IP Library Granted Patent US 12,217,213
Granted Patent B2
US 12,217,213 · App. 18/467,420 · Granted Feb 4, 2025

Systems and methods for adaptive route optimization for learned task planning

Inventors: Ryan Michael Gross (Normal, IL); Jody Ann Thoele (Bloomington, IL); Joseph Robert Brannan (Bloomington, IL); Eric R. Moore (Heyworth, IL)
Assignee: State Farm Mutual Automobile Insurance Company
G06Q10/10G01C21/3484G06F16/245G06F16/29G06Q10/047G06Q30/0205G06Q40/08G06Q50/14G06N20/00
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,217,213
App. No.
18/467,420
Filed
Sep 14, 2023
Granted
Feb 4, 2025
Kind
B2
Art Unit
3691
USPC
705/4
Abstract

An adaptive mapping (AM) computing device having at least one processor in communication with at least one memory device is provided. The AM computing device may be configured to retrieve a plurality of tasks associated with a user, and retrieve geographic mapping data. The AM computing device may also generate a route model based upon the retrieved plurality of tasks and the retrieved geographic mapping data. The AM computing device may execute the route model to determine an optimal route, and transmit, to the user, an optimized travel plan based upon the optimal route.

Claims (54)

1. An adaptive mapping computing device comprising:

at least one processor in communication with at least one non-transitory memory device, wherein the at least one processor is configured to:

generate a route model based upon a plurality of tasks associated with a user, preferred modes of transportation of the user, and geographic mapping data including a starting location of the user;

execute the route model to determine an optimized travel plan for the user including an optimal route and one or more optimal modes of transportation for the optimal route;

receive, from a user computing device associated with the user, geolocation data of the user computing device indicating a real-time location of the user;

continuously receive and analyze real-time information from one or more data sources and the geolocation data from the user computing device to continuously update the optimized travel plan in real-time, thereby enabling the adaptive mapping computing device to perform, in real-time, continuous and adaptive route pathing and transportation mode selection based upon the real-time location of the user, fluctuating conditions, and merchant information associated with the plurality of tasks and a plurality of merchants;

retrieve and analyze the merchant information to select an optimal order of travel to each task location associated with the plurality of tasks, wherein analyzing the merchant information includes comparing (a) at least one of services or products offered by the plurality of merchants to the plurality of tasks, and (b) one or more locations of each of the plurality of merchants to the optimal order of travel;

transmit, to the user computing device, the updated optimized travel plan including the selected optimal order of travel;

provide a computer application configured to display, on a user interface of the user computing device, the updated optimized travel plan including the selected optimal order of travel; and

execute the computer application, wherein executing the computer application includes displaying the updated optimized travel plan including the selected optimal order of travel on the user interface of the user computing device.

2. The computing device of claim 1 , wherein the plurality of tasks and the preferred modes of transportation, and the geographic mapping data are retrieved from at least one database.

3. The computing device of claim 1 , wherein the at least one processor is further configured to execute the route model to determine the optimal route and the one or more optimal modes of transportation, the one or more optimal modes of transportation available at the starting location of the user.

4. The computing device of claim 1 , wherein the real-time information includes at least one of real-time weather data or real-time traffic data.

5. The computing device of claim 1 , wherein the at least one processor is further configured to:

provide the computer application configured to display, on the user interface of the user computing device, the updated optimized travel plan overlaid on a map.

6. The computing device of claim 1 , wherein the at least one processor is further configured to generate the route model based upon traffic data and weather data.

7. The computing device of claim 1 , wherein the at least one processor is further configured to:

generate a task model associated with the user, wherein the task model is based upon one of tasks input by the user and predicted tasks determined from historical data associated with the user, the historical data including previous tasks planned for the user; and

generate the route model based upon risk data associated with at least one of the user or estimated routes associated with the plurality of tasks.

8. A computer-implemented method implemented by an adaptive mapping computing device having at least one processor in communication with at least one non-transitory memory device, the method comprising:

generating a route model based upon a plurality of tasks associated with a user, preferred modes of transportation of the user, and geographic mapping data including a starting location of the user;

executing the route model to determine an optimized travel plan for the user including and optimal route and one or more optimal modes of transportation for the optimal route;

receiving, from a user computing device associated with the user, geolocation data of the user computing device indicating a real-time location of the user;

continuously receiving and analyzing real-time information from one or more data sources and the geolocation data from the user computing device to continuously update the optimized travel plan in real-time, thereby enabling the adaptive mapping computing device to perform, in real-time, continuous and adaptive route pathing and transportation mode selection based upon the real-time location of the user, fluctuating conditions, and merchant information associated with the plurality of tasks and a plurality of merchants;

retrieving and analyzing the merchant information to select an optimal order of travel to each task location associated with the plurality of tasks, wherein analyzing the merchant information comprises comparing (a) at least one of services or products offered by the plurality of merchants to the plurality of tasks, and (b) one or more locations of each of the plurality of merchants to the optimal order of travel;

transmitting, to the user computing device, the updated optimized travel plan including the selected optimal order of travel;

providing a computer application configured to display, on a user interface of the user computing device, the updated optimized travel plan including the selected optimal order of travel; and

executing the computer application, wherein executing the computer application comprises displaying the updated optimized travel plan including the selected optimal order of travel on the user interface of the user computing device.

9. The computer-implemented method of claim 8 , wherein the plurality of tasks and the preferred modes of transportation, and the geographic mapping data are retrieved from at least one database.

10. The computer-implemented method of claim 8 further comprising executing the route model to determine the optimal route and the one or more optimal modes of transportation, the one or more optimal modes of transportation available at the starting location of the user.

