IP Library › Granted Patent US 10,759,444
Granted Patent B2
US 10,759,444 · App. 15/644,283 · Granted Sep 1, 2020

Resource optimization in vehicles

Inventors: Nikolaos Michalakis (Saratoga, CA); Julian M. Mason (Redwood City, CA); James J. Kuffner, Jr. (Sunnyvale, CA); James M. Adler (Redwood City, CA)
Assignee: Toyota Research Institute, Inc.
B60W50/06G06F9/505G06F9/5044G06F11/3013G06F11/3051G06F11/3433H04L67/12B60W2050/0013B60W2050/0077G06F2209/509
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Quick Facts
Patent No.
US 10,759,444
App. No.
15/644,283
Granted
Sep 1, 2020
Kind
B2
Abstract

This disclosure describes various embodiments for resource optimization in a vehicle. In an embodiment, a system for resource optimization in a vehicle is described. The system may comprise a memory; a processor coupled to the memory; and a resource optimization module. The resource optimization module may be configured to: monitor usage of local computing resources of the vehicle, the local computing resources comprising the processor and available bandwidth of a transmission medium; determine an availability of the local computing resources; evaluate data captured by one or more sensors of the vehicle; and determine whether to process the data locally or remotely based, at least in part, on the availability of the local computing resources and the data captured by the one or more sensors.

Claims (79)

1. A system for resource optimization in a vehicle, the system comprising:

a memory;

a processor coupled to the memory; and

a resource optimization module including instructions that when executed by the processor cause the processor:

monitor usage of local computing resources of the vehicle, the local computing resources comprising the processor and available bandwidth of a transmission medium;

determine an availability of the local computing resources;

evaluate data captured by one or more sensors of the vehicle;

determine whether to process the data locally or remotely based, at least in part, on the availability of the local computing resources and the data captured by the one or more sensors; and

when the data is processed locally producing first results, subsequently process the data a second time using different software to produce second results, compare the first results to the second results, and adjust a detection algorithm of the one or more sensors based on the comparison.

2. The system of claim 1 , wherein the resource optimization module is further configured to determine to process the data locally based, at least in part, on the availability of the local computing resources indicating that the processor has sufficient processing power to execute a processing algorithm on the data while the vehicle is in motion.

3. The system of claim 1 , wherein the processor is configured to process the data based upon the resource optimization module determining the availability of local computing resources is adequate for processing the data.

4. The system of claim 3 , wherein the processor is further configured to store:

a result comprising processed data;

the data; and

metadata comprising a tag indicating the data has been processed.

5. The system of claim 4 , wherein the resource optimization module is further configured to:

determine an availability of additional computing resources; and

determine, based upon determining the availability of the additional computing resources, to remotely process one or more of: at least portion of the data and the result.

6. The system of claim 1 , wherein the processor is further configured to store:

at least a portion of the data for later processing based upon the resource optimization module determining the availability of local computing resources is not adequate for processing the data; and

metadata comprising a first tag indicating the data has not been processed.

7. The system of claim 6 , wherein the processor is further configured to:

process a subset of the data based upon the resource optimization module determining the availability of local computing resources is adequate for processing the subset of the data; and

write a second tag indicating the subset of the data has been processed to the metadata.

8. The system of claim 7 , wherein the resource optimization module is further configured to:

determine an availability of additional computing resources; and

determine to process at least a portion of the data remotely based upon determining the availability of the additional computing resources.

9. The system of claim 6 , wherein the resource optimization module is further configured to:

determine an availability of additional computing resources;

analyze the metadata associated with the data; and

determine not to process at least a portion of the data remotely based upon determining a second tag in the metadata indicates the data should not be transmitted.

10. A method for resource optimization in a vehicle, the method comprising:

monitoring usage of local computing resources of the vehicle, the local computing resources comprising a processor and available bandwidth of a transmission medium;

determining an availability of the local computing resources;

evaluating data captured by one or more sensors of the vehicle;

determining whether to process the data locally or remotely based, at least in part, on the availability of the local computing resources and the data captured by the one or more sensors; and

when the data is processed locally producing first results:

subsequently processing the data a second time using different software to produce second results,

comparing the first results to the second results, and

adjusting a detection algorithm of the one or more sensors based on the comparison.

11. The method of claim 10 , further comprising creating metadata describing characteristics of the data.

12. The method of claim 10 , further comprising processing the data based upon determining the availability of local computing resources is adequate for processing the data.

13. The method of claim 12 , further comprising storing:

a result comprising processed data;

the data; and

metadata comprising a tag indicating the data has been processed.

14. The method of claim 13 , further comprising:

determining an availability of additional computing resources; and

remotely processing, based upon determining the availability of the additional computing resources, one or more of: at least portion of the data and the result.

15. The method of claim 10 , further comprising:

storing at least a portion of the data for later processing based upon determining the availability of local computing resources is not adequate for processing the data; and

storing metadata comprising a first tag indicating the data has not been processed.

16. The method of claim 15 , further comprising:

processing a subset of the data based upon determining the availability of local computing resources is adequate for processing the subset of the data; and

writing a second tag indicating the subset of the data has been processed to the metadata.

17. The method of claim 16 , further comprising:

determining an availability of additional computing resources; and

processing at least a portion of the data remotely based upon determining the availability of the additional computing resources.

18. The method of claim 15 , further comprising:

determining an availability of additional computing resources;

analyzing the metadata associated with the data; and

determining not to process at least a portion of the data remotely based upon determining a second tag in the metadata indicates the data should not be transmitted.

19. A vehicle comprising:

one or more sensors;

a memory;

a processor coupled to the memory; and

a resource optimization module including instructions that when executed by the processor cause the processor:

monitor usage of local computing resources of the vehicle, the local computing resources comprising the processor and available bandwidth of a transmission medium;

determine an availability of the local computing resources;

evaluate data captured by the one or more sensors;

determine whether to process the data locally or remotely based, at least in part, on the availability of the local computing resources and the data captured by the one or more sensors; and

when the data is processed locally producing first results:

subsequently process the data a second time using different software to produce second results,

compare the first results to the second results, and

adjust a detection algorithm of the one or more sensors based on the comparison.

20. The vehicle of claim 19 , wherein the resource optimization module is further configured to:

determine an availability of additional computing resources; and

determine to process at least a portion of the data remotely based upon determining the availability of the additional computing resources.

21. The method of claim 10 , further comprising determining to process the data locally when the data contains personally identifiable information.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 29, 2020
From: TOYOTA RESEARCH INSTITUTE, INC.
To: TOYOTA JIDOSHA KABUSHIKI KAISHA
Reel/Frame 053915/0464 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 24, 2017
From: MICHALAKIS, NIKOLAOS; MASON, JULIAN M.; KUFFNER, JAMES J.; ADLER, JAMES M.
To: TOYOTA RESEARCH INSTITUTE, INC.
Reel/Frame 043668/0235 →
Continuity (1)
Related Publication 20190009790A1 · Jan 10, 2019
Cited By (2)
US 12,505,704 US 12,533,922