METHOD AND APPARATUS FOR PROVIDING ROAD SURFACE FRICTION DATA FOR A RESPONSE ACTION

• US 20160176408A1
• Filed: 12/22/2014
• Published: 06/23/2016
• Est. Priority Date: 12/22/2014
• Status: Active Grant

• Current Assignee: HERE Global B.V. (Nokia Corporation)
• Original Assignee: HERE Global B.V. (Nokia Corporation)
• Inventors: LYNCH, James D.
• Granted Patent: US 9,815,476 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B60W 2050/0075 Automatic parameter input, automatic initialising or calibrating means
• CPC Class Codes: B60W 2552/40 Coefficient of friction
• CPC Class Codes: B60W 2555/20 Ambient conditions, e.g. wind or rain
• CPC Class Codes: B60W 2556/45 External transmission of data to or from the vehicle
• CPC Class Codes: B60W 40/064 Degree of grip
• CPC Class Codes: B60W 40/068 Road friction coefficient
• CPC Class Codes: B60W 50/082 Selecting or switching between different modes of propelling
• CPC Class Codes: B60W 60/0053 from vehicle to occupant

Abstract

An approach is provided for determining road surface friction data for at least one travel segment via sensor data and/or guideline friction map to cause at least one response action. The approach involves processing and/or facilitating a processing of sensor data to determine at least one road-vehicle friction change associated with at least one travel segment. The approach also involves causing, at least in part, a comparison of the at least one road-vehicle friction change to at least one guideline friction map. The approach further involves determining at least one response action to the at least one road-friction change based, at least in part, on the comparison.

Claims

1. A method comprising:

processing and/or facilitating a processing of sensor data to determine at least one road-vehicle friction change associated with at least one travel segment;

causing, at least in part, a comparison of the at least one road-vehicle friction change to at least one guideline friction map; and

determining at least one response action to the at least one road-friction change based, at least in part, on the comparison.

2. A method of claim 1, further comprising:

determining at least one expected friction change value, at least one expected extent of the at least one expected friction change value, or a combination thereof for the at least one travel segment from the at least one guideline friction map,

wherein the comparison is based, at least in part, on the at least one expected friction change value, the at least one expected extent, or a combination thereof.

3. A method of claim 1, wherein the at least one road-vehicle friction change is associated with at least one autonomous vehicle, at least one highly-assisted driving vehicle, or a combination thereof.

4. A method of claim 3, wherein the at least one autonomous vehicle, the at least one highly-assisted driving vehicle, or a combination thereof is operating in at least one autonomous mode of operation, the method further comprising:

determining that the at least one road-vehicle friction change is similar to the at least one expected road friction change and that the at least one expected extent is less than at least one distance threshold; and

causing, at least in part, a designation of a continuation of the at least one autonomous mode of operation as the at least one response action.

5. A method of claim 3, wherein the at least one autonomous vehicle, the at least one highly-assisted driving vehicle, or a combination thereof is operating in at least one autonomous mode of operation, the method further comprising:

determining that the at least one road-vehicle friction change is similar to the at least one expected road friction change and that the at least one expected extent is greater than at least one distance threshold; and

causing, at least in part, a designation of a change to at least one manual mode of operation as the at least one response action.

6. A method of claim 3, wherein the at least one autonomous vehicle, the at least one highly-assisted driving vehicle, or a combination thereof is operating in at least one autonomous mode of operation, the method further comprising:

determining that the at least one road-vehicle friction change is similar to the at least one expected road friction change and that the at least one road-vehicle friction change is expected to be constant for the at least one travel segment; and

causing, at least in part, a designation of a change to at least one manual mode of operation as the at least one response action.

7. A method of claim 1, further comprising:

receiving at least one incidence report regarding at least one friction related event associated with the at least one travel segment;

determining whether to ignore the at least one incidence report based, at least in part, on the at least one guideline friction map.

8. A method of claim 1, further comprising:

causing, at least in part, an aggregation of friction data for at least one travel segment, one or more other travel segments, or a combination thereof; and

processing and/or facilitating a processing of the friction data to cause, at least in part, a generation of the at least one guideline friction map.

