VEHICLE CONTROL FOR REDUCING ROAD WEAR

• US 20180314258A1
• Filed: 04/28/2017
• Published: 11/01/2018
• Est. Priority Date: 04/28/2017
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: BREW, KEVIN W., GORDON, MICHAEL S., KOZLOSKI, JAMES R., PICKOVER, CLIFFORD A.
• Granted Patent: US 10,640,121 B2
• Time in Patent Office: Days
• CPC Class Codes: B60W 2552/05 Type of road, e.g. motorways, local streets, paved or unpaved roads
• CPC Class Codes: B60W 2552/35 Road bumpiness, e.g. potholes
• CPC Class Codes: B60W 2554/80 Spatial relation or speed relative to objects
• CPC Class Codes: B60W 2555/20 Ambient conditions, e.g. wind or rain
• CPC Class Codes: B60W 30/10 Path keeping cruise control for automatically following a preceding vehicle B60W30/165
• CPC Class Codes: B60W 40/06 Road conditions
• CPC Class Codes: G05D 1/0212 with means for defining a desired trajectory involving a plurality of land vehicles G05D1/0287

Abstract

In a computer-implemented method embodiment of the present invention, a self-driving vehicle (SDV) is steered onto a particular tire path on a roadway based on past taken tire paths. One or more processors determine a pattern of tire path usage by vehicles on a roadway. Based on this previous tire path usage, the processor(s) direct an SDV on-board computer on an SDV to pick at least one second tire path for the SDV to drive thereon based on the pattern of tire path usage by the vehicles on the roadway.

Claims

1. A computer-implemented method comprising:

determining, by one or more processors, a pattern of tire path usage by vehicles on a roadway; and

directing, by one or more processors, an on-board computer of a vehicle to recommend at least one tire path for the vehicle to drive thereon based on the pattern of tire path usage by the vehicles on the roadway.

2. The computer-implemented method of claim 1, wherein the vehicle is a self-driving vehicle (SDV), wherein the at least one tire path comprises multiple tire paths, and wherein the computer-implemented method further comprises:

determining, by one or more processors, that the roadway is paved; and

directing, by one or more processors, an SDV on-board computer on the SDV to select a distribution of the multiple tire paths of a paved roadway for the SDV to drive thereon.

3. The computer-implemented method of claim 1, wherein the vehicle is a self-driving vehicle (SDV), wherein the roadway is unpaved, and wherein computer-implemented method further comprises:

determining, by one or more processors, that the roadway is unpaved;

identifying, by one or more processors, a most frequently used tire path from the pattern of tire path usage by the vehicles on an unpaved roadway; and

selecting, by one or more processors, the most frequently used tire path of the unpaved roadway as the at least one tire path for the SDV to drive thereon.

4. The computer-implemented method of claim 1, wherein the vehicle is a self-driving vehicle (SDV), and wherein the computer-implemented method further comprises:

identifying, by one or more processors, rutting in at least one tire path from the pattern of tire path usage by the vehicles on the roadway; and

directing, by one or more processors, an SDV on-board computer on the SDV to pick a tire path that is less rutted than said at least one tire path for the SDV to drive thereon.

5. The computer-implemented method of claim 1, wherein the vehicle is a self-driving vehicle (SDV) and the at least one tire path for the SDV is picked based on at least one factor from a group consisting of:

a type of road material used to construct the roadway;

a width of the roadway;

an amount of traffic on the roadway;

a speed of traffic on the roadway;

types of other vehicles on the roadway;

weights of other vehicles on the roadway;

weather conditions on the roadway; and

defects in a surface of the roadway.

6. The computer-implemented method of claim 2, wherein said determining, by one or more processors, that the roadway is paved, further comprises determining, by one or more processors, that the roadway is constructed of materials selected from a group consisting of asphalt, concrete, composite pavement, and bituminous surfaces.

7. The computer-implemented method of claim 3, wherein said determining, by one or more processors, that the roadway is unpaved, further comprises determining, by one or more processors, that the roadway is constructed of one or more materials from a group consisting snow, sand, mud, loose gravel, and dirt.

8. The computer-implemented method of claim 1, wherein the vehicle is a self-driving vehicle (SDV), and wherein the computer-implemented method further comprises:

determining, by one or more processors, that the SDV is riding on studded tires; and

adjusting, by one or more processors, which at least one tire path is chosen based on the SDV riding on the studded tire.

