Adaptive dynamic model for automated vehicle

Patent metadata

Field	Value
Publication number	US-10990102-B2
Application number	US-201715622284-A
Country	US
Kind code	B2
Filing date	Jun 14, 2017
Priority date	Jun 14, 2017
Publication date	Apr 27, 2021
Grant date	Apr 27, 2021

Abstract

An operating system for an automated vehicle includes a failure-detector and a controller. The failure-detector detects a component-failure on a host-vehicle. Examples of the component-failure include a flat-tire and engine trouble that reduces engine-power. The controller operates the host-vehicle based on a dynamic-model. The dynamic-model is varied based on the component-failure detected by the failure-detector.

First claim

We claim:

1. A system comprising:
a tire-pressure-detector that determines a tire-pressure of at least one tire of an automated vehicle;
a failure-detector that detects that a soft-tire or flat-tire has occurred when the tire pressure is less than a pressure-threshold;
a processor configured to:
adjust a dynamic-model of the automated vehicle based on the detected soft-tire or flat-tire, the dynamic-model representing a dynamic characterization of the automated vehicle;
predict, using the adjusted dynamic model, a dynamic behavior of the automated vehicle in response to steering, braking, acceleration or deceleration of the automated vehicle; and

a controller that operates the automated vehicle based on the adjusted dynamic-model.

2. The system in accordance with claim 1 , wherein the dynamic-model is adjusted by decreasing a maximum-curve-speed for a curve radius of an upcoming curve of a travel-lane.

3. The system of claim 1 , wherein multiple values of the pressure-threshold are used to continually vary the dynamic-model to cover instances of the soft-tire or the flat-tire.

4. The system of claim 1 , wherein the processor:
determines that a steering behavior of the automated vehicle is asymmetrical due to the soft-tire or flat-tire; and
adjusts the dynamic-model to anticipate the asymmetric behavior by increasing an expected change in steering to steer the automated vehicle through an upcoming curve of a travel-lane.

5. The system of claim 1 , wherein the processor:
determines that the automated vehicle is operating in manual mode where a human-operator is steering the automated vehicle; and
adjusts the dynamic-model to steer the automated vehicle to stay within a travel-lane when the human-operator allows the automated vehicle to deviate too far from a center of the travel-lane.

6. The system of claim 1 , wherein the pressure-threshold is less than a recommended-pressure for a given tire, and a soft-tire is detected when the tire-pressure is detected to be lower than the recommended-pressure.

7. A method comprising:
determining, using a tire-pressure detector, a tire-pressure of at least one tire of an automated vehicle;
detecting, using a failure-detector, that a soft-tire or flat-tire has occurred when the tire-pressure is less than a pressure-threshold;
responsive to the detecting, adjusting a dynamic-model of the automated vehicle, the dynamic-model representing a dynamic characterization of the automated vehicle;
predicting, using the dynamic-model, a dynamic behavior of the automated vehicle in response to steering, braking, acceleration or deceleration of the automated vehicle; and
operating, using a controller, the automated vehicle based on the adjusted dynamic-model.

8. The method in accordance with claim 7 , wherein adjusting the dynamic-model includes decreasing a maximum-curve-speed for a curve radius of an upcoming curve of a travel-lane is decreased.

9. The method of claim 7 , wherein multiple values of the pressure-threshold are used to continually vary the dynamic-model to cover instances of the soft-tire or the flat-tire.

10. The method of claim 7 , further comprising:
determining that a steering behavior of the automated vehicle is asymmetrical due to the soft-tire or the flat-tire; and
adjusting the dynamic-model to anticipate the asymmetric behavior by increasing an expected change in steering to steer the automated vehicle through an upcoming curve of a travel-lane.

11. The method of claim 7 , further comprising:
determining that the automated vehicle is operating in manual mode where a human-operator is steering the automated vehicle; and
adjusting the dynamic-model to steer the automated vehicle to stay within a travel-lane when the human-operator allows the automated vehicle to deviate too far from a center of the travel-lane.

12. The method of claim 7 , wherein the pressure-threshold is less than a recommended-pressure for a given tire, and a soft-tire is detected when the tire-pressure is detected to be lower than the recommended-pressure.

13. A non-transitory, computer-readable storage medium having instructions stored thereon that when executed by one or more processors, cause the one or more processors to perform operations comprising:
determining, using a tire-pressure detector, a tire-pressure of at least one tire of an automated vehicle;
detecting, using a failure-detector, that a soft-tire or flat-tire has occurred when the tire-pressure is less than a pressure-threshold;
responsive to the detecting, adjusting a dynamic-model of the automated vehicle, the dynamic-model representing a dynamic characterization of the automated vehicle and predicting a dynamic behavior of the automated vehicle in response to steering, braking, acceleration or deceleration of the automated vehicle; and
operating, using a controller, the automated vehicle based on the adjusted dynamic-model.

14. The non-transitory, computer-readable storage medium in accordance with claim 13 , wherein adjusting the dynamic-model includes decreasing a maximum-curve-speed for a curve radius of an upcoming curve of a travel-lane.

15. The non-transitory, computer-readable storage medium of claim 13 , wherein multiple values of the pressure-threshold are used to continually vary the dynamic-model to cover instances of the soft-tire or the flat-tire.

16. The non-transitory, computer-readable storage medium of claim 13 , further comprising:
determining that a steering behavior of the automated vehicle is asymmetrical due to the soft-tire or the flat-tire; and
adjusting the dynamic-model to anticipate the asymmetric behavior by increasing an expected change in steering to steer the automated vehicle through an upcoming curve of a travel-lane.

17. The non-transitory, computer-readable storage medium of claim 13 , further comprising:
determining that the automated vehicle is operating in manual mode where a human-operator is steering the automated vehicle; and
adjusting the dynamic-model to steer the automated vehicle to stay within a travel-lane when the human-operator allows the automated vehicle to deviate too far from a center of the travel-lane.

18. The non-transitory, computer-readable storage medium of claim 13 , wherein the pressure-threshold is less than a recommended-pressure for a given tire, and a soft-tire is detected when the tire-pressure is detected to be lower than the recommended-pressure.

Assignees

• Motional Ad Llc

Inventors

• Wei Junqing
• Sun Ludong
• Batts Zachary Thomas
• Snider Jarrod M
• Kim Junsung

Classifications

• B60W50/0205 Primary

  Diagnosing or detecting failures; Failure detection models · CPC title

• B60W2520/28

  Wheel speed · CPC title

• B60W50/038

  Limiting the input power, torque or speed · CPC title

• B60W2520/10

  Longitudinal speed · CPC title

• B60W2050/021

  Means for detecting failure or malfunction · CPC title