IP Library Granted Patent US 12,249,241
Granted Patent B2
US 12,249,241 · App. 18/912,425 · Granted Mar 11, 2025

Methods and systems for digital alerting of vehicles based on a characteristic of a road and at least one factor corresponding to an object

Inventors: Jigar Patel (Arlington Heights, IL); Cory Hohs (Chicago, IL); Jeremy Agulnek (Chicago, IL)
Assignee: HAAS, Inc.
G08G1/161G08G1/166
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Quick Facts
Patent No.
US 12,249,241
App. No.
18/912,425
Granted
Mar 11, 2025
Kind
B2
Abstract

Embodiments of a method, a non-transitory computer readable medium, and a system for vehicle alerting are disclosed. In an example, a computer-implemented method for alerting vehicles, the method including receiving, at a cloud computing system, digital data that includes location information about an object, determining, by the cloud computing system, a characteristic of a road that corresponds to the location information, and initiating, by the cloud computing system, a digital alerting operation for nearby vehicles in response to the characteristic of the road and at least one additional factor that corresponds to the object.

Claims (28)

1. A computer-implemented method for alerting vehicles, the method comprising:

receiving, at a cloud computing system, digital data that includes location information about an object;

determining, by the cloud computing system, a functional classification (FC) of a road that corresponds to the location information; and

initiating, by the cloud computing system, a digital alerting operation for nearby vehicles in response to the FC of the road and at least one additional factor that corresponds to the object.

2. The computer-implemented method of claim 1 , wherein the digital data received at the cloud computing system indicates that the object is a vehicle that is stationary, the determined FC of the road is FC 1 , the at least one additional factor that corresponds to the object is that the object is a stationary vehicle, and wherein initiating the digital alerting operation involves generating vehicle-specific digital alerts for nearby vehicles.

3. The computer-implemented method of claim 1 , wherein the digital data received at the cloud computing system indicates that the object is a vehicle that is in park, the determined FC of the road is FC 1 , and the at least one additional factor that corresponds to the object is that the object is a vehicle in park, wherein initiating the digital alerting operation involves generating vehicle-specific digital alerts for nearby vehicles.

4. The computer-implemented method of claim 1 , wherein the digital data received at the cloud computing system indicates that the object is a vehicle with a deployed airbag, the determined of the road is FC 1 , the at least one additional factor that corresponds to the object is that the object is a vehicle with a deployed airbag, and wherein initiating the digital alerting operation involves generating vehicle-specific digital alerts for nearby vehicles.

5. The computer-implemented method of claim 1 , wherein the digital data received at the cloud computing system indicates that the object is a bicyclist, the determined FC of the road is FC 1 , the at least one additional factor that corresponds to the object is that the object is a bicycle, and wherein initiating the digital alerting operation involves generating vehicle-specific digital alerts for nearby vehicles.

6. The computer-implemented method of claim 1 , wherein the digital data received at the cloud computing system indicates that the object is a pedestrian, the determined FC of the road is FC 1 , the at least one additional factor that corresponds to the object is that the object is a pedestrian, and wherein initiating the digital alerting operation involves generating vehicle-specific digital alerts for nearby vehicles.

7. The computer-implemented method of claim 1 , wherein the digital data received at the cloud computing system indicates that the object is an animal, the determined FC of the road is FC 1 , the at least one additional factor that corresponds to the object is that the object is an animal, and wherein initiating the digital alerting operation involves generating vehicle-specific digital alerts for nearby vehicles.

8. The computer-implemented method of claim 1 , wherein the digital data received at the cloud computing system indicates that the object is a roadway obstacle, the determined FC of the road is FC 1 , the at least one additional factor that corresponds to the object is that the object is a roadway obstacle, and wherein initiating the digital alerting operation involves generating vehicle-specific digital alerts for nearby vehicles.

9. The computer-implemented method of claim 1 , wherein the digital data indicates that the object is travelling in a particular direction, the method further comprising determining a particular direction of travel of the road from the location information, and wherein the particular direction of travel of the object does not match the particular direction of travel of the road.

10. The computer-implemented method of claim 1 , wherein the digital alerting operation involves determining an alerting zone relative to the object, identifying vehicles that are within the alerting zone, and outputting vehicle-specific digital alerts for the vehicles that are within the alerting zone.

