Abstract: A first set of traces is received by a device, each trace including a set of location data. Each set of location data includes an origin point, a plurality of intermediate points, and a destination point in an ordered sequence. A bounding box surrounding a trace of the first set of traces is drawn, the bounding box corresponding to endpoints of the trace. A function determines a threshold and classifies a trace as stationary or non-stationary. A trace is classified as stationary or non-stationary by comparing a ratio represented by the trace length divided by the bounding box diagonal length to the determined threshold. In response to classifying the trace as stationary, the trace is labeled as stationary. In response to classifying the trace as non-stationary, extremities are extracted from the trace for re-classifying.

Abstract: A process, and corresponding system for performing the process, is described for editing and representing property values for a digital map. The process stores a library of expressions for styling a digital map. The process retrieves electronic map data and displays a user interface including a property editor panel and a visual map portion. The property editor panel displays a plurality of map styles. The visual map portion displays a representation of the electronic map data. For a selected map style, the process displays a plurality of style properties and a text field for receiving expressions corresponding to a style property. The process receives, via the text field, an expression and determines a set of suggested expressions corresponding to the style property. The process applies the received expression to the electronic map data and renders in the visual map portion an edited representation of the electronic map data.

Abstract: A polygon Boolean operation and topology correction algorithm generates valid polygons despite polygon data containing self-intersecting polygons, overlapping polygons, polygons including a chain of holes, and/or polygons including complex intersections. A polygon Boolean operation and topology correction algorithm uses two variants of the Vatti algorithm along with a topology correction algorithm to address problematic areas within input data, such as the overlapping area shared between one or more polygons or a polygon having no area at all. Upon performing a variant of the Vatti algorithm to identify hot pixels within an arrangement of polygons, the polygon Boolean operation and topology correction algorithm runs a second variant of the Vatti algorithm to generate polygons within an integer coordinate system using snap-rounding.

Abstract: A process, and corresponding system for performing the process, is described herein for visual identification of label collision for a digital map. The process determines a set of labels to be rendered in a visual map corresponding to a digital map. For each label in the set, a label boundary is created around the label. If any of the label boundaries in the set of labels overlap, the process determines a display priority for each of the first label and the second label in an overlapping label pair. In response to the first label in the pair having a higher display priority than the second label in the pair, the boundary for the first label is rendered in a first visual style and the label boundary for the second label in a second visual style. As priorities or properties are changed, the visual map is updated to reflect the changes.

Abstract: A process, and corresponding system for performing the process, is described for editing and representing property values for a digital map. The process retrieves electronic map data from a style sheet corresponding to a vector map tile set for a digital map. The process displays a plurality of templates and receives selection of a template. The process displays a visual map representing the electronic map with the set of map style layers of the selected template. The process displays a theme and a plurality of components. Each component is a set of map style layers and is a subset of the set of map style layers of the template. The process receives selection of a component. The process displays a plurality of property values associated with the selected component. The process receives an edit to a property value. The process updates the visual map to reflect the edited property value.

Abstract: A mobile computing device receives an image from a camera physically located within a vehicle. The mobile computing device inputs the image into a convolutional model that generates a set of object detections and a set of segmented environment blocks in the image. The convolutional model includes subsets of encoding and decoding layers, as well as parameters associated with the layers. The convolutional model relates the image and parameters to the sets of object detections and segmented environment blocks. A server that stores object detections and segmented environment blocks is updated with the sets of object detections and segmented environment blocks detected in the image.

Abstract: A process, and corresponding system for performing the process, is described for editing and representing property values for a digital map. The process retrieves electronic map data from a style sheet corresponding to a vector map tile set for a digital map and displays map layer styles in a property editor panel, where each map style layer references a portion of the data and one or more visual style rules to apply to the portion. The process also displays a visual map with the map layer styles applied. Upon receiving selection of one or more map style layers from the plurality of map style layers, the process displays style layer properties and values corresponding to each. The process renders in the visual map only the selected one or more style layers marked as visible. As edits are made in the property editor panel, the visual map is updated to reflect the changes.

Abstract: An augmented reality (AR) module receives a location notification including a current location from a client device. The AR module determines a set of geographic vector data within a threshold distance of the current location of the client device. The AR module identifies a set of candidate geometries within the geographic vector data. The AR module identifies a set of content items presentable at candidate geometries. The AR module translates the set of geographic vector data into an AR world view based on the current location of the client device. The AR world view includes a candidate geometry presenting a content item.

Abstract: Digital data corresponding to a trace by a device is received. The digital data includes location data and time data obtained over a period of time and representing movement of the device. A set of derived values for the plurality of metrics is calculated from the sets of values corresponding to the metrics, and the set of derived values is input to a neural network classification model to determine whether the received digital data represents movement of a first type. In response to determining that the digital data represents movement of the first type, the received digital data corresponding to the trace is labelled with the first type of movement.

Abstract: A vector tile generator receives map features from a database of raw map data. Each map feature includes geometry data and property data. The vector tile generator stores the property data in a property store. The vector tile generator generates, based on the geometry data, a set of zoom data organized into a plurality of zoom levels. Each zoom level includes at least some of the map features. The vector tile generator maps the map features of the set of zoom data to a plurality of tiles that includes a set of tiles for each of the zoom levels. For each tile, the vector tile generator clips map features mapped to the tile based on a boundary of the tile, encodes the clipped map features to a vector format, and merges the encoded clipped map features with the stored property data corresponding to the map features in the tile.

