IP Library Granted Patent US 12691901
Granted Patent B2
US 12691901 · App. 19/340,391 · Granted Jul 28, 2026

System and method for safe predictive control of autonomous vehicles

Inventors: Vahid Azimi (Mountain View, CA); Apeksha Kumavat (Palo Alto, CA); Ehsan Sabouni (Mountain View, CA); Parsa Taleb (Mountain View, CA); Arjun Narang (Mountain View, CA); Gautam Narang (Palo Alto, CA)
Assignee: Gatik AI Inc.
B60W60/001B60W10/20B60W50/045B60W2520/10B60W2520/12B60W2520/14B60W2556/40B60W2710/20
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12691901
App. No.
19/340,391
Granted
Jul 28, 2026
Kind
B2
Abstract

In variants, the system can include: a localization module; an objective generator; a mapping module; and a controller system including a set of Model Predictive Control (MPC) modules, a safety function generator, and a tire stiffness estimation module. The system can optionally include or be used with a Drive-by-Wire (DBW) system. The system functions to control an autonomous vehicle to track a planned trajectory. The system and/or components thereof are preferably located on a set of computing systems of an autonomous vehicle, but can additionally and/or alternatively be located elsewhere.

Claims (46)

1 . A method, comprising:

capturing a set of measurements of a scene surrounding a vehicle;

based on the set of measurements, determining a trajectory for the vehicle;

based on the trajectory, determining a set of constraints for a pair of controllers, the pair of controllers comprising a lateral controller and a longitudinal controller, wherein the lateral controller and longitudinal controller determine vehicle commands in separate and distinct domains;

during a first timestep:

based on the trajectory and using a first controller of the pair of controllers, determining a first set of vehicle commands and a first set of coupling signals; and

based on the trajectory, the set of constraints, and the first set of coupling signals, and using a second controller of the pair of controllers, determining a second set of vehicle commands and a second set of coupling signals; and

during a second timestep:

based on the second set of coupling signals, and using the first controller, determining a third set of vehicle commands and a third set of coupling signals; and

based on the third set of coupling signals, using the second controller, determining a fourth set of vehicle commands;

determining a set of vehicle actuator control instructions based on the third set of vehicle commands and the fourth set of vehicle commands; and

controlling a set of actuators of the vehicle according to the set of vehicle actuator control instructions.

2 . The method of claim 1 , wherein the first controller is the longitudinal controller, wherein the first set of vehicle commands comprises a longitudinal kinematic parameter, and wherein the second controller is the lateral controller, wherein the second set of vehicle commands comprises an angular kinematic parameter.

3 . The method of claim 2 , wherein the first set of coupling signals and second set of coupling signals represent kinematic interdependencies between lateral and longitudinal vehicle dynamics.

4 . The method of claim 3 , wherein the first set of coupling signals comprises a longitudinal velocity of the vehicle, and the second set of coupling signals comprises a yaw rate and lateral velocity of the vehicle.

5 . The method of claim 1 , wherein the first and second set of vehicle commands comprise vehicle component controls.

6 . The method of claim 1 , wherein the set of constraints comprises a steering constraint having a 4 th -order control barrier function based on a lateral position error and an orientation error, and wherein determining the second set of vehicle commands comprises using the steering constraint.

7 . The method of claim 1 , wherein determining the set of constraints comprises:

based on a virtual representation of a set of objects in the scene, determining a set of regions within a trajectory error space defined by:

a first axis representing a translational error relative to the trajectory; and

a second axis representing a rotational error relative to the trajectory; and

transforming the set of regions into the set of constraints.

8 . The method of claim 7 , wherein the set of regions is a time series of multiple regions.

9 . The method of claim 7 , wherein the set of constraints comprises control barrier functions used by a strict subset of the pair of controllers during vehicle commands determination.

10 . The method of claim 7 , wherein determining the set of regions comprises generating a convex approximation of a plurality of error values in the trajectory error space.

11 . A method, comprising:

using a set of sensors onboard a vehicle, capturing a set of measurements of a set of objects proximal to the vehicle;

based on the set of measurements, determining a virtual representation of the set of objects;

based on the set of measurements, determining a vehicle trajectory;

based on the virtual representation of the set of objects, determining a set of regions within a trajectory error space defined by:

a first component of vehicle trajectory error; and

a second component of vehicle trajectory error distinct from the first component of vehicle trajectory error, wherein a region of the set of regions defines a constraint on error in the first component of vehicle trajectory as a function of the second component of vehicle trajectory error;

based on the set of regions in trajectory error space, determining a set of constraints;

based on the trajectory and the set of constraints, using a set of controllers, determining a set of vehicle controls; and

controlling a powertrain of the vehicle based on the set of vehicle controls.

12 . The method of claim 11 , wherein each region of the set of regions comprises a respective kinematic operating envelope for the vehicle relative to the trajectory.

13 . The method of claim 12 , wherein the first component of trajectory error is a lateral translational deviation from the trajectory, and the second component of trajectory error is a heading deviation from the trajectory.

14 . The method of claim 11 , wherein the set of regions comprises a time series of regions.

15 . The method of claim 14 , wherein determining the set of vehicle controls comprises using multiple distinct regions of the time series of regions.

16 . The method of claim 14 , wherein each region of the set of regions corresponds to a respective timestep in a control horizon.

17 . The method of claim 16 , wherein an object of the set of objects corresponds to the respective timestep, and detection of the respective object triggers determination of the respective region.

18 . The method of claim 14 , wherein a consecutive subset of regions of the time series of regions are identical.

19 . The method of claim 11 , wherein the set of controllers comprises:

a lateral controller determining commands for a first set of vehicle actuators; and

a longitudinal controller determining control instructions for a second set of vehicle actuators distinct from the first set of vehicle actuators.

20 . The method of claim 11 , wherein the set of constraints applies to exactly one controller of the set of controllers, wherein the exactly one controller is the lateral controller.