An end-to-end system for data generation, map creation using the generated data, and localization to the created map is disclosed. Mapstreams—or streams of sensor data, perception outputs from deep neural networks (DNNs), and/or relative trajectory data—corresponding to any number of drives by any number of vehicles may be generated and uploaded to the cloud. The mapstreams may be used to generate map data—and ultimately a fused high definition (HD) map—that represents data generated over a plurality of drives. When localizing to the fused HD map, individual localization results may be generated based on comparisons of real-time data from a sensor modality to map data corresponding to the same sensor modality. This process may be repeated for any number of sensor modalities and the results may be fused together to determine a final fused localization result.

Described herein is a fibre optic sensing method and system for generating a dynamic digital representation of a plurality of objects and associated zones in a geographic area. In general, the disclosed method and system comprises (a) generating a zone feature dataset, including identifying and classifying the associated zones in the area, each zone being classified into a zone type based on static and/or quasi-static zone features and having at least two object-sensed conditions; (b) generating an object tracking dataset, including tracking signals of at least some of the plurality of objects in the geographic area using a distributed fibre optic sensing network, and processing the tracking signals to obtain object-specific tracking data; (c) generating an event dataset, including using the tracking data to determine when the conditions of the zones are changing; digitizing and storing the changed conditions of the zones; and (d) rendering a dynamic representation of the conditions of the zones. The disclosed method and system may be useful to deduce, represent and monitor object type, tracks, events and states of static and/or quasi-static features of the geographic area in a dynamic real-time digital model of the geographic area.

Third-party overlay data that includes customized graphics such as animations may be rendered on a base map using a hardware-accelerated framework. When third-party overlay data is deemed incompatible with a first version of a base map, features of the base map may be flexed to better accommodate the overlay data.

Systems and methods for aggregating and integrating distributed grid element inputs are disclosed. A data platform is provided for a distribution power grid. The data platform provides a crowd-sourced gaming system for identifying grid elements and determining dynamic electric power topology. The data platform also provides an interactive interface for displaying a view of a certain area with identified grid elements. The data platform communicatively connects to the identified grid elements, collects data from the identified grid elements, and manages the distribution power grid.

An end-to-end system for data generation, map creation using the generated data, and localization to the created map is disclosed. Mapstreams—or streams of sensor data, perception outputs from deep neural networks (DNNs), and/or relative trajectory data—corresponding to any number of drives by any number of vehicles may be generated and uploaded to the cloud. The mapstreams may be used to generate map data—and ultimately a fused high definition (HD) map—that represents data generated over a plurality of drives. When localizing to the fused HD map, individual localization results may be generated based on comparisons of real-time data from a sensor modality to map data corresponding to the same sensor modality. This process may be repeated for any number of sensor modalities and the results may be fused together to determine a final fused localization result.

A method, apparatus and computer program product are provided for generating a transition variability index related to autonomous driving. In this regard, a first transition variability index is calculated. The first transition variability index is indicative of a first degree of variability in relation to transition of vehicles from respective autonomous levels while traveling proximate a first spatial reference point. Furthermore, a second transition variability index is generated. The second transition variability index is indicative of a second degree of variability in relation to transition of vehicles from respective autonomous levels while traveling along proximate a second spatial reference point. Updating of transition data associated with one of the first and second spatial reference points relative to another one of the first and second spatial reference points is then prioritized based on a comparison between the first transition variability index and the second transition variability index.

A method generates map visualizations with multiple map layers. A user selects a data source with geographic data. A device displays a data visualization user interface, including a schema information region with data fields, and shelf regions that defining characteristics for a data visualization. The user selects a first geographic data, and the user interface generates a map data visualization using coordinates associated with the first geographic data field. The visualization includes a first plurality of data marks in a first layer. The user selects a second geographic data field. In response, the user interface displays a new layer icon. Upon activation of the new layer icon by the second geographic data field, the user interface superimposes a second layer over the existing map data visualization to form an updated map data visualization. The second layer includes a second plurality of data marks corresponding to the second geographic data field.

A method, apparatus, and user interface for a vehicle window damage detection system comprising obtaining image data of at least one vehicle window and determining a window damage indicator based on the obtained image data, identifying one or more road segments, and associating the determined window damage indicator with one or more identified road segments to update a map layer of a geographic database.

The present disclosure is directed to systems and methods for providing a stable topological representation of pathway networks as well as features associated with these networks. The disclosure is exemplified using road networks which have applications in mapping, navigation, and autonomous vehicles. Extensions may be learned through practice of the disclosure. Utilizing implementations disclosed herein may provide advantages for data conflation between different mapping systems and map data while improving overall stability by developing a common reference standard that is tied to semantic features rather than abstract geographic representations.

An approach is provided for requesting a map update based on an accident and/or damaged/malfunctioning sensors to allow a vehicle to continue driving. The approach involves determining, by one or more processors, a status of one or more sensors, one or more systems, or a combination thereof of a vehicle. The approach also involves transmitting, by the one or more processors, a request for a map update based on the status of the one or more sensors, the one or more systems, or a combination thereof of the vehicle. The approach further involves receiving, by the one or more processors, the map update in response to the request. The approach further involves configuring, by the one or more processors, at least one system of the vehicle to operate using the map update.