Abstract: Examples disclosed herein may involve a computing system configured to (i) maintain a map that is representative of a real-world environment, the map including a plurality of layers that are each encoded with a different type of map data, (ii) obtain sensor data indicative of a given area of the real-world environment, (iii) based on an evaluation of the obtained sensor data and map data corresponding to the given area, detect that a change has occurred in the given area, (iv) based on the collected sensor data, derive information about the change including at least a type of the change and a location of the change, (v) based on the derived information, determine that one or more layers of the map is impacted by the change, and (vi) effect an update to the one or more layers of the map based on the derived information.

Abstract: Examples disclosed herein may involve a computing system configured to (i) after one or more sensor-equipped vehicles have traversed a real-world environment and captured sensor data that is representative of the real-world environment, perform an analysis of the sensor data; (ii) based on the analysis of the sensor data, derive a set of information about a traffic light within the real-world environment that includes one or more of (a) signal-face information that comprises an identification of each signal face of the traffic light or (b) traffic-rule information that comprises an indication of at least one traffic rule that is applicable to the traffic light; and (iii) encode the derived set of information about the traffic light into a map for the real-world environment.

Abstract: Systems, methods, and non-transitory computer-readable media can determine contextual information describing at least one physical structure corresponding to a location based at least in part on data captured by one or more sensors of a vehicle. A set of candidate interaction points for the at least one physical structure can be determined based at least in part on the determined contextual information describing the at least one physical structure corresponding to the location. The set of candidate interaction points can be filtered to identify one or more interaction points. An interaction point can be selected from the one or more interaction points to use for stopping the vehicle.

Abstract: Examples disclosed herein may involve a computing system configured to (i) identify a stationary element in a real-world environment for which to infer information, (ii) detect a semantic relationship between the stationary element and one or more other stationary elements in the real-world environment, (iii) based on the detected semantic relationship, infer information about the stationary element, (iv) include the inferred information about the stationary element within a set of information that describes the stationary element.

Abstract: Examples disclosed herein may involve a computing system configured to (i) maintain a map that is representative of a real-world environment, the map including a plurality of layers that are each encoded with a different type of map data, (ii) obtain sensor data indicative of a given area of the real-world environment, (iii) based on an evaluation of the obtained sensor data and map data corresponding to the given area, detect that a change has occurred in the given area, (iv) based on the collected sensor data, derive information about the detected change including at least a type of the change and a location of the change, (v) based on the derived information about the detected change, determine that one or more layers of the map is impacted by the detected change, and (vi) effect an update to the one or more layers of the map based on the derived information about the change.

Abstract: Systems, methods, and non-transitory computer-readable media can determine contextual information describing at least one physical structure corresponding to a location based at least in part on data captured by one or more sensors of a vehicle. A set of candidate interaction points for the at least one physical structure can be determined based at least in part on the determined contextual information describing the at least one physical structure corresponding to the location. The set of candidate interaction points can be filtered to identify one or more interaction points. An interaction point can be selected from the one or more interaction points to use for stopping the vehicle.

Abstract: Examples disclosed herein may involve a computing system configured to (i) identify a stationary element in a real-world environment for which to infer information, (ii) detect a semantic relationship between the stationary element and one or more other stationary elements in the real-world environment, (iii) based on the detected semantic relationship, infer information about the stationary element, (iv) include the inferred information about the stationary element within a set of information that describes the stationary element.

Abstract: Systems, methods, and non-transitory computer-readable media can receive a starting location and a destination location. A route from the starting location to the destination location is determined. A video preview of the route is generated based on map data associated with the route. The video preview depicts one or more vehicles to be taken by a user traversing the route.

Abstract: Examples disclosed herein may involve a computing system that is operable to (i) identify a source map and a target map for transferring map data, where the source map and the target map have different respective coordinate frames and respective coverage areas that at least partially overlap, (ii) select a real-world element for which to transfer previously-created map data from the source map to the target map, (iii) select a source image associated with the source map in which the selected real-world element appears and has been labeled, (iv) select a target image associated with the target map in which the selected real-world element appears, (v) derive a geometric relationship between the source image and the target image, and (vi) use the derived geometric relationship between the source image and the target image to determine a position of the real-world element within the respective coordinate frame of the target map.

Abstract: Systems, methods, and non-transitory computer-readable media can determine map information defining a map, wherein the map comprises a plurality of regions. A quality level is assigned to each region of the plurality of regions based on map information available for that region. The quality level is associated with at least one of: a resolution metric, a volume metric, a recency metric, a verification metric, or an elegance metric associated with the map information available for that region. A first region of the plurality of regions is identified that is at risk of being downgraded to a lower quality level. Instructions are issued to one or more vehicles that cause the one or more vehicles to traverse the first region and capture sensor data within the first region.

