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EP-4741768-A2 - PRIORITIZED PROVISION AND RETRIEVAL OF OFFLINE MAP DATA

EP4741768A2EP 4741768 A2EP4741768 A2EP 4741768A2EP-4741768-A2

Abstract

Provided are methods, systems, devices, and tangible non-transitory computer readable media for offline mapping and navigation. The disclosed technology determines a current region associated with a current location of a navigation device. Predicted travel destinations from the current region are determined based on aggregated travel data. The aggregated travel data can include previous travel destinations from within the current region. Based on the current region and the predicted travel destinations, additional regions associated with the current region are determined. Further, connectivity information is determined based on network data. The connectivity information is associated with network connectivity within the additional regions. The additional regions is prioritized based on the connectivity information. Furthermore, portions of offline map data associated with the respective additional regions are sent to the navigation device in an order partly based on the priority of the additional regions.

Inventors

  • RAISHER, Jordan Michael
  • MCLARNON, Brett Andrew

Assignees

  • Google LLC

Dates

Publication Date
20260513
Application Date
20191114

Claims (15)

  1. A computer-implemented method of providing offline maps, the computer-implemented method comprising: determining, by a computing system (130) comprising one or more processors (132), a current region (306; 504; 606) associated with a current location of a navigation device (102; 200; 302; 502; 602); determining, by the computing system (130), based at least in part on inputting aggregated travel data (208) into one or more machine-learned models (120; 140), predicted travel destinations from the current region (306; 504; 606); determining, by the computing system (130), based at least in part on the current region (306; 504; 606) and the predicted travel destinations, one or more additional regions (308; 508-522; 608) associated with the current region (306; 504; 606); determining, by the computing system (130), connectivity information based at least in part on network data (204), wherein the connectivity information is associated with network connectivity available to the navigation device (102; 200; 302; 502; 602) within each of the one or more additional regions (308; 508-522; 608); prioritizing, by the computing system (103), the one or more additional regions (308; 508-522; 608) based at least in part on the connectivity information; and sending, by the computing system (130), one or more portions of offline map data (206) associated with the respective one or more additional regions (308; 508-522; 608) to the navigation device (102; 200; 302; 502; 602) in an order based at least in part on a priority of the one or more additional regions (308; 508-522; 608).
  2. The computer-implemented method of claim 1, wherein the determining, by the computing system (130), the connectivity information based at least in part on the network data (204), wherein the connectivity information is associated with network connectivity available to the navigation device (102; 200; 302; 502; 602) within each of the one or more additional regions (308; 508-522; 608) comprises: inputting the network data (204) into the one or more machine-learned models (120; 140), wherein the one or more machine-learned models (120; 140) are configured to determine the connectivity information based on the network data (204).
  3. The computer-implemented method of claim 1 or claim 2, wherein the connectivity information comprises a likelihood of network throughput being above a threshold level at one or more locations within the one or more additional regions (308; 508-522; 608).
  4. The computer-implemented method of any one of the preceding claims, wherein the one or more machine-learned models (120; 140) are trained based on training data (162) comprising information associated with a state of networks in the current region (306; 504; 606) or a state of the one or more additional regions (308; 508-522; 608).
  5. The computer-implemented method of claim 4, wherein the training data (162) comprises previous travel destinations or previous locations of the navigation device (102; 200; 302; 502; 602).
  6. The computer-implemented method of any one of the preceding claims, wherein the determining, by the computing system, the connectivity information based at least in part on the network data, wherein the connectivity information is associated with network connectivity available to the navigation device within each of the one or more additional regions comprises: determining, by the computing system, when the one or more additional regions comprise a foreign region associated with a nationality different from the current location; and determining, by the computing system, the connectivity information based at least in part on aggregated foreign region data comprising information associated with an aggregated level of connectivity available within the foreign region.
  7. The computer-implemented method of claim 6, wherein the aggregated foreign region data is based at least in part on an average amount of the network connectivity provided by carrier networks within the foreign region.
  8. The computer-implemented method of any one of the preceding claims, wherein the network data comprises a size of each of the one or more portions of the offline map data associated with each of the one or more additional regions, one or more low connectivity zones in which the network throughput is below a network throughput threshold, a signal strength in one or more locations in each of the one or more additional regions, a signal to noise ratio in one or more locations in each of the one or more additional regions, or a network throughput in one or more locations in each of the one or more additional regions.
  9. The computer-implemented method of any one of the preceding claims, wherein the one or more additional regions (308; 508-522; 608) associated with the current region (306; 504; 606) comprise one or more additional regions (308; 508-522; 608) within a predetermined distance from the current region (306; 504; 606).
  10. The computer-implemented method of any one of the preceding claims, wherein the prioritizing, by the computing system (130), the one or more additional regions (308; 508-522; 608) based at least in part on the connectivity information comprises: increasing, by the computing system (130), the priority of the one or more additional regions (308; 508-522; 608) in which the network connectivity is below a predetermined network connectivity threshold, and/or determining, by the computing system (130), a data size of each of the one or more portions of the offline map data (206) and prioritizing, by the computing system (130), the one or more additional regions (308; 508-522; 608) based at least in part on the data size of each of the one or more portions of the offline map data (206).
  11. The computer-implemented method of any one of the preceding claims, wherein the aggregated travel data is anonymized to exclude identifying information associated with travel to the previous travel destinations.
  12. The computer-implemented method of any one of the preceding claims, wherein a size of each of the one or more additional regions (308; 508-522; 608) is directly correlated with a distance from the current location of the navigation device (102; 200; 302; 502; 602) to each of the one or more additional regions (308; 508-522; 608) respectively, and/or wherein each of the one or more additional regions (308; 508-522; 608) is respectively associated with one or more S2 cells or one or more Mercator tiles.
  13. The computer-implemented method of any one of the preceding claims, wherein the one or more machine-learned models (120; 140) comprise one or more neural networks.
  14. One or more tangible, non-transitory computer-readable media storing computer-readable instructions that when executed by one or more processors cause the one or more processors to perform the method of any of the preceding claims.
  15. A computing system comprising: one or more processors; one or more non-transitory computer-readable media storing instructions that when executed by the one or more processors cause the one or more processors to perform the method of any of claims 1 to 13.

