IP Library › Granted Patent US 11,248,912
Granted Patent B2
US 11,248,912 · App. 16/533,961 · Granted Feb 15, 2022

System and methods for simulations of vehicle-based item delivery

Inventors: Pramita Mitra (West Bloomfield, MI); David Melcher (Ypsilanti, MI); Abhishek Sharma (Ann Arbor, MI); Prashant Rao (Ypsilanti, MI); Amanuel Zeryihun (Pinole, CA)
Assignee: Ford Global Technologies, LLC
G01C21/20B64C39/024G05B13/042G06Q10/047G06Q10/08355B64C2201/027B64C2201/066B64C2201/128B64C2201/146
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Quick Facts
Patent No.
US 11,248,912
App. No.
16/533,961
Granted
Feb 15, 2022
Kind
B2
Abstract

Systems, methods, and computer-readable media are disclosed for simulations of vehicle-based item delivery. In some examples, a method can include generating a simulation of at least a portion of an environment in which items are to be delivered by a delivery vehicle; determining delivery locations associated with at least one delivery route for the delivery vehicle in the environment within the simulation; determining delivery location groups for the delivery location based on a delivery range of drones associated with the delivery vehicles; and determining waypoints for the delivery vehicle on the delivery route based on a minimum travel time associated with at least one drone of the drones.

Claims (69)

1. A device, comprising:

at least one memory device that stores computer-executable instructions; and

at least one processor configured to access the at least one memory device, wherein the at least one processor is configured to execute the computer-executable instructions to:

generate a simulation of at least a portion of an environment in which items are to be delivered by a delivery vehicle;

determine delivery locations associated with at least one delivery route for the delivery vehicle in the environment within the simulation;

determine delivery location groups for the delivery location based on a delivery range of drones associated with the delivery vehicles;

determine waypoints for the delivery vehicle on the delivery route based on a minimum travel time associated with at least one drone of the drones; and

generate a physics-based model that is based on at least one of an environmental parameter or a power capacity associated with the drone; and

generate second waypoints based on the physics-based model.

2. The device of claim 1 , wherein the physics-based model comprises at least one of a number of recharge cycles on a drone battery, a capacity of the drone battery, or an internal resistance of the drone battery.

3. The device of claim 1 , wherein determining the delivery location groups further comprises:

determining circles on a map, the circles having radii based on a delivery range of the drones available on the delivery vehicle;

determining overlap areas where two or more circles of the circles overlap; and

determining the delivery location groups that maximize a number of circles that overlap.

4. The device of claim 1 , wherein determining the waypoints comprises:

determining a circle of a smallest radius on a map that encompasses the delivery locations; and

determining a waypoint of the waypoints at a center of the circle.

5. The device of claim 1 , wherein the computer-executable instructions further comprise instructions to:

determine that a distance between the delivery location groups is below a predetermined threshold; and

determine a waypoint of the waypoints at an approximate location of a centroid of a polygon comprising vertices formed by the delivery locations in the delivery location group.

6. The device of claim 1 , wherein the computer-executable instructions further comprise instructions to:

present a graphical user interface for the simulation that comprises a status of a delivery of an item to a delivery location of the delivery locations, a package state, and a drone operational state.

7. A method, comprising:

generating a simulation of at least a portion of an environment in which items are to be delivered by a delivery vehicle;

determining delivery locations associated with at least one delivery route for the delivery vehicle in the environment within the simulation;

determining delivery location groups for the delivery location based on a delivery range of drones associated with the delivery vehicles, wherein determining the delivery location groups further comprises:

determining circles on a map, the circles having radii based on a delivery range of the drones available on the delivery vehicle;

determining overlap areas where two or more circles of the circles overlap; and

determining the delivery location groups that maximize a number of circles that overlap; and

determining waypoints for the delivery vehicle on the delivery route based on a minimum travel time associated with at least one drone of the drones.

