Learning based controller for autonomous driving
US-2021291862-A1 · Sep 23, 2021 · US
US12434722B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12434722-B2 |
| Application number | US-202217953568-A |
| Country | US |
| Kind code | B2 |
| Filing date | Sep 27, 2022 |
| Priority date | Sep 29, 2021 |
| Publication date | Oct 7, 2025 |
| Grant date | Oct 7, 2025 |
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A computer implemented method for lateral control of a vehicle comprises the following steps carried out by computer hardware components: determining a location error of the vehicle; determining an orientation error of the vehicle; determining a cost function based on the location error and the orientation error using a circular transformation; and processing the cost function in a model predictive controller to control the vehicle laterally.
Opening claim text (preview).
The invention claimed is: 1. A computer-implemented method for lateral control of a vehicle, the computer-implemented method being carried out by computer hardware components and comprising: determining a location error of the vehicle; determining an orientation error of the vehicle; determining a cost function based on the location error and the orientation error using a circular transformation; and processing the cost function in a model predictive controller to control the vehicle laterally, wherein: the cost function includes an integral over an error term, the error term involves both the location error and the orientation error, the error term includes a product based on the location error and the orientation error, the cost function is determined according to equations (a) and (b): e tr =cos θ e 2 *tan −1 ( d−d ref )+sin θ e 2 *θ e (a) J=∫ 0 T e tr 2 (b) θ e represents the orientation error with respect to a reference, d represents an initial value of a lateral offset from a vehicle sensor input, d ref represents a reference value that the vehicle should track, J represents the cost function that needs to be minimized, and T represents a prediction horizon. 2. The computer-implemented method of claim 1 , wherein the cost function comprises a non-holonomic ellipsoid cost function. 3. The computer-implemented method of claim 1 , wherein the cost function is based on a cosine function. 4. The computer-implemented method of claim 1 , wherein the cost function is based on a sine function. 5. The computer-implemented method of claim 1 , wherein the cost function is based on a tangent function. 6. The computer-implemented method of claim 1 , wherein controlling the vehicle laterally comprises determining the lateral offset of the vehicle. 7. The computer-implemented method of claim 1 , wherein controlling the vehicle laterally comprises determining an optimal steering angle value. 8. A computer system comprising a plurality of computer hardware components configured to carry out instructions including: determining a location error of a vehicle; determining an orientation error of the vehicle; determining a cost function based on the location error and the orientation error using a circular transformation; and processing the cost function in a model predictive controller to control the vehicle laterally, wherein: the cost function includes an integral over an error term, the error term involves both the location error and the orientation error, the error term includes a product based on the location error and the orientation error, the cost function is determined according to equations (a) and (b): e tr =cos θ e 2 *tan −1 ( d−d ref )+sin θ e 2 *θ e (a) J=∫ 0 T e tr 2 (b) θ e represents the orientation error with respect to a reference, d represents an initial value of a lateral offset from a vehicle sensor input, d ref represents a reference value that the vehicle should track, J represents the cost function that needs to be minimized, and T represents a prediction horizon. 9. A vehicle comprising: the computer system of claim 8 ; and a sensor configured to determine the location error and/or the orientation error. 10. The vehicle of claim 9 , wherein the sensor comprises at least one of a radar sensor, a lidar sensor, an ultrasound sensor, a camera, or a global navigation satellite system sensor. 11. A non-transitory computer readable medium comprising instructions including: determining a location error of a vehicle; determining an orientation error of the vehicle; determining a cost function based on the location error and the orientation error using a circular transformation; and processing the cost function in a model predictive controller to control the vehicle laterally, wherein: the cost function includes an integral over an error term, the error term involves both the location error and the orientation error, the error term includes a product based on the location error and the orientation error, the cost function is determined according to equations (a) and (b): e tr =cos θ e 2 *tan −1 ( d−d ref )+sin θ e 2 *θ e (a) J=∫ 0 T e tr 2 (b) θ e represents the orientation error with respect to a reference, d represents an initial value of a lateral offset from a vehicle sensor input, d ref represents a reference value that the vehicle should track, J represents the cost function that needs to be minimized, and T represents a prediction horizon.
Radar; Laser, e.g. lidar · CPC title
Image sensing, e.g. optical camera · CPC title
using a predictor · CPC title
Audio sensitive means, e.g. ultrasound · CPC title
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