Consideration of Risks in Active Sensing for an Autonomous Vehicle

• US 20160082953A1
• Filed: 09/24/2015
• Published: 03/24/2016
• Est. Priority Date: 05/14/2012
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Teller, Eric, Lombrozo, Peter
• Granted Patent: US 9,682,704 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B60K 2360/175 Autonomous driving
• CPC Class Codes: B60K 2370/175 Autonomous driving
• CPC Class Codes: B60K 35/28 characterised by the type of the output information, e.g. video entertainment or vehicle dynamics information; characterised by the purpose of the output information, e.g. for attracting the attention of the driver
• CPC Class Codes: B60W 2420/10 Transducer, e.g. piezoelectric elements
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2420/408 Radar; Laser, e.g. lidar
• CPC Class Codes: B60W 2420/50 Magnetic or electromagnetic sensors
• CPC Class Codes: B60W 2420/54 Audio sensitive means, e.g. ultrasound
• CPC Class Codes: B60W 2520/125 Lateral acceleration
• CPC Class Codes: B60W 2520/14 Yaw
• CPC Class Codes: B60W 2520/16 Pitch
• CPC Class Codes: B60W 2520/18 Roll
• CPC Class Codes: B60W 2540/12 Brake pedal position
• CPC Class Codes: B60W 2540/14 Clutch pedal position
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2554/20 Static objects
• CPC Class Codes: B60W 2554/4029 Pedestrians
• CPC Class Codes: B60W 2554/4041 Position
• CPC Class Codes: B60W 2554/806 Relative heading
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 2900/00 : Indexing codes relating to the purpose of, or problem solved of road vehicle drive control systems not otherwise provided for in groups B60W30/00
• 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 30/08 : Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
• CPC Class Codes: B60W 30/18163 : Lane change; Overtaking manoeuvres
• CPC Class Codes: B60W 60/0016 : of the vehicle or its occupants

Abstract

An autonomous vehicle configured for active sensing may also be configured to weigh expected information gains from active-sensing actions against risk costs associated with the active-sensing actions. An example method involves: (a) receiving information from one or more sensors of an autonomous vehicle, (b) determining a risk-cost framework that indicates risk costs across a range of degrees to which an active-sensing action can be performed, wherein the active-sensing action comprises an action that is performable by the autonomous vehicle to potentially improve the information upon which at least one of the control processes for the autonomous vehicle is based, (c) determining an information-improvement expectation framework across the range of degrees to which the active-sensing action can be performed, and (d) applying the risk-cost framework and the information-improvement expectation framework to determine a degree to which the active-sensing action should be performed.

Claims

1. A computer-implemented method comprising:

(i) receiving, by a computing system, information from one or more sensors of an autonomous vehicle, wherein one or more control processes for the autonomous vehicle are based upon the information;

(ii) determining, by the computing system, an information-improvement expectation that corresponds to an active-sensing action, wherein the active-sensing action comprises an action that is performable by the autonomous vehicle to potentially improve the information upon which at least one of the control processes for the autonomous vehicle is based;

(iii) determining, by the computing system, a risk cost that corresponds to the active-sensing action;

(iv) determining, by the computing system, whether or not the risk cost is less than a threshold risk cost, wherein the threshold risk cost corresponds to the information-improvement expectation;

(v) if the risk cost is less than the threshold risk cost, then initiating the active-sensing action; and

(vi) otherwise, if the risk cost is greater than or equal to the threshold risk cost, then making an adjustment to the active-sensing action.

2. The method of claim 1, wherein the one or more sensors comprise one or more of:

(a) at least one camera, (b) at least one microphone, (c) a Global Positioning System (GPS), (d) at least one accelerometer, (e) at least one gyroscope, (f) at least one compass, (g) a RADAR, (h) at least one laser rangefinder, (i) LIDAR, (j) at least one steering sensor, (k) a throttle sensor, and (l) at least one brake sensor.

3. The method of claim 1, wherein the active-sensing action comprises one or more of:

(a) a change in speed of the autonomous vehicle, (b) a change in position of the autonomous vehicle relative to an aspect of an environment of the autonomous vehicle, (c) a change in position of the autonomous vehicle within a lane, (d) a change in position of at least one of the sensors, (e) a change in operation of at least one of the sensors, and/or (f) a change to the processing of sensor data from at least one of the sensors, wherein the sensor data provides information upon which at least one control process is based.

4. The method of claim 1, wherein determining the information-improvement expectation that corresponds to the active-sensing action comprises:

determining an information value of sensor data in a first state of the autonomous vehicle;

determining an expected information value of the sensor data that is expected to be provided in a second state of the autonomous vehicle; and

subtracting the information value from the expected information value to determine an information-improvement value for the active sensing action.

5. The method of claim 1, wherein determining the information-improvement expectation that corresponds to the active-sensing action comprises:

(i) determining an information-improvement value of a given improvement to the information upon which the at least one of the control process is based;

(ii) determining a probability of the given improvement occurring as a result of the autonomous vehicle performing the active-sensing action; and

(iii) multiplying the information value of the given improvement by the probability of the given improvement occurring to determine an expected information value for the given improvement.

6. The method of claim 1, wherein the risk cost is indicative of a risk associated with the autonomous vehicle performing the active-sensing action.

7. The method of claim 1, wherein the risk cost is indicative of a change in risk associated with the autonomous vehicle performing the active-sensing action.

