Adaptive dynamic model for automated vehicle
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.
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.