Mode transition for an autonomous vehicle

• US 9,365,213 B2
• Filed: 04/30/2014
• Issued: 06/14/2016
• Est. Priority Date: 04/30/2014
• Status: Active Grant

• Current Assignee: HERE Global B.V. (Nokia Corporation)
• Original Assignee: HERE Global B.V. (Nokia Corporation)
• Inventors: Stenneth, Leon Oliver, Boroditsky, Vladimir
• Primary Examiner(s): BUTLER, RODNEY ALLEN
• Application Number:
  US14/266,085
• Publication Number:
  US 20150314780A1
• Time in Patent Office: 776 Days
• US Class Current: 1/1
• CPC Class Codes: B60W 2050/007 Switching between manual and automatic parameter input, and vice versa
• CPC Class Codes: B60W 2050/0075 Automatic parameter input, automatic initialising or calibrating means
• CPC Class Codes: B60W 2050/0095 Automatic control mode change
• CPC Class Codes: B60W 2540/229 Attention level, e.g. attentive to driving, reading or sleeping
• CPC Class Codes: B60W 2540/24 Drug level, e.g. alcohol
• CPC Class Codes: B60W 2552/05 Type of road, e.g. motorways, local streets, paved or unpaved roads
• CPC Class Codes: B60W 2554/406 Traffic density
• CPC Class Codes: B60W 2555/20 Ambient conditions, e.g. wind or rain
• CPC Class Codes: B60W 2556/10 Historical data
• CPC Class Codes: B60W 2556/20 Data confidence level
• CPC Class Codes: B60W 2556/45 External transmission of data to or from the vehicle
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 2556/65 Data transmitted between vehicles
• CPC Class Codes: B60W 30/00 Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
• CPC Class Codes: B60W 30/182 Selecting between different operative modes, e.g. comfort and performance modes
• CPC Class Codes: B60W 60/0059 Estimation of the risk associated with autonomous or manual driving, e.g. situation too complex, sensor failure or driver incapacity
• CPC Class Codes: G05D 1/0061 for transition from automatic pilot to manual pilot and vice versa

Abstract

An autonomous vehicle may be operable in an autonomous mode and a manual mode. A confidence threshold is accessed from a database. The confidence threshold may be associated with a particular geographic area containing the autonomous vehicle. The confidence threshold may be constant for the geographic area accessible by the autonomous vehicle. A computing device calculates a vehicle confidence level based on at least one confidence factor and compares the confidence threshold to the vehicle confidence level. The computing device generates a driving mode command for a vehicle based on the comparison. In one example, the driving mode command transitions the autonomous vehicle to the autonomous mode, if applicable, when the vehicle confidence score exceeds the confidence threshold. In one example, the driving mode command transitions the autonomous vehicle to the manual mode, if applicable, when the vehicle confidence score does not exceed the confidence threshold.

Claims

1. A method comprising:

accessing, from a database, a confidence threshold for a geographic area, wherein the geographic area has at least one geographic characteristic;

calculating, using a processor, a vehicle confidence level based on at least one confidence factor;

performing a comparison of the confidence threshold to the vehicle confidence level, wherein the confidence threshold corresponds to the at least one geographic characteristic;

generating a driving mode command for a vehicle based on the comparison; and

transitioning, automatically using the processor, the vehicle to or from an autonomous driving mode based on the vehicle mode command when the comparison is within the confidence threshold for the geographic area based on the at least one geographic characteristic.

2. The method of claim 1, wherein the at least one confidence factor includes sensor data from one or more sensors.

3. The method of claim 2, wherein the one or more sensors include a weather sensor, a driving sensor, a road status sensor, or a parking sensor.

4. The method of claim 2, wherein the at least one confidence factor includes correctness data.

5. The method of claim 1, further comprising:

receiving location data for the vehicle in the geographic area, wherein the database is accessed according to the location data for the confidence threshold for the geographic area.

6. The method of claim 1, further comprising:

adjusting the vehicle confidence level based on a quantity of sensors.

7. The method of claim 1, further comprising:

receiving sensor data from a second vehicle; and

increasing the vehicle confidence level based on the sensor data from the second vehicle.

8. The method of claim 1, wherein the vehicle confidence level is based on sensor data for weather in the geographic area and sensor data for operation of the vehicle.

9. The method of claim 8, wherein the sensor data for weather in the geographic data is a combination of real-time data and historical data.

10. The method of claim 1, wherein transitioning the vehicle comprises:

transitioning from a manual driving mode to an autonomous driving mode based on the vehicle mode command.

11. The method of claim 1, wherein the geographic characteristic is traffic data in the geographic area.

12. The method of claim 11, wherein when the traffic data shows an increase in traffic in a geographic zone, compared to a historical baseline of traffic, the confidence threshold is raised or lowered.

13. 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 at least perform;

accessing a confidence threshold for at least one geographic area;

calculating a vehicle confidence score based on sensor data;

performing a comparison of the confidence threshold to the vehicle confidence score, wherein the confidence threshold corresponds to the at least one geographic area; and

generating an autonomous driving command for a vehicle based on the comparison,

wherein the autonomous driving command includes a transition to autonomous mode or a transition to manual mode when the comparison is within the confidence threshold for the at least one geographic area.

14. The apparatus of claim 13, wherein sensor data describes weather in proximity of the vehicle or traffic in proximity of the vehicle.

15. The apparatus of claim 13, wherein sensor data describes correctness of an array of sensors.

16. The apparatus of claim 13, wherein sensor data describes a road status for a road the vehicle is traveling on.

17. The apparatus of claim 13, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least perform:

receiving sensor data from a second vehicle; and

increasing the vehicle confidence score based on the sensor data from the second vehicle.

18. The apparatus of claim 13, wherein the autonomous driving command includes an automatic transition to autonomous mode.

19. The apparatus of claim 13, wherein the sensor data includes first sensor data for weather in the vicinity of the vehicle and second sensor data for operation of the vehicle.