Autonomous vehicle degradation level monitoring

• US 10,262,471 B2
• Filed: 05/23/2017
• Issued: 04/16/2019
• Est. Priority Date: 05/23/2017
• Status: Active Grant

• Current Assignee: Uatc, LLC (Uber Technologies, Inc.)
• Original Assignee: Uber Technologies, Inc.
• Inventors: Kislovskiy, Dima, Bradley, David McAllister
• Primary Examiner(s): Troost, Aaron L
• Application Number:
  US15/602,303
• Publication Number:
  US 20180342113A1
• Time in Patent Office: 693 Days
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G07C 5/0808 Diagnosing performance data testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005
• CPC Class Codes: G07C 5/0841 Registering performance data recording measured values G01D; information storage G11B
• CPC Class Codes: G08G 1/09623 Systems involving the acquisition of information from passive traffic signs by means mounted on the vehicle G08G1/0967 takes precedence
• CPC Class Codes: G08G 1/165 for passive traffic, e.g. including static obstacles, trees
• CPC Class Codes: G08G 1/166 for active traffic, e.g. moving vehicles, pedestrians, bikes
• CPC Class Codes: G08G 1/202 Dispatching vehicles on the basis of a location, e.g. taxi dispatching

Abstract

An on-trip monitoring system for an on-demand transportation service can monitor live log data from autonomous vehicles (AVs) operating throughout a given region. The system can determine a degradation level for a respective AV based on the live log data, and when the degradation level exceeds a determined threshold, the system can transmit an update command to the respective AV to service or decommission the respective AV.

Claims

1. An on-trip monitoring system for autonomous vehicles (AVs) comprising:

one or more processors; and

one or more memory resources storing instructions that, when executed by the one or more processors, cause the on-trip monitoring system to;

monitor live log data from AVs operating throughout a given region;

determine a degradation level for a respective AV of the AVs based on the live log data from the respective AV; and

when the degradation level exceeds a determined threshold, transmit an update command to the respective AV to service or decommission the respective AV;

wherein the determined threshold corresponds to a variable risk threshold dependent upon a set of current conditions comprising at least one of lighting conditions, weather conditions, a time of day, day of week, traffic conditions, or road surface conditions.

2. The on-trip monitoring system of claim 1, wherein the live log data comprise sensor data from the AVs, and wherein the executed instructions cause the on-trip monitoring system to determine the degradation level based, at least in part, on a data quality of the sensor data from the respective AV.

3. The on-trip monitoring system of claim 1, wherein the live log data indicates a calibration fault condition with at least one sensor of the respective AV.

4. The on-trip monitoring system of claim 1, wherein the live log data comprises at least one of diagnostics data or telemetry data.

5. The on-trip monitoring system of claim 1, and wherein the executed instructions further cause the on-trip monitoring system to:

manage an on-demand transportation service by matching transport requests from requesting users with the AVs operating throughout the given region.

6. The on-trip monitoring system of claim 1, wherein the variable risk threshold further depends upon a predicted set of conditions comprising at least one of predicted lighting conditions, predicted weather conditions, predicted traffic conditions, or predicted road surface conditions.

7. The on-trip monitoring system of claim 1, wherein the degradation level of the respective AV indicates at least one of a required hardware upgrade, a required software upgrade, required standard hardware maintenance, or required standard mechanical maintenance.

8. The on-trip monitoring system of claim 1, wherein the executed instructions further cause the on-trip monitoring system to:

record the live log data in memory;

wherein the executed instructions cause the on-trip monitoring system to further determine the degradation level for the respective AV based on a retrospective analysis of the live log data from the respective AV.

9. The on-trip monitoring system of claim 8, wherein the retrospective analysis comprises at least one of an analysis of AV predictions of trajectories of external entities versus actual trajectories of the external entities, and an analysis of object classification accuracy.

10. A non-transitory computer readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to:

monitor live log data from autonomous vehicles (AVs) operating throughout a given region;

determine a degradation level for a respective AV of the AVs based on the live log data from the respective AV; and

when the degradation level exceeds a determined threshold, transmit an update command to the respective AV to service or decommission the respective AV;

wherein the determined threshold corresponds to a variable risk threshold dependent upon a set of current conditions comprising at least one of lighting conditions, weather conditions, a time of day, day of week, traffic conditions, or road surface conditions.

11. The non-transitory computer readable medium of claim 10, wherein the live log data comprise sensor data from the AVs, and wherein the executed instructions cause the one or more processors to determine the degradation level based, at least in part, on a data quality of the sensor data from the respective AV.

12. The non-transitory computer readable medium of claim 10, wherein the live log data indicates a calibration fault condition with at least one sensor of the respective AV.

13. The non-transitory computer readable medium of claim 10, wherein the live log data comprises at least one of diagnostics data or telemetry data.

14. The non-transitory computer readable medium of claim 10, and wherein the executed instructions further cause the one or more processors to:

manage an on-demand transportation service by matching transport requests from requesting users with the AVs operating throughout the given region.

15. The non-transitory computer readable medium of claim 10, wherein the variable risk threshold further depends upon a predicted set of conditions comprising at least one of predicted lighting conditions, predicted weather conditions, predicted traffic conditions, or predicted road surface conditions.

16. The non-transitory computer readable medium of claim 10, wherein the degradation level of the respective AV indicates at least one of a required hardware upgrade, a required software upgrade, required standard hardware maintenance, or required standard mechanical maintenance.

17. The non-transitory computer readable medium of claim 10, wherein the executed instructions further cause the one or more processors to:

record the live log data in memory;

wherein the executed instructions cause the one or more processors to determine the degradation level for the respective AV based on a retrospective analysis of the live log data.

18. A computer-implemented method of facilitating an on-demand transportation service, the method being performed by one or more processors and comprising:

monitoring live log data from autonomous vehicles (AVs) operating throughout a given region;

determining a degradation level for a respective AV of the AVs based on the live log data from the respective AV; and

when the degradation level exceeds a determined threshold, transmitting an update command to the respective AV to service or decommission the respective AV;

wherein the determined threshold corresponds to a variable risk threshold dependent upon a set of current conditions comprising at least one of lighting conditions, weather conditions, a time of day, day of week, traffic conditions, or road surface conditions.