9. The computer-implemented method of claim 1, wherein the vehicle is a self-driving vehicle (SDV), and wherein the computer-implemented method further comprises:

receiving, by an on-board computer of the SDV, road condition reports about the roadway from multiple other SDVs on the roadway; and

adjusting, by the on-board computer of the SDV, which at least one tire path is chosen based on road condition reports about the roadway from multiple other SDVs on the roadway.

10. The computer-implemented method of claim 9, further comprising:

receiving, by the SDV on-board computer of the SDV, the road condition reports from a blockchain that is supported by the multiple other SDVs.

11. The computer-implemented method of claim 1, wherein the computer-implemented method is executed as a cloud-based service.

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

determining, by one or more processors, that the roadway is unpaved;

identifying, by one or more processors, a most frequently used tire path from the pattern of tire path usage by the vehicles on an unpaved roadway; and

selecting, by one or more processors, the most frequently used tire path of the unpaved roadway as the at least one tire path for the SDV to drive thereon.

12. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions readable and executable by a processor to cause the processor to:

determine a pattern of tire path usage by vehicles on a roadway; and

direct a self-driving vehicle (SDV) on-board computer on an SDV to pick at least one tire path for the SDV to drive thereon based on the pattern of tire path usage by the vehicles on the roadway.

13. The computer program product of claim 12, wherein the at least one tire path are multiple tire paths on the roadway, wherein the roadway is paved, and wherein the program instructions readable and executable by a processor to cause the processor to:

direct the SDV on-board computer to select a distribution of the multiple tire paths for the SDV to drive thereon.

14. The computer program product of claim 12, wherein the roadway is unpaved, and wherein a first tire path and a second tire path are a same time path on the roadway.

15. The computer program product of claim 12, wherein the program instructions are further readable and executable by the processor to cause the processor to:

identify rutting in at least one tire path from the pattern of tire path usage by the vehicles on the roadway; and

direct the SDV on-board computer on the SDV to pick a tire path that is not rutted as said at least one tire path for the SDV to drive upon.

16. The computer program product of claim 12, wherein the program instructions are further readable and executable by the processor to cause the processor to:

receive road condition reports about the roadway from a blockchain that is supported by the multiple other SDVs on the roadway; and

adjust which at least one tire path is chosen based on the road condition reports about the roadway from the blockchain.

17. The computer program product of claim 12, wherein the program instructions are provided as a service in a cloud environment.

18. A system comprising:

one or more processors;

one or more computer readable memories operably coupled to the one or more processors;

wherein the one or more computer readable memories having

program instructions stored thereon for execution by at least one of the one or more processors, the program instructions comprising;

program instructions to determine a pattern of tire path usage by vehicles on a roadway; and

program instructions to direct a self-driving vehicle (SDV) on-board computer on an SDV to pick at least one tire path for the SDV to drive thereon based on the pattern of tire path usage by the vehicles on the roadway.

19. The system of claim 18, wherein the at least one tire path are multiple tire paths on the roadway, wherein the roadway is paved, and wherein system further comprises:

program instructions to direct the SDV on-board computer to select a distribution of the multiple tire paths for the SDV to drive thereon.

20. The system of claim 18, wherein the program instructions are provided as a service in a cloud environment.

21. A computer-implemented method comprising:

determining, by one or more processors, a pattern of tire path usage by vehicles on a roadway; and

directing, by one or more processors, a Self-Driving Vehicle (SDV) on-board computer of an SDV to recommend at least one tire path for the SDV to drive thereon based on the pattern of tire path usage by the vehicles on the roadway.

22. The computer-implemented method of claim 21, further comprising:

determining, by one or more processors, that the roadway is paved; and

directing, by one or more processors, the SDV on-board computer to select a distribution of the multiple tire paths of a paved roadway for the SDV to drive on.

24. A computer-implemented method comprising:

determining, by one or more processors, a pattern of tire path usage by multiple Self-Driving Vehicles (SDVs) on a roadway;

receiving, by an SDV on-board computer on a present SDV that is currently traveling on the roadway, the pattern of tire path usage by the multiple SDVs that have traveled on the roadway during a past time period; and

directing, by one or more processors, an SDV on-board computer of the present SDV to control the present SDV to travel along at least one tire path based on the pattern of tire path usage by the multiple SDVs that have previously traveled on the roadway.

25. The computer-implemented method of claim 24, further comprising:

determining, by one or more processors, that the roadway is paved; and

directing, by one or more processors, the SDV on-board computer to select a distribution of the multiple tire paths of a paved roadway for the current SDV to drive on.