IP Library › Granted Patent US 11,753,040
Granted Patent B1
US 11,753,040 · App. 17/208,724 · Granted Sep 12, 2023

Autonomous vehicle delivery

Inventors: Ryan Gammelgard (Bloomington, IL); Justin Davis (Normal, IL)
Assignee: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
B60W60/00256G01C21/3407G05D1/0016G05D1/0212G05D1/0287G06Q10/047G06Q10/06315G06Q50/28B60W2540/21B64U10/13B64U2101/60G10L15/22
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Quick Facts
Patent No.
US 11,753,040
App. No.
17/208,724
Granted
Sep 12, 2023
Kind
B1
Abstract

Autonomous vehicle methods and systems are described herein for communicating with an autonomous or semi-autonomous vehicle to remotely control operation of the vehicle, to detect and remove unauthorized passengers, to deliver loads, to receive registration information for the vehicle, to provide accessibility information to the vehicle, and/or to receive sensor or other environmental data to integrate with an electronic game or other extended reality experience.

Claims (69)

1. A computer-implemented method for optimizing delivery routes and delivering loads using a combination of one or more autonomous or semi-autonomous vehicles and one or more drones, comprising:

determining, by one or more processors, a destination location for transporting a first load from a starting location;

determining, by the one or more processors, a first route for one or more autonomous or semi-autonomous vehicles to transport the first load;

causing, by the one or more processors, the autonomous or semi-autonomous vehicle to transport the first load to the destination location along the first route;

determining, by the one or more processors and after the autonomous or semi-autonomous vehicle has begun to transport the first load, that a second load is to be transported from the starting location to the destination location;

determining, by the one or more processors, a second route for one or more drones to transport the second load to the autonomous or semi-autonomous vehicle at an intermediate location that intersects with the first route; and

causing, by the one or more processors, the one or more drones to transport the second load along the second route to the autonomous or semi-autonomous vehicle at the intermediate location.

2. The computer-implemented method of claim 1 , wherein:

the first route is determined based upon at least one of: (i) geographical data for a geographic area including the starting location and the destination location, or (ii) one or more vehicle characteristics of the one or more autonomous or semi-autonomous vehicles; and

the second route is determined based upon at least one of: (i) the geographical data and (ii) one or more vehicle characteristics of the one or more drones.

3. The computer-implemented method of claim 1 , wherein the one or more drones are one or more first drones and further comprising causing, by the one or more processors, the one or more autonomous or semi-autonomous vehicles to transport one or more second drones along the first route.

4. The computer-implemented method of claim 3 , further comprising:

determining, by the one or more processors, a third route for the one or more second drones to transport the first or second loads, wherein the third route intersects with the first route at a drop-off location; and

causing, by the one or more processors, the one or more second drones to transport the first or second loads from the drop-off location to the destination location along the third route.

5. The computer-implemented method of claim 4 , wherein:

the drop-off location is adjacent to the destination location; and

the one or more second drones transport the first or second loads to an entrance of the destination location.

6. The computer-implemented method of claim 1 , further comprising:

in response to the one or more drones transporting at least the second load, receiving a verbal command directed to the one or more drones; and

performing, by the or more drones, one or more tasks based upon the verbal command.

7. The computer-implemented method of claim 1 , further comprising:

determining, by the one or more processors, one or more physical characteristics of the second load;

determining, by the one or more processors, a number of drones necessary to deliver the second load to the intermediate location within a user-determined time frame based upon the one or more physical characteristics of the second load; and

determining, by the one or more processors, whether the autonomous or semi-autonomous vehicle is capable of carrying the first and second loads and the determined number of drones based upon at least the one or more physical characteristics of the first and second loads.

8. A computer system configured to optimize delivery routes and deliver loads using a combination of one or more autonomous or semi-autonomous vehicles and one or more drones, the computer system comprising one or more local or remote processors, transceivers, and/or sensors configured to:

determine a destination location for transporting a first load from a starting location;

determine a first route for one or more autonomous or semi-autonomous vehicles to transport the first load;

cause the autonomous or semi-autonomous vehicle to transport the first load to the destination location along the first route;

determine, after the autonomous or semi-autonomous vehicle has begun to transport the first load, that a second load is to be transported from the starting location to the destination location;

determine a second route for one or more drones to transport the second load to the autonomous or semi-autonomous vehicle at an intermediate location that intersects with the first route; and

cause the one or more drones to transport the second load along the second route to the autonomous or semi-autonomous vehicle at the intermediate location.