8. The method of claim 7 , wherein the method further comprises:

generating a physics-based model that is based on at least one of an environmental parameter or a power capacity associated with the drone; and

generating second waypoints based on the physics-based model.

9. The method of claim 8 , wherein the physics-based model comprises at least one of a number of recharge cycles on a drone battery, a capacity of the drone battery, or an internal resistance of the drone battery.

10. The method of claim 7 , wherein determining the waypoints comprises:

determining a circle of a smallest radius on a map that encompasses the delivery locations; and

determining a waypoint of the waypoints at a center of the circle.

11. The method of claim 7 , wherein the computer-executable instructions further comprise instructions to:

determine that a distance between the delivery location groups is below a predetermined threshold; and

determine a waypoint of the waypoints at an approximate location of a centroid of a polygon comprising vertices formed by the delivery locations in the delivery location group.

12. The method of claim 7 , wherein the computer-executable instructions further comprise instructions to:

present a graphical user interface for the simulation that comprises a status of a delivery of an item to a delivery location of the delivery locations, a package state, and a drone operational state.

13. A non-transitory computer-readable medium storing computer-executable instructions which, when executed by a processor, cause the processor to perform operations comprising:

generating a simulation of at least a portion of an environment in which items are to be delivered by a delivery vehicle;

determining delivery locations associated with at least one delivery route for the delivery vehicle in the environment within the simulation;

determining delivery location groups for the delivery location based on a delivery range of drones associated with the delivery vehicles; and

determining waypoints for the delivery vehicle on the delivery route based on a minimum travel time associated with at least one drone of the drones, wherein determining the waypoints comprises:

determining a circle of a smallest radius on a map that encompasses the delivery locations; and

determining a waypoint of the waypoints at a center of the circle.

14. The non-transitory computer-readable medium of claim 13 , wherein the computer-executable instructions further comprise computer-executable instructions to:

generate a physics-based model that is based on at least one of an environmental parameter or a power capacity associated with the drone; and

generate second waypoints based on the physics-based model.

15. The non-transitory computer-readable medium of claim 14 , wherein the physics-based model comprises at least one of a number of recharge cycles on a drone battery, a capacity of the drone battery, or an internal resistance of the drone battery.

16. The non-transitory computer-readable medium of claim 13 , wherein determining the delivery location groups further comprises:

determining circles on a map, the circles having radii based on a delivery range of the drones available on the delivery vehicle;

determining overlap areas where two or more circles of the circles overlap; and

determining the delivery location groups that maximize a number of circles that overlap.

17. The non-transitory computer-readable medium of claim 13 , wherein the computer-executable instructions further comprise instructions to:

determine that a distance between the delivery location groups is below a predetermined threshold; and

determine a waypoint of the waypoints at an approximate location of a centroid of a polygon comprising vertices formed by the delivery locations in the delivery location group.

18. A device, comprising:

at least one memory device that stores computer-executable instructions; and

at least one processor configured to access the at least one memory device, wherein the at least one processor is configured to execute the computer-executable instructions to:

generate a simulation of at least a portion of an environment in which items are to be delivered by a delivery vehicle;

determine delivery locations associated with at least one delivery route for the delivery vehicle in the environment within the simulation;

determine delivery location groups for the delivery location based on a delivery range of drones associated with the delivery vehicles;

determine waypoints for the delivery vehicle on the delivery route based on a minimum travel time associated with at least one drone of the drones;

determine that a distance between the delivery location groups is below a predetermined threshold; and

determine a waypoint of the waypoints at an approximate location of a centroid of a polygon comprising vertices formed by the delivery locations in the delivery location group.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 12, 2020
From: MITRA, PRAMITA; MELCHER, DAVID; SHARMA, ABHISHEK; RAO, PRASHANT; ZERYIHUN, AMANUEL
To: FORD GLOBAL TECHNOLOGIES, LLC
Reel/Frame 052633/0288 →
Continuity (1)
Related Publication 20210041241A1 · Feb 11, 2021