Humanized steering model for automated vehicles

• US 9,914,475 B2
• Filed: 10/05/2015
• Issued: 03/13/2018
• Est. Priority Date: 10/05/2015
• Status: Active Grant

• Current Assignee: Aptiv Technologies AG (Aptiv PLC)
• Original Assignee: Delphi Technologies, Inc. (BorgWarner Incorporated)
• Inventors: Sun, Ludong, Laur, Michael H., Wieskamp, Jonathan L., Yan, Miao
• Primary Examiner(s): Nguyen, Cuong H
• Application Number:
  US14/874,760
• Publication Number:
  US 20170096164A1
• Time in Patent Office: 890 Days
• Field of Search: 701 28, 701 23, 701 36, 701 44, 706900-905, 706 25- 26, 706 41, 706 44, 312587
• CPC Class Codes: B60G 17/0162 mainly during a motion involving steering operation, e.g. cornering, overtaking B60G17/0164 takes precedence
• CPC Class Codes: B60G 2400/40 Steering conditions
• CPC Class Codes: B62D 1/04 Hand wheels
• CPC Class Codes: B62D 1/28 non-mechanical , e.g. following a line or other known markers
• CPC Class Codes: B62D 6/002 computing target steering angles for front or rear wheels B62D7/159 takes precedence
• CPC Class Codes: B62D 6/007 adjustable by the driver, e.g. sport mode
• CPC Class Codes: G01S 13/931 of land vehicles
• CPC Class Codes: G01S 2013/9323 Alternative operation using light waves
• CPC Class Codes: G01S 7/417 involving the use of neural networks
• CPC Class Codes: G06N 3/044 Recurrent networks, e.g. Hopfield networks
• CPC Class Codes: G06N 3/048 Activation functions
• CPC Class Codes: G06N 3/084 Backpropagation, e.g. using gradient descent

Abstract

A humanized steering system for an automated vehicle includes one or more steering-wheels operable to steer a vehicle, an angle-sensor configured to determine a steering-angle of the steering-wheels, a hand-wheel used by an operator of the vehicle to influence the steering-angle and thereby manually steer the vehicle, a steering-actuator operable to influence the steering-angle thereby steer the vehicle when the operator does not manually steer the vehicle, a position-sensor operable to indicate a relative-position an object proximate to the vehicle, and a controller. The controller is configured to receive the steering-angle and the relative-position, determine, using deep-learning techniques, a steering-model based on the steering-angle and the relative-position, and operate the steering-actuator when the operator does not manually steer the vehicle to steer the vehicle in accordance with the steering-model, whereby the vehicle is steered in a manner similar to how the operator manually steers the vehicle.

Claims

1. A humanized steering system for an automated vehicle, said system comprising:

one or more steering-wheels operable to steer a vehicle;

an angle-sensor configured to determine a steering-angle of the steering-wheels;

a hand-wheel used by an operator of the vehicle to influence the steering-angle and thereby manually steer the vehicle;

a steering-actuator operable to influence the steering-angle thereby steer the vehicle when the operator does not manually steer the vehicle;

a position-sensor operable to indicate a relative-position an object proximate to the vehicle; and

a controller configured to

receive the steering-angle and the relative-position,

determine, using deep-learning techniques, a steering-model based on the steering-angle and the relative-position while the operator is using the hand-wheel to manually steer the vehicle, and

operate the steering-actuator when the operator does not manually steer the vