	US 12,269,503 B2
	Method of anticipatory control for automated driving
Yubiao Zhang, Sterling Heights, MI (US); and Bakhtiar B. Litkouhi, Washington, MI (US)
Assigned to GM GLOBAL TECHNOLOGY OPERATIONS LLC, Detroit, MI (US)
Filed by GM Global Technology Operations LLC, Detroit, MI (US)
Filed on Nov. 16, 2022, as Appl. No. 18/055,953.
Prior Publication US 2024/0157963 A1, May 16, 2024
Int. Cl. B60W 60/00 (2020.01); B60W 50/00 (2006.01)

CPC B60W 60/001 (2020.02) [B60W 50/0097 (2013.01); B60W 2050/0028 (2013.01); B60W 2552/15 (2020.02); B60W 2552/40 (2020.02)]

20 Claims

1. A method of anticipatory control for automated driving, comprising:

receiving planned path data, road data, and speed profile data, wherein the planned path data includes information about a planned path of a vehicle, and the planned path includes a plurality of steps, and the speed profile data includes a planned speed of the vehicle along the planned path;

determining a plurality of anticipatory constraints for each of the plurality of steps along the planned path using the planned path data, the road data, and the speed profile data, wherein the anticipatory constraints include tire force limits for each of the plurality of steps of the planned path and steering limits for each of the plurality of steps of the planned path;

determining a plurality of control actions using a Model Predictive Control (MPC), wherein a prediction model of the MPC is updated in real time with the plurality of anticipatory constraints for each of the plurality of steps along the planned path and the road data for each of the plurality of steps along the planned path; and

determining a reference trajectory for the planned path of the vehicle, wherein the reference trajectory includes a reference position, a reference velocity, and an initial steering profile for the planned path, wherein the reference trajectory and desired vehicle states are obtained using one or more of an offline bicycle model and a quasi-stationary approach,

wherein the offline bicycle model operates according to:

v_y=−r+ρV_x Eq. 1

r=C_rL/I_zV_x²V_y−bLC_r/I_zV_x²r+aM/I_zρV_x Eq. 2

δ_ƒ=C_ƒ+C_r/C_ƒV_xV_y+C_ƒα−C_rb/C_ƒV_xr+M/C_ƒρV_x² Eq. 3

Δψ=−V_yV_x Eq. 4

where:

M is a total mass of the vehicle; δ_ƒ is an initial road wheel angle command; r is a yaw rate of the vehicle; V_xis a longitudinal speed of the vehicle; C_ris a tire cornering stiffness of rear tires of the vehicle; C_fis a tire cornering stiffness of front tires of the vehicle; ρ is a curvature of the road; V_yis a lateral speed of the vehicle; L is a distance from a front axle to a rear axle of the vehicle; I_zis a yaw inertia of the vehicle; a is the distance from a center of gravity of the vehicle to the front axle of the vehicle; b is a distance from the center of gravity of the vehicle to the rear axle of the vehicle; and Δψ is a heading orientation error of the vehicle with respect to a centerline of the road, and

wherein the quasi-stationary approach operates according to:

Δy=0 Eq. 5

Δψ=−(b−MaV_x²/LC_r)ρ Eq. 6

V_y=(b−MaV_x²/LC_r)ρV_x Eq. 7

r=ρV_x Eq. 8

where: Δy is an orthogonal distance from the center of gravity of the vehicle to the centerline of the road; Δψ is the heading orientation error of the vehicle with respect to the centerline of the road; r is the yaw rate of the vehicle; V_xis the longitudinal speed of the vehicle; ρ is the curvature of the road; b is the distance from the center of gravity of the vehicle to the rear axle of the vehicle; M is the total mass of the vehicle; L is the distance from the front axle to the rear axle of the vehicle; C_ris the tire cornering stiffness of the rear tires; and a is the distance from the center of gravity of the vehicle the front axle of the vehicle; and

controlling the vehicle using the plurality of control actions to cause the vehicle to autonomously follow the planned path.