IP Library Granted Patent US 10,737,698
Granted Patent B2
US 10,737,698 · App. 16/161,366 · Granted Aug 11, 2020

Technologies for assisting vehicles with changing road conditions

Inventors: Igor Tatourian (Fountain Hills, AZ); Rita H. Wouhaybi (Portland, OR); Hong Li (Folsom, CA)
Assignee: Intel Corporation
B60W30/188B60W10/06B60W30/143B60W40/02B60W40/076B60W50/0097B60W50/14G08G1/017G08G1/0112G08G1/0116G08G1/0129G08G1/0141G08G1/0145G08G1/09675G08G1/096725G08G1/096741G08G1/096775B60K2370/169B60W2420/52B60W2420/54B60W2530/00B60W2530/209B60W2552/00B60W2552/15B60W2552/40B60W2555/20B60W2556/65B60W2756/10Y02T10/84
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Quick Facts
Patent No.
US 10,737,698
App. No.
16/161,366
Granted
Aug 11, 2020
Kind
B2
Abstract

Technologies for assisting vehicles with changing road conditions includes vehicle assistance data based on crowd-sourced road data received from a plurality of vehicles and/or infrastructure sensors. The crowd-sourced road data may be associated with a particular section of roadway and may be used to various characteristics of the roadway such as grade, surface, hazardous conditions, and so forth. The vehicle assistance data may be provided to an in-vehicle computing device to assist or facilitate traversal of the roadway.

Claims (93)

1. One or more non-transitory machine readable storage media comprising a plurality of instructions stored thereon that, when executed, causes an in-vehicle computing system of a vehicle to:

receive vehicle assistance data from a vehicle assistance server, wherein the vehicle assistance data is generated based on vehicle profile information and crowd-sourced road data associated with a road segment corresponding to a location of the vehicle;

determine a vehicle parameter value to be adjusted based on the received vehicle assistance data; and

cause an adjustment of the vehicle parameter value based on the received vehicle assistance data.

2. The one or more non-transitory machine readable storage media of claim 1 , wherein the profile information includes vehicle operational data, wherein the vehicle operational data includes the location of the vehicle.

3. The one or more non-transitory machine readable storage media of claim 1 , wherein to cause the adjustment of the vehicle parameter value comprises to cause an adjustment of a setting of a cruise control system.

4. The one or more non-transitory machine readable storage media of claim 1 , wherein the plurality of instructions further causes the in-vehicle computing system to:

receive, from the vehicle assistance server, road condition data generated based on the crowd-sourced road data, wherein the road condition data is indicative of one or more road conditions of the road segment.

5. The one or more non-transitory machine readable storage media of claim 4 , wherein the road condition data generated based on the crowd-sourced road data is indicative of traffic on the road segment.

6. The one or more non-transitory machine readable storage media of claim 4 , wherein the road condition data generated based on the crowd-sourced road data is indicative of slippery conditions on the road segment.

7. The one or more non-transitory machine readable storage media of claim 4 , wherein the road condition data generated based on the crowd-sourced road data is indicative of an animal on the road segment.

8. The one or more non-transitory machine readable storage media of claim 4 , wherein the road condition data generated based on the crowd-sourced road data is indicative of an obstruction on the road segment.

9. The one or more non-transitory machine readable storage media of claim 4 , wherein the road condition data generated based on the crowd-sourced road data is indicative of a road grade of the road segment.

10. The one or more non-transitory machine readable storage media of claim 1 , wherein the plurality of instructions further cause the in-vehicle computing system to:

receive sensor data from one or more sensors of the vehicle that is indicative of additional road data associated with the road segment; and

send the additional road data to the vehicle assistance server, wherein the additional road data is usable by the vehicle assistance server to generate additional vehicle assistance data based on crowd-sourcing.

11. The one or more non-transitory machine readable storage media of claim 1 , wherein the plurality of instructions further causes the in-vehicle computing system to:

receive sensor data from one or more sensors of the vehicle that is indicative of an obstruction on the road segment; and

send an indication of the obstruction on the road segment to the vehicle assistance server.

12. The one or more non-transitory machine readable storage media of claim 1 , wherein the plurality of instructions further causes the in-vehicle computing system to:

receive, from the vehicle assistance server, road hazard data generated based on the crowd-sourced road data, wherein the road hazard data is indicative of a traffic jam on the road segment; and

predict a future speed of the vehicle based on the road hazard data,

wherein to determine the vehicle parameter value to be adjusted based on the received vehicle assistance data comprises to determine a throttle parameter value based on the predicted future speed,

wherein to cause the adjustment of the vehicle parameter value based on the received vehicle assistance data comprises to cause an adjustment of the throttle parameter value based on the predicted future speed.