Description

FIELD The present disclosure relates generally to a system for providing and retrieving offline data associated with geographic regions. BACKGROUND Operations associated with mapping information can be implemented on a variety of computing devices. These operations can include processing the mapping information for access and use by a user or computing system. Further, the operations can include sending and receiving data to remote computing systems. However, the types of operations and the ways in which the operations are performed can change over time, as can the underlying hardware that implements the operations. Accordingly, there are different ways to leverage computing resources associated with mapping information. SUMMARY Aspects and advantages of embodiments of the present disclosure will be set forth in part in the following description, or may be learned from the description, or may be learned through practice of the embodiments. One example aspect of the present disclosure is directed to a computer- implemented method of providing offline map data. The computer-implemented method can include determining, by a computing system including one or more processors, a current region associated with a current location of a navigation device. The computer-implemented method can include determining, by the computing system, based at least in part on aggregated travel data, predicted travel destinations from the current region. The aggregated travel data can include previous travel destinations from within the current region. The computer-implemented method can include determining, by the computing system, based at least in part on the current region and the predicted travel destinations, one or more additional regions associated with the current region. The computer-implemented method can include determining, by the computing system, connectivity information based at least in part on network data. The connectivity information can be associated with network connectivity available to the navigation device within each of the one or more additional regions. The computer-implemented method can include prioritizing, by the computing system, the one or more additional regions based at least in part on the connectivity information. Furthermore, the computer-implemented method can include sending, by the computing system, one or more portions of offline map data associated with the respective one or more additional regions to the navigation device in an order based at least in part on the priority of the one or more additional regions. Another example aspect of the present disclosure is directed to one or more tangible non-transitory computer-readable media storing computer-readable instructions that when executed by one or more processors cause the one or more processors to perform operations. The operations can include determining a current region associated with a current location of a navigation device. The operations can include determining, based at least in part on aggregated travel data, predicted travel destinations from the current region. The aggregated travel data can include previous travel destinations from within the current region. The operations can include determining, based at least in part on the current region and the predicted travel destinations, one or more additional regions associated with the current region. The operations can include determining connectivity information based at least in part on network data. The connectivity information can be associated with network connectivity available to the navigation device within each of the one or more additional regions. The operations can include prioritizing the one or more additional regions based at least in part on the connectivity information. Furthermore, the operations can include sending one or more portions of offline map data associated with the respective one or more additional regions to the navigation device in an order based at least in part on the priority of the one or more additional regions. Another example aspect of the present disclosure is directed to a computing system that can include: one or more processors; and one or more tangible non-transitory computer-readable media storing instructions that when executed by the one or more processors cause the one or more processors to perform operations. The operations can include determining a current region associated with a current location of a navigation device. The operations can include determining, based at least in part on aggregated travel data, predicted travel destinations from the current region. The aggregated travel data can include previous travel destinations from within the current region. The operations can include determining, based at least in part on the current region and the predicted travel destinations, one or more additional regions associated with the current region. The operations can include determining connectivity information based at least in par