9. A method of claim 8, wherein the friction data is collected under standard conditions for the at least one travel segment, the one or more other travel segments, or a combination thereof.

10. A method of claim 8, wherein the friction data is collected over a period of time, the method further comprising:

processing and/or facilitating a processing of the friction data to cause, at least in part, a removal of one or more time-varying features from the friction prior to the generation of the at least one friction map.

10b. b. A method in claim 10, wherein a change in friction observed over an extended time causes a generation of a road repair warning.

11. An apparatus comprising:

at least one processor; and

at least one memory including computer program code for one or more programs,

the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following,

process and/or facilitate a processing of sensor data to determine at least one road-vehicle friction change associated with at least one travel segment;

cause, at least in part, a comparison of the at least one road-vehicle friction change to at least one guideline friction map; and

determine at least one response action to the at least one road-friction change based, at least in part, on the comparison.

12. An apparatus of claim 11, wherein the apparatus is further caused to:

determine at least one expected friction change value, at least one expected extent of the at least one expected friction change value, or a combination thereof for the at least one travel segment from the at least one guideline friction map,

wherein the comparison is based, at least in part, on the at least one expected friction change value, the at least one expected extent, or a combination thereof.

13. An apparatus of claim 11, wherein the at least one road-vehicle friction change is associated with at least one autonomous vehicle, at least one highly-assisted driving vehicle, or a combination thereof.

14. An apparatus of claim 13, wherein the at least one autonomous vehicle, the at least one highly-assisted driving vehicle, or a combination thereof is operating in at least one autonomous mode of operation, and wherein the apparatus is further caused to:

determine that the at least one road-vehicle friction change is similar to the at least one expected road friction change and that the at least one expected extent is less than at least one distance threshold; and

cause, at least in part, a designation of a continuation of the at least one autonomous mode of operation as the at least one response action.

15. An apparatus of claim 13, wherein the at least one autonomous vehicle, the at least one highly-assisted driving vehicle, or a combination thereof is operating in at least one autonomous mode of operation, and wherein the apparatus is further caused to:

determine that the at least one road-vehicle friction change is similar to the at least one expected road friction change and that the at least one expected extent is greater than at least one distance threshold; and

cause, at least in part, a designation of a change to at least one manual mode of operation as the at least one response action.

16. An apparatus of claim 13, wherein the at least one autonomous vehicle, the at least one highly-assisted driving vehicle, or a combination thereof is operating in at least one autonomous mode of operation, and wherein the apparatus is further caused to:

determine that the at least one road-vehicle friction change is similar to the at least one expected road friction change and that the at least one road-vehicle friction change is expected to be constant for the at least one travel segment; and

cause, at least in part, a designation of a change to at least one manual mode of operation as the at least one response action.

17. An apparatus of claim 11, wherein the apparatus is further caused to:

receive at least one incidence report regarding at least one friction related event associated with the at least one travel segment; and

determine whether to ignore the at least one incidence report based, at least in part, on the at least one guideline friction map.

18. A computer-readable storage medium carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to perform:

process and/or facilitate a processing of sensor data to determine at least one road-vehicle friction change associated with at least one travel segment;

cause, at least in part, a comparison of the at least one road-vehicle friction change to at least one guideline friction map; and

determine at least one response action to the at least one road-friction change based, at least in part, on the comparison.

19. A computer-readable storage medium of claim 18, wherein the apparatus is further caused to perform:

determine at least one expected friction change value, at least one expected extent of the at least one expected friction change value, or a combination thereof for the at least one travel segment from the at least one guideline friction map,

wherein the comparison is based, at least in part, on the at least one expected friction change value, the at least one expected extent, or a combination thereof.

20. A computer-readable storage medium of claim 18, wherein the at least one road-vehicle friction change is associated with at least one autonomous vehicle, at least one highly-assisted driving vehicle, or a combination thereof.

21-48. -48. (canceled)