9. The computer system of claim 8 , wherein:

the first route is determined based upon at least one of: (i) geographical data for a geographic area including the starting location and the destination location, or (ii) one or more vehicle characteristics of the one or more autonomous or semi-autonomous vehicles; and

the second route is determined based upon at least one of: (i) the geographical data and (ii) one or more vehicle characteristics of the one or more drones.

10. The computer system of claim 8 , wherein the one or more drones are one or more first drones and the one or more local or remote processors, transceivers, and/or sensors are further configured to cause the one or more autonomous or semi-autonomous vehicles to transport one or more second drones along the first route.

11. The computer system of claim 10 , wherein the one or more local or remote processors, transceivers, and/or sensors are further configured to:

determine a third route for the one or more second drones to transport the first or second loads, wherein the third route intersects with the first route at a drop-off location; and

cause the one or more second drones to transport the first or second loads from the drop-off location to the destination location along the third route.

12. The computer system of claim 11 , wherein:

the drop-off location is adjacent to the destination location; and

the one or more second drones transport the first or second loads to an entrance of the destination location.

13. The computer system of claim 8 , wherein the one or more local or remote processors, transceivers, and/or sensors are further configured to:

in response to the one or more drones transporting at least the second load, receive a verbal command directed to the one or more drones; and

perform, by the or more drones, one or more tasks based upon the verbal command.

14. The computer system of claim 8 , wherein the one or more local or remote processors, transceivers, and/or sensors are further configured to:

determine one or more physical characteristics of the second load;

determine a number of drones necessary to deliver the second load to the intermediate location within a user-determined time frame based upon the one or more physical characteristics of the second load; and

determine whether the autonomous or semi-autonomous vehicle is capable of carrying the first and second loads and the determined number of drones based upon at least the one or more physical characteristics of the first and second loads.

15. A non-transitory computer-readable medium storing thereon a set of instructions that, when executed by one or more processors, causes the one or more processors to:

determine a destination location for transporting a first load from a starting location;

determine a first route for one or more autonomous or semi-autonomous vehicles to transport the first load;

cause the autonomous or semi-autonomous vehicle to transport the first load to the destination location along the first route;

determine, after the autonomous or semi-autonomous vehicle has begun to transport the first load, that a second load is to be transported from the starting location to the destination location;

determine a second route for one or more drones to transport the second load to the autonomous or semi-autonomous vehicle at an intermediate location that intersects with the first route; and

cause the one or more drones to transport the second load along the second route to the autonomous or semi-autonomous vehicle at the intermediate location.

16. The non-transitory computer-readable medium of claim 15 , wherein:

the first route is determined based upon at least one of: (i) geographical data for a geographic area including the starting location and the destination location, or (ii) one or more vehicle characteristics of the one or more autonomous or semi-autonomous vehicles; and

the second route is determined based upon at least one of: (i) the geographical data and (ii) one or more vehicle characteristics of the one or more drones.

17. The non-transitory computer-readable medium of claim 15 , wherein the one or more drones are one or more first drones and the instructions further cause the one or more processors to cause the one or more autonomous or semi-autonomous vehicles to transport one or more second drones along the first route.

18. The non-transitory computer-readable medium of claim 17 , wherein the instructions further cause the one or more processors to:

determine a third route for the one or more second drones to transport the first or second loads, wherein the third route intersects with the first route at a drop-off location; and

cause the one or more second drones to transport the first or second loads from the drop-off location to the destination location along the third route.

19. The non-transitory computer-readable medium of claim 18 , wherein:

the drop-off location is adjacent to the destination location; and

the one or more second drones transport the first or second loads to an entrance of the destination location.

20. The non-transitory computer-readable medium of claim 15 , wherein the instructions further cause the one or more processors to:

determine one or more physical characteristics of the second load;

determine a number of drones necessary to deliver the second load to the intermediate location within a user-determined time frame based upon the one or more physical characteristics of the second load; and

determine whether the autonomous or semi-autonomous vehicle is capable of carrying the first and second loads and the determined number of drones based upon at least the one or more physical characteristics of the first and second loads.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 30, 2021
From: GAMMELGARD, RYAN; DAVIS, JUSTIN
To: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
Reel/Frame 055769/0300 →
Continuity (2)
Provisional Application 63159772 · Mar 11, 2021
Provisional Application 63158968 · Mar 10, 2021
Cited By (3)
US 12,392,626 US 12,430,455 US 12,662,083