11. The method of claim 1 , wherein the FC of the road is a functional classification that includes interstate, other freeways or expressways, other principal arterial roadways, minor arterial, major collector, minor collector, and local roadways.

12. The method of claim 11 , wherein functional classifications of roads are functional classifications as defined by a government transportation agency.

13. The method of claim 1 , wherein determining the FC of the road that corresponds to the location information involves a reverse geocoding operation in which the location information is compared to a digital map to determine the FC of the road.

14. The method of claim 1 , wherein determining the FC of the road that corresponds to the location information involves a reverse geocoding operation in which the location information is compared to a digital map to determine the FC of the road.

15. A non-transitory computer readable medium comprising instructions to be executed in a computer system, wherein the instructions when executed in the computer system perform a method comprising:

receiving, at a cloud computing system, digital data that includes location information about an object;

determining, by the cloud computing system, a functional classification (FC) of a road that corresponds to the location information; and

initiating, by the cloud computing system, a digital alerting operation for nearby vehicles in response to the FC of the road and at least one additional factor that corresponds to the object.

16. A system comprising:

at least one processor and a non-transitory computer readable medium comprising instructions to be executed by the at least one processor, wherein the instructions when executed by the at least one processor perform a method that includes;

receiving, at a cloud computing system, digital data that includes location information about an object;

determining, by the cloud computing system, a functional classification of a road that corresponds to the location information; and

initiating, by the cloud computing system, a digital alerting operation for nearby vehicles in response to the FC of the road and at least one additional factor that corresponds to the object.

17. The system of claim 16 , wherein the digital data received at the cloud computing system indicates that the object is a vehicle that is stationary, the determined FC of the road is FC 1 , the at least one additional factor that corresponds to the object is that the object is a stationary vehicle, and wherein initiating the digital alerting operation involves generating vehicle-specific digital alerts for nearby vehicles.

18. The non-transitory computer readable medium of claim 15 , wherein the digital data received at the cloud computing system indicates that the object is a vehicle that is stationary, the determined FC of the road is FC 1 , the at least one additional factor that corresponds to the object is that the object is a stationary vehicle, and wherein initiating the digital alerting operation involves generating vehicle-specific digital alerts for nearby vehicles.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 25, 2024
From: PATEL, JIGAR; HOHS, CORY; AGULNEK, JEREMY
To: HAAS, INC.
Reel/Frame 069025/0333 →
Continuity (3)
Continuation In Part 18378605 · Oct 10, 2023
Continuation In Part 17990592 · Nov 18, 2022
Related Publication 20250037583A1 · Jan 30, 2025
References Cited (24)
US 8612131B2 · Gutierrez et al. · 2013 [cited by applicant]
US 9396210B1 · Crook · 2016 [cited by examiner]
US 9659496B2 · Massey et al. · 2017 [cited by applicant]
US 10008111B1 · Grant · 2018 [cited by applicant]
US 10582354B1 · Isaac · 2020 [cited by examiner]
US 12033506B1 · Deyaf et al. · 2024 [cited by applicant]
US 12109938B2 · Tucker · 2024 [cited by examiner]
US 20070159354A1 · Rosenberg · 2007 [cited by applicant]
US 20080074286A1 · Gill et al. · 2008 [cited by applicant]
US 20090174572A1 · Smith · 2009 [cited by applicant]
US 20120313792A1 · Behm et al. · 2012 [cited by applicant]
US 20140279707A1 · Joshua et al. · 2014 [cited by applicant]
US 20150254978A1 · Mawbey et al. · 2015 [cited by applicant]
US 20160210858A1 · Foster et al. · 2016 [cited by applicant]
US 20170144669A1 · Spata · 2017 [cited by examiner]
US 20170268896A1 · Bai · 2017 [cited by examiner]
US 20180268690A1 · Gebers · 2018 [cited by applicant]
US 20200074853A1 · Miller et al. · 2020 [cited by applicant]
US 20210097311A1 · McBeth · 2021 [cited by examiner]
US 20220013006A1 · Srivastava · 2022 [cited by examiner]
US 20230124536A1 · Chien et al. · 2023 [cited by applicant]
US 20240067087A1 · Tucker · 2024 [cited by examiner]
US 20240085214A1 · Nayak · 2024 [cited by examiner]
US 20240094010A1 · Bernhardt · 2024 [cited by examiner]