Abstract: A method for avoiding likely one-way segments of roads in route planning is described. In selecting an optimal route, the cost of a possible route is computed by adding the costs associated with the segments along the route. Cost is a metric that is associated with the total expense to traverse a route in order to determine whether the route should be chosen over another. Each segment of a road is associated with a cost factor that represents the traffic condition of the segment. For a given segment, automobile traces that traveled the segment are counted. A ratio of traces traveled in one direction to traces traveled in the opposite direction is determined. If the ratio is below a certain threshold, the segment of the road is regarded as likely one-way. The original cost factor is replaced with a new cost factor that penalizes the segment in routing calculations.

Abstract: Efficiently generating terrain openness involves a digital elevation model comprising a texture representing a first geographic area and at least part of a plurality of mipmap levels representing geographic areas bordering the first geographic area. The texture and mipmap levels include pixels encoding elevation values for locations of geographic areas. For each pixel of the texture, derivatives are determined, as well as an openness factor based at least in part on the elevations at one or more pixels of the mipmap levels. The derivatives and openness factor are added to the texture. A hill shading factor is determined for each pixel based at least in part on the derivatives. An electronic map of the first geographic area is rendered using the openness and hill shading factors of each pixel of the texture. The rendering is sent for display.

Abstract: Techniques are described for efficient label insertion and collision handling. A bounding geometry for a label to be graphically displayed on a display screen as part of an electronic map is determined, wherein the bounding geometry comprises a circle. The bounding geometry is inserted into a grid index, wherein the grid index represents a viewport of the electronic map. Disjoint regions of the grid index intersected by the bounding geometry are identified, wherein each disjoint region represents a different portion of the viewport. For each intersected disjoint region, it is identified whether there is at least one collision between the bounding geometry and one or more existing bounding geometries in the disjoint region; and responsive to identifying whether there is at least one collision in the intersected disjoint region, a target opacity of the label is set.

Abstract: Techniques are described for efficient duplicate label handling. A vector tile is added to a render tree of an electronic map, the vector tile comprising a first set of labels. A vector tile family of the vector tile is identified, each vector tile of the family comprising a second set of labels. For each label of the first set, for each vector tile in the vector tile family, second labels from the second set are identified, and for each identified label, coordinates of the label of the first set are compared to coordinates of the identified label to determine whether the coordinates are within a threshold similarity of each other. Responsive to the determination, the label of the first set of labels is associated with an identifier with which the identified label is associated.

Abstract: A feature extraction system extracts map features from an aerial image. The feature extraction system receives an aerial image having pixels and predicts, for each pixel, a probability that the pixel corresponds to a map feature based on a machine learning model. The machine learning model is trained to determine a probability that a pixel corresponds to the map feature based on a training dataset comprising pairs of aerial images and corresponding mask images that describe known instances of the map feature. The feature extraction system identifies a subset of pixels of the plurality of pixels. Each pixel in the subset has a predicted probability that is greater than or equal to a threshold probability that a pixel corresponds to the map feature. The feature extraction system further determines a bounded geometry enclosing the identified subset of pixels, the bounding geometry encompassing an instance of the map feature.

Abstract: In an embodiment, a data processing method providing an improvement in filtering telemetry data received from mobile devices comprises receiving, from a mobile device, telemetry data comprising a plurality of probes, each probe identifying a location of the mobile device at a time of the probe, wherein the plurality of probes form first digital trace data identifying a path of the mobile device; determining, for a particular probe of the plurality of probes, a first attribute of the particular probe; determining whether the first attribute of the particular probe satisfies a first threshold; in response to satisfying the first threshold, deleting the particular probe from the plurality of probes and dividing the first digital trace data into second digital trace data and third digital trace data; performing an action using the second digital trace data and the third digital trace data.

Abstract: An oblique imagery application receives an oblique image captured by an oblique camera at a non-orthogonal angle with respect to a ground plane and map data including a map tile corresponding to geographic coordinates. A principal axis is determined that is orthogonal to an image plane defined by the oblique image and intersecting a center of the oblique image. For each pixel of the oblique image, a pixel vector is determined and a set of deviation coordinates based on a deviation of the pixel vector from the principal axis is determined for the pixel, with the pixel vector of a pixel passing through a focal point of the oblique camera and ending at the pixel. The map tile is associated to the pixels of the oblique image based on the camera parameters, the deviation coordinates of the pixels, the oblique camera parameters, and the geographic coordinates of the map tile.

Abstract: A method for providing an improvement in speed estimation for route planning involves identifying a plurality of observed speeds for a segment of road during a first time period, the plurality of observed speeds corresponding to the plurality of traces of the segment of road. The method further involves identifying a plurality of discrete values in the plurality of observed speeds, and determining a count for each of the plurality of discrete values. The method further involves aggregating the counts for the plurality of traces including the segment to create aggregated counts for the segment, and determining the speed estimate from the aggregated counts for the plurality of traces including the segment.

Abstract: A system determines spatial locations of pixels of an image. The system includes a processor configured to: receive location data from devices located within a hotspot; generate a density map for the hotspot including density pixels associated with spatial locations defined by the location data, each density pixel having a value indicating an amount of location data received from an associated spatial location; match the density pixels of the density map to at least a portion of the pixels of the image; and determine spatial locations of the at least a portion of the pixels of the image based on the spatial locations of the matching density pixels of the density map. In some embodiments, the image and density map are converted to edge maps, and a convolution is applied to the edge maps to match the density map to the pixels of the image.

Abstract: A trace comprising location data about a computing device is received at a mapping server, where the trace stores the location data about the computing device in an ordered set of points. The origin and destination of the trace are obscured. Then, the trace is then separated into a set of subtraces by dividing the received points of location data into a set of subtraces, and removing the links between subtraces of the set of subtraces. For example, subtraces can be divided based on size, distance, elapsed time, or features of interest present in the location data.