Abstract: Systems, methods, and non-transitory computer-readable media can determine map information defining a map, wherein the map comprises a plurality of regions. A quality level is assigned to each region of the plurality of regions based on map information available for that region. The quality level is associated with at least one of: a resolution metric, a volume metric, a recency metric, a verification metric, or an elegance metric associated with the map information available for that region. A first region of the plurality of regions is identified that is at risk of being downgraded to a lower quality level. Instructions are issued to one or more vehicles that cause the one or more vehicles to traverse the first region and capture sensor data within the first region.

Abstract: Systems, methods, and non-transitory computer-readable media can determine map information defining a map, wherein the map comprises a plurality of regions. A quality level is assigned to each region of the plurality of regions based on map information available for that region. The quality level is associated with at least one of: a resolution metric, a volume metric, a recency metric, a verification metric, or an elegance metric associated with the map information available for that region. A first region of the plurality of regions is identified that is at risk of being downgraded to a lower quality level. Instructions are issued to one or more vehicles that cause the one or more vehicles to traverse the first region and capture sensor data within the first region.

Abstract: Systems, methods, and non-transitory computer-readable media can receive a starting location and a destination location. A route from the starting location to the destination location is determined. A video preview of the route is generated based on map data associated with the route. The video preview depicts one or more vehicles to be taken by a user traversing the route.

Abstract: Examples disclosed herein may involve a computing system configured to (i) maintain a map that is representative of a real-world environment, the map including a plurality of layers that are each encoded with a different type of map data, (ii) obtain sensor data indicative of a given area of the real-world environment, (iii) based on an evaluation of the obtained sensor data and map data corresponding to the given area, detect that a change has occurred in the given area, (iv) based on the collected sensor data, derive information about the detected change including at least a type of the change and a location of the change, (v) based on the derived information about the detected change, determine that one or more layers of the map is impacted by the detected change, and (vi) effect an update to the one or more layers of the map based on the derived information about the change.

Abstract: Examples disclosed herein may involve a computing system configured to (i) identify a stationary element in a real-world environment for which to infer information, (ii) detect a semantic relationship between the stationary element and one or more other stationary elements in the real-world environment, (iii) based on the detected semantic relationship, infer information about the stationary element, (iv) include the inferred information about the stationary element within a set of information that describes the stationary element.

Abstract: Examples disclosed herein may involve a computing system that is operable to (i) identify a source map and a target map for transferring map data, where the source map and the target map have different respective coordinate frames and respective coverage areas that at least partially overlap, (ii) select a real-world element for which to transfer previously-created map data from the source map to the target map, (iii) select a source image associated with the source map in which the selected real-world element appears and has been labeled, (iv) select a target image associated with the target map in which the selected real-world element appears, (v) derive a geometric relationship between the source image and the target image, and (vi) use the derived geometric relationship between the source image and the target image to determine a position of the real-world element within the respective coordinate frame of the target map.

Abstract: Systems, methods, and non-transitory computer-readable media can receive a starting location and a destination location. A route from the starting location to the destination location is determined. A video preview of the route is generated based on map data associated with the route. The video preview depicts one or more vehicles to be taken by a user traversing the route.

Abstract: Systems, methods, and non-transitory computer-readable media can determine map information defining a map, wherein the map comprises a plurality of regions. A quality level is assigned to each region of the plurality of regions based on map information available for that region. The quality level is associated with at least one of: a resolution metric, a volume metric, a recency metric, a verification metric, or an elegance metric associated with the map information available for that region. A first region of the plurality of regions is identified that is at risk of being downgraded to a lower quality level. Instructions are issued to one or more vehicles that cause the one or more vehicles to traverse the first region and capture sensor data within the first region.

Abstract: Systems, methods, and non-transitory computer-readable media can receive a starting location and a destination location. A route from the starting location to the destination location is determined. A video preview of the route is generated based on map data associated with the route. The video preview depicts one or more vehicles to be taken by a user traversing the route.

Abstract: Systems, methods, and non-transitory computer-readable media can determine contextual information describing at least one physical structure corresponding to a location based at least in part on data captured by one or more sensors of a vehicle. A set of candidate interaction points for the at least one physical structure can be determined based at least in part on the determined contextual information describing the at least one physical structure corresponding to the location. The set of candidate interaction points can be filtered to identify one or more interaction points. An interaction point can be selected from the one or more interaction points to use for stopping the vehicle.