13. The one or more non-transitory machine readable storage media of claim 1 , wherein the plurality of instructions further causes the in-vehicle computing system to:

predict, based on the vehicle assistance data, an energy usage associated with the road segment.

14. The one or more non-transitory machine readable storage media of claim 1 , wherein the plurality of instructions further causes the in-vehicle computing system to:

predict, based on the vehicle assistance data, a change in a grade of the road segment;

wherein to determine the vehicle parameter value to be adjusted based on the received vehicle assistance data comprises to determine a gear parameter value to be adjusted based on the predicted change in the grade of the road segment,

wherein to cause the adjustment of the vehicle parameter value based on the received vehicle assistance data comprises to cause an adjustment of the gear parameter value based on the predicted change in the grade of the road segment.

15. One or more non-transitory machine readable storage media comprising a plurality of instructions stored thereon that in response to being executed causes a vehicle assistance server to:

receive road data from each of a plurality of vehicles, wherein the road data includes data indicative of at least one characteristic of a road segment traversed by each of the plurality of vehicles;

aggregate the road data received from a set of the plurality of vehicles to generate crowd-sourced road data associated with the road segment;

determine vehicle assistance data for a vehicle based on vehicle profile information of the vehicle and the crowd-sourced road data associated with the first road segment, wherein the vehicle assistance data is usable by an in-vehicle computing device of the vehicle to facilitate traversal of the road segment by the vehicle; and

transmit the vehicle assistance data to the vehicle.

16. The one or more non-transitory machine readable storage media of claim 15 , wherein the plurality of instructions further causes the vehicle assistance server to:

send, to the vehicle, road condition data generated based on the crowd-sourced road data, wherein the road condition data is indicative of one or more road conditions of the road segment.

17. The one or more non-transitory machine readable storage media of claim 16 , wherein the road condition data generated based on the crowd-sourced road data is indicative of traffic on the road segment.

18. The one or more non-transitory machine readable storage media of claim 16 , wherein the road condition data generated based on the crowd-sourced road data is indicative of a road grade of the road segment.

19. A vehicle comprising:

a communication circuit to receive vehicle assistance data from a vehicle assistance server, wherein the vehicle assistance data is generated based on vehicle profile information and crowd-sourced road data associated with a road segment corresponding to a location of the vehicle;

a vehicle assistance circuit to:

determine a vehicle parameter value to be adjusted based on the received vehicle assistance data; and

cause an adjustment of the vehicle parameter value based on the received vehicle assistance data.

20. The vehicle of claim 19 , wherein the communication circuit is further to:

receive, from the vehicle assistance server, road condition data generated based on the crowd-sourced road data, wherein the road condition data is indicative of one or more road conditions of the road segment.

21. The vehicle of claim 20 , wherein the road condition data generated based on the crowd-sourced road data is indicative of slippery conditions on the road segment.

22. The vehicle of claim 20 , wherein the road condition data generated based on the crowd-sourced road data is indicative of a road grade of the road segment.

23. The vehicle of claim 19 , wherein the communication circuit is further to receive, from the vehicle assistance server, road hazard data generated based on the crowd-sourced road data, wherein the road hazard data is indicative of a traffic jam on the road segment,

wherein the vehicle assistance circuit is further to predict a future speed of the vehicle based on the road hazard data,

wherein to determine the vehicle parameter value to be adjusted based on the received vehicle assistance data comprises to determine a throttle parameter value based on the predicted future speed, and

wherein to cause the adjustment of the vehicle parameter value based on the received vehicle assistance data comprises to cause an adjustment of the throttle parameter value based on the predicted future speed.

24. A vehicle assistance server comprising:

one or more processors;

memory coupled to the one or more processors; and

one or more machine readable storage media comprising a plurality of instructions stored thereon that in response to being executed causes the vehicle assistance server to:

receive road data from each of a plurality of vehicles, wherein the road data includes data indicative of at least one characteristic of a road segment traversed by each of the plurality of vehicles;

aggregate the road data received from a set of the plurality of vehicles to generate crowd-sourced road data associated with the road segment;

determine vehicle assistance data for a vehicle based on vehicle profile information of the vehicle and the crowd-sourced road data associated with the first road segment, wherein the vehicle assistance data is usable by an in-vehicle computing device of the vehicle to facilitate traversal of the road segment by the vehicle; and

transmit the vehicle assistance data to the vehicle.