8. The method of claim 1, wherein determining the risk cost that corresponds to the active-sensing action comprises determining a risk penalty for one or more bad events that could occur as a result of the active-sensing action.

9. The method of claim 8, wherein determining the risk penalty for a given bad event comprises:

determining a risk magnitude for the given bad event;

determining the probability of the given bad event as a result of the active-sensing action; and

multiplying the risk magnitude for the given bad event by the probability of the given bad event occurring to determine the risk penalty for the given bad event.

10. The method of claim 1:

wherein the active-sensing action comprises a movement of the autonomous vehicle into a different position relative to at least one other vehicle to potentially improve environmental information provided by image data from a camera; and

wherein determining the information-improvement expectation comprises determining an expected improvement to a process that is based on the environmental information, wherein the expected improvement corresponds to the movement of the autonomous vehicle into the different position relative to the at least one other vehicle.

11. The method of claim 1:

wherein the active-sensing action comprises an action by the autonomous vehicle to potentially improve a view of a GPS satellite; and

wherein determining the information-improvement expectation that corresponds to the active-sensing action comprises determining an expected improvement to a process that is based on data from a GPS signal, wherein the expected improvement corresponds to the action by the autonomous vehicle to improve the view of the GPS satellite.

12. The method of claim 1, wherein making the adjustment to the active-sensing action comprises changing the extent of the active-sensing action.

13. The method of claim 12, wherein changing the extent of the active-sensing action comprises one or more of:

(a) adjusting an amount of a change in speed of the autonomous vehicle, (b) adjusting at least one of a distance and a direction of a change in position of the autonomous vehicle relative to an aspect of an environment of the autonomous vehicle, (c) adjusting at least one of a distance and a direction of a change in position of the autonomous vehicle within a lane, (d) adjusting at least one of a distance and a direction of a change in position of at least one of the sensors, and (e) adjusting a degree of a change in operation of at least one of the sensors.

14. The method of claim 1, wherein the adjustment to the active-sensing action changes at least one of the information-improvement expectation and the determined risk cost corresponding to the active-sensing action.

15. The method of claim 1, further comprising, if the risk cost is greater than or equal to the threshold risk cost, repeating (ii) to (vi) for the adjusted active-sensing action until either the determined risk cost is less than the threshold risk cost, or a determination is made that no further adjustments should be made to the active-sensing action.

16. An autonomous-vehicle system comprising:

one or more sensor interfaces operable to receive data from one or more sensors of an autonomous vehicle; and

a computer system configured to;

(i) receive, via the one or more sensor interfaces, information from the one or more sensors, wherein one or more control processes for the autonomous vehicle are based upon the information;

(ii) determine an information-improvement expectation that corresponds to an active-sensing action, wherein the active-sensing action comprises an action that is performable by the autonomous vehicle to potentially improve the information upon which at least one of the control processes for the autonomous vehicle is based;

(iii) determine a risk cost that corresponds to the active-sensing action;

(iv) determine whether or not the risk cost is less than a threshold risk cost, wherein the threshold risk cost corresponds to the information-improvement expectation;

(v) if the risk cost is less than the threshold risk cost, then initiate the active-sensing action; and

(vi) if the risk cost is greater than or equal than the threshold risk cost, then make an adjustment to the active-sensing action.

17. The autonomous-vehicle system of claim 16, wherein the adjustment to the active-sensing action comprises a change in extent of the active-sensing action.

18. The autonomous-vehicle system of claim 16, wherein the change in extent the active-sensing action comprises one or more of:

(a) an adjustment to an amount of a change in speed of the autonomous vehicle, (b) an adjustment to at least one of a distance and a direction of a change in position of the autonomous vehicle relative to an aspect of an environment of the autonomous vehicle, (c) an adjustment to at least one of a distance and a direction of a change in position of the autonomous vehicle within a lane, (d) an adjustment to at least one of a distance and a direction of a change in position of at least one of the sensors, and (e) an adjustment to a degree of a change in operation of at least one of the sensors.

19. A method comprising:

receiving, by a computing system, information from one or more sensors of an autonomous vehicle, wherein one or more control processes for the autonomous vehicle are based upon the information;

determining, by the computing system, a risk-cost framework that indicates risk costs across a range of degrees to which an active-sensing action can be performed, wherein the active-sensing action comprises an action that is performable by the autonomous vehicle to potentially improve the information upon which at least one of the control processes for the autonomous vehicle is based;

determining, by the computing system, an information-improvement expectation framework that indicates information-improvement expectations across the range of degrees to which the active-sensing action can be performed;

applying, by the computing system, the risk-cost framework and the information-improvement expectation framework to determine a degree to which the active-sensing action should be performed; and

initiating the active-sensing action of the determined degree.

20. The method of claim 19, wherein the determined degree maximizes the information-improvement expectation corresponding to the active-sensing action, with a constraint that a score corresponding to the active-sensing action is less than a threshold score.

21. The method of claim 19, wherein determining the information-improvement expectation framework comprises:

determining information-improvement expectation data across one or more of;

(a) a range of speed changes for the autonomous vehicle, (b) a range of positional changes of the autonomous vehicle relative to an aspect of an environment of the autonomous vehicle, (c) a range of positional changes of the autonomous vehicle within a lane, (d) a range of positional changes of at least one of the sensors, and (e) a range of operational adjustments to at least one of the sensors.