11. The computer-implemented method of claim 8 , wherein the real-time information includes at least one of real-time weather data or real-time traffic data.

12. The computer-implemented method of claim 8 further comprising:

providing the computer application configured to display, on the user interface of the user computing device, the updated optimized travel plan overlaid on a map.

13. The computer-implemented method of claim 8 further comprising generating the route model based upon traffic data and weather data.

14. The computer-implemented method of claim 8 further comprising:

generating a task model associated with the user, wherein the task model is based upon one of tasks input by the user and predicted tasks determined from historical data associated with the user, the historical data including previous tasks planned for the user; and

generating the route model based upon risk data associated with at least one of the user or estimated routes associated with the plurality of tasks.

15. At least one non-transitory computer-readable storage medium having computer-executable instructions embodied thereon, wherein when executed by an adaptive mapping computing device having at least one processor in communication with at least one memory device, the computer-executable instructions cause the at least one processor to:

generate a route model based upon a plurality of tasks associated with a user, preferred modes of transportation of the user, and geographic mapping data including a starting location of the user;

execute the route model to determine an optimized travel plan for the user including and optimal route and one or more optimal modes of transportation for the optimal route;

receive, from a user computing device associated with the user, geolocation data of the user computing device indicating a real-time location of the user;

continuously receive and analyze real-time information from one or more data sources and the geolocation data from the user computing device to continuously update the optimized travel plan in real-time, thereby enabling the adaptive mapping computing device to perform, in real-time, continuous and adaptive route pathing and transportation mode selection based upon the real-time location of the user, fluctuating conditions, and merchant information associated with the plurality of tasks and a plurality of merchants;

retrieve and analyze the merchant information to select an optimal order of travel to each task location associated with the plurality of tasks, wherein analyzing the merchant information includes comparing (a) at least one of services or products offered by the plurality of merchants to the plurality of tasks, and (b) one or more locations of each of the plurality of merchants to the optimal order of travel;

transmit, to the user computing device, the updated optimized travel plan including the selected optimal order of travel;

provide a computer application configured to display, on a user interface of the user computing device, the updated optimized travel plan including the selected optimal order of travel; and

execute the computer application, wherein executing the computer application comprises displaying the updated optimized travel plan including the selected optimal order of travel on the user interface of the user computing device.

16. The at least one non-transitory computer-readable storage medium of claim 15 , wherein the computer-executable instructions further cause the at least one processor to execute the route model to determine the optimal route and the one or more optimal modes of transportation, the one or more optimal modes of transportation available at the starting location of the user.

17. The at least one non-transitory computer-readable storage medium of claim 15 , wherein the real-time information includes at least one of real-time weather data or real-time traffic data.

18. The at least one non-transitory computer-readable storage medium of claim 15 , wherein the computer-executable instructions further cause the at least one processor to:

provide the computer application configured to display, on the user interface of the user computing device, the updated optimized travel plan overlaid on a map.

19. The at least one non-transitory computer-readable storage medium of claim 15 , wherein the computer-executable instructions further cause the at least one processor to generate the route model based upon traffic data and weather data.

20. The at least one non-transitory computer-readable storage medium of claim 15 , wherein the computer-executable instructions further cause the at least one processor to:

generate a task model associated with the user, wherein the task model is based upon one of tasks input by the user and predicted tasks determined from historical data associated with the user, the historical data including previous tasks planned for the user; and

generate the route model based upon risk data associated with at least one of the user or estimated routes associated with the plurality of tasks.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 14, 2023
From: GROSS, RYAN MICHAEL; THOELE, JODY ANN; BRANNAN, JOSEPH ROBERT; MOORE, ERIC R.
To: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
Reel/Frame 064908/0693 →
Continuity (3)
Continuation 17127441 · Dec 18, 2020
Provisional Application 62972866 · Feb 11, 2020
Related Publication 20230419262A1 · Dec 28, 2023
References Cited (27)
US 5291412A · Tamai et al. · 1994 [cited by applicant]
US 6944536B2 · Singleton · 2005 [cited by applicant]
US 9103687B1 · Loo et al. · 2015 [cited by applicant]
US 9311271B2 · Wright · 2016 [cited by applicant]
US 9633487B2 · Wright · 2017 [cited by applicant]
US 9650042B2 · Sujan et al. · 2017 [cited by applicant]
US 9911087B1 · Henderson et al. · 2018 [cited by applicant]
US 10101164B2 · Thakur · 2018 [cited by applicant]
US 10192369B2 · Wright · 2019 [cited by applicant]
US 10198879B2 · Wright · 2019 [cited by applicant]
US 11466997B1 · Williams · 2022 [cited by examiner]
US 20140222330A1 · Kohlenberg · 2014 [cited by examiner]
US 20180216952A1 · Krumm et al. · 2018 [cited by applicant]
US 20180299282A1 · Cummins et al. · 2018 [cited by applicant]
US 20200034757A1 · Gupta · 2020 [cited by examiner]
US 20200284601A1 · Myers · 2020 [cited by examiner]
US 20200363220A1 · Simoudis · 2020 [cited by examiner]
US 20210063173A1 · Cope · 2021 [cited by examiner]
US 20220366509A1 · Brannan · 2022 [cited by examiner]
US 20230236033A1 · Simoudis · 2023 [cited by examiner]
CN 105651289A · 2016 [cited by applicant]
CN 106952189A · 2017 [cited by applicant]
CN 110033143A · 2019 [cited by applicant]
EP 3420313A1 · 2019 [cited by applicant]
TW 201724006A · 2017 [cited by applicant]
TW 201727563A · 2017 [cited by applicant]
WO 2017146790A1 · 2017 [cited by applicant]