includes updating the roadway map by changing identified features determined to have changed and maintaining identified features determined to have remain unchanged.

A method of generating a roadway map includes receiving an image of a roadway. The method further includes performing a spectral analysis of the received image to determine reflectivity data for a plurality of wavelengths of light. The method further includes identifying a feature of the roadway in response to the determined reflectivity data exhibiting a reflection peak. The method further includes classifying the identified feature based on a size or a pitch of the exhibited reflection peak. The method further includes generating the roadway map based on the classification of the identified feature.

A method of generating a roadway map includes receiving an image of a roadway. The method further includes performing a spectral analysis of the received image to determine reflectivity data for a plurality of wavelengths of light. The method further includes identifying a feature of the roadway in response to the determined reflectivity data exhibiting a reflection peak. The method further includes classifying the identified feature based on a size or a pitch of the exhibited reflection peak. The method further includes generating the roadway map based on the classification of the identified feature.

A method of generating a first person view map includes receiving an image from above a roadway. The method further includes generating a road graph based on the received image, wherein the road graph comprises a plurality of road segments. The method further includes converting the received image using the road graph in order to generate a first person view image for each road segment of the plurality of road segments. The method further includes combining the plurality of road segments to define the first person view map.

A method of generating a first person view map includes receiving an image from above a roadway. The method further includes generating a road graph based on the received image, wherein the road graph comprises a plurality of road segments. The method further includes converting the received image using the road graph in order to generate a first person view image for each road segment of the plurality of road segments. The method further includes combining the plurality of road segments to define the first person view map.

A method of determining a roadway map includes receiving an image from above a roadway. The method further includes generating a skeletonized map based on the received image, wherein the skeletonized map comprises a plurality of roads. The method includes identifying intersections based on joining of multiple roads of the plurality of roads in the skeletonized map. The method includes partitioning the skeletonized map based on the identified intersections, wherein partitioning the skeletonized map defines a roadway data set and an intersection data set. The method includes analyzing the roadway data set to determine a number of lanes in each roadway of the plurality of roads. The method further includes analyzing the intersection data set to lane connections in the identified intersections. The method further includes merging results of the analyzed road data set and the analyzed intersection data set to generate the roadway map.

A method of determining a roadway map includes receiving an image from above a roadway. The method further includes generating a skeletonized map based on the received image, wherein the skeletonized map comprises a plurality of roads. The method includes identifying intersections based on joining of multiple roads of the plurality of roads in the skeletonized map. The method includes partitioning the skeletonized map based on the identified intersections, wherein partitioning the skeletonized map defines a roadway data set and an intersection data set. The method includes analyzing the roadway data set to determine a number of lanes in each roadway of the plurality of roads. The method further includes analyzing the intersection data set to lane connections in the identified intersections. The method further includes merging results of the analyzed road data set and the analyzed intersection data set to generate the roadway map.

Methods, systems and apparatus, including computer programs encoded on computer storage media for determining a center location of a ground control point used in aerial surveys. Machine learning models are used to identify in digital images pixel coordinates of the ground control point identified in the digital images. These image pixel coordinates are used in photogrammetric processing and software.

Methods, systems and apparatus, including computer programs encoded on computer storage media for determining a center location of a ground control point used in aerial surveys. Machine learning models are used to identify in digital images pixel coordinates of the ground control point identified in the digital images. These image pixel coordinates are used in photogrammetric processing and software.