Systems and methods for scheduling environment perception-based data offloading for numerous connected vehicles

1. A method for offloading data comprising:

capturing an image of a view of interest from a vehicle;

segmenting the image into a plurality of blocks;

determining a scheduling priority for each of one or more blocks among the plurality of blocks based on block values, wherein the block values relate to one or more objects of interest contained in each of the one or more blocks; and

offloading, from the vehicle to a server, one or more blocks based on the scheduling priority of the one or more blocks.

2. The method of claim 1 , further comprising, before determining the scheduling priority:

generating, by the server, a global map based on a plurality of images from a plurality of vehicles;

identifying, by the server, a plurality of objects in the global map; and

identifying, by the server, a plurality of objects of interest among the plurality of objects.

3. The method of claim 1 , further comprising:

identifying, by the server, a first set of vehicles among a plurality of vehicles based on localization data related to the first set of vehicles; and

grouping, by the server, the identified first set of vehicles to form a coarse grouping including the vehicle.

4. The method of claim 3 , further comprising:

identifying a second set of vehicles within the coarse grouping having a shared object of interest; and

grouping the identified second set of vehicles to form a fine grouping including the vehicle.

5. The method of claim 1 , further comprising calculating the block values for the one or more blocks among the plurality of blocks based on parameters for each of the one or more blocks.

6. The method of claim 5 , wherein the parameters include a number of objects, an object type, an object speed, or combinations thereof.

7. The method of claim 1 , wherein determining the scheduling priority for each of one or more blocks among the plurality of blocks is based on the block values of one or more blocks such that a higher block value corresponds to a higher scheduling priority.

8. The method of claim 1 , further comprising:

calculating an average block value for each vehicle among a plurality of vehicles; and

scheduling offloading by one or more vehicles among the plurality of vehicles based on the average block values.

9. The method of claim 1 , wherein determining the scheduling priority for each of one or more blocks among the plurality of blocks further comprises:

determining a block coverage for each of the one or more blocks; and

optimizing the scheduling priority according to a maximization function of the block values and the block coverage as weighted by a set of quality of service requirements.

10. The method of claim 1 , further comprising, before offloading:

identifying a block among the one or more blocks that includes redundant information; and

removing the block from the one or more blocks.

11. A system for offloading data comprising a processor operable to:

capture an image of a view of interest from a vehicle;

segment the image into a plurality of blocks;

determine a scheduling priority for each of one or more blocks among the plurality of blocks based on block values, wherein the block values relate to one or more objects of interest contained in each of the one or more blocks; and

offload, from the vehicle to a server, one or more blocks based on the scheduling priority of the one or more blocks.

12. The system of claim 11 , wherein the processor is further operable to, before determining the scheduling priority:

generate, by the server, a global map based on a plurality of images from a plurality of vehicles;

identify, by the server, a plurality of objects in the global map; and

identify, by the server, a plurality of objects of interest among the plurality of objects.

13. The system of claim 11 , wherein the processor is further operable to:

identify, by the server, a first set of vehicles among a plurality of vehicles based on localization data related to the first set of vehicles; and

group, by the server, the identified first set of vehicles to form a coarse grouping including the vehicle.

14. The system of claim 13 , wherein the processor is further operable to:

identify a second set of vehicles within the coarse grouping having a shared object of interest; and

group the identified second set of vehicles to form a fine grouping including the vehicle.

15. The system of claim 11 , wherein determining the scheduling priority for each of one or more blocks among the plurality of blocks further comprises:

determining a block coverage for each of the one or more blocks; and

optimizing the scheduling priority according to a maximization function of the block values and the block coverage as weighted by a set of quality of service requirements.

16. The system of claim 11 , wherein the processor is further operable to, before offloading:

identify a block among the one or more blocks that includes redundant information; and

remove the block from the one or more blocks.

17. A server comprising:

a controller programmed to:

group a plurality of vehicles;

obtain images from the plurality of vehicles, each of the images corresponding to one of the plurality of vehicles and having a plurality of blocks;

obtain an image value of each of the images based on one or more objects of interest contained in each of the images;

determine scheduling priorities for the plurality of vehicles based on the image values; and

instruct the plurality of vehicles to offload data based on the scheduling priorities.

18. The server of claim 17 , wherein the controller is further programmed to:

determine a block value of each block included in an image among the images based on one or more objects of interest contained in each of the blocks;

determine scheduling priorities for the blocks based on the block values; and

instruct the vehicle corresponding to the image to offload blocks based on the scheduling priorities for the plurality of blocks.

19. The server of claim 18 , wherein the controller is further programmed to:

optimize the scheduling priorities for the plurality of vehicles and the scheduling priorities for the plurality of blocks such that a total of the block values of blocks received by the server is maximized.

20. The server of claim 17 , wherein the controller is configured to:

obtain the image value of each of the images based on an average of block values of the corresponding image.