25. The vehicle assistance server of claim 24 , wherein the plurality of instructions further causes the vehicle assistance server to:

send, to the vehicle, road condition data generated based on the crowd-sourced road data, wherein the road condition data is indicative of one or more road conditions of the road segment.

26. The vehicle assistance server of claim 25 , wherein the road condition data generated based on the crowd-sourced road data is indicative of slippery conditions on the road segment.

27. A compute device comprising:

a communication circuit to receive vehicle assistance data from a vehicle assistance server, wherein the vehicle assistance data is generated based on vehicle profile information of a vehicle and crowd-sourced road data associated with a road segment corresponding to a location of the vehicle; and

an output module to:

determine a vehicle parameter value of the vehicle to be adjusted based on the received vehicle assistance data; and

cause an adjustment of the vehicle parameter value based on the received vehicle assistance data.

28. The compute device of claim 27 , wherein the communication circuit is further to:

receive, from the vehicle assistance server, road condition data generated based on the crowd-sourced road data, wherein the road condition data is indicative of one or more road conditions of the road segment.

29. The compute device of claim 27 , wherein the communication circuit is further to receive, from the vehicle assistance server, road hazard data generated based on the crowd-sourced road data, wherein the road hazard data is indicative of a traffic jam on the road segment,

wherein the output module is further to predict a future speed of the vehicle based on the road hazard data,

wherein to determine the vehicle parameter value to be adjusted based on the received vehicle assistance data comprises to determine a throttle parameter value based on the predicted future speed, and

wherein to cause the adjustment of the vehicle parameter value based on the received vehicle assistance data comprises to cause an adjustment of the throttle parameter value based on the predicted future speed.

30. A computing system comprising:

a control circuit to receive vehicle assistance data from a vehicle assistance server, wherein the vehicle assistance data is based on road data corresponding to a location of a vehicle, and

the control circuit to determine information for adjusting operation of the vehicle based on the received vehicle assistance data; and

an interface unit to send the information to adjust operation of the vehicle.

31. The computing system of claim 30 , wherein the control circuit is further to:

receive, from the vehicle assistance server, road condition data generated based on the road data, wherein the road condition data is indicative of one or more road conditions of the road segment.

32. The computing system of claim 30 , wherein the control circuit is further to:

receive, from the vehicle assistance server, road hazard data generated based on the road data, wherein the road hazard data is indicative of a traffic jam on the road segment; and predict a future speed of the vehicle based on the road hazard data,

wherein to determine information for adjusting operation of the vehicle based on the received vehicle assistance data comprises to determine a throttle parameter value based on the predicted future speed, and

wherein to send the information to adjust operation of the vehicle comprises to send the throttle parameter value.

33. A computing system comprising:

a control circuit to receive vehicle assistance data from a vehicle assistance server, wherein the vehicle assistance data is based on road data corresponding to a location of a vehicle; and

a processor cooperatively connected to the control circuit, the processor to determine information for adjusting operation of the vehicle and to output a signal that triggers an adjustment of the operation of the vehicle.

34. The computing system of claim 33 , wherein the control circuit is further to:

receive, from the vehicle assistance server, road condition data generated based on the road data, wherein the road condition data is indicative of one or more road conditions of the road segment.

35. The computing system of claim 33 , wherein the control circuit is further to receive, from the vehicle assistance server, road hazard data generated based on the road data, wherein the road hazard data is indicative of a traffic jam on the road segment; and

wherein the processor is further to predict a future speed of the vehicle based on the road hazard data,

wherein to determine information for adjusting operation of the vehicle comprises to determine a throttle parameter value based on the predicted future speed, and

wherein to output a signal that triggers an adjustment of the operation of the vehicle comprises to output the throttle parameter value.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 15, 2022
From: INTEL CORPORATION
To: TAHOE RESEARCH, LTD.
Reel/Frame 061175/0176 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 1, 2020
From: TATOURIAN, IGOR; WOUHAYBI, RITA H.; LI, HONG
To: INTEL CORPORATION
Reel/Frame 052281/0512 →
Continuity (3)
Continuation 15413924 · Jan 24, 2017
Continuation 14671755 · Mar 27, 2015
Related Publication 20190283753A1 · Sep 19, 2019
Cited By (1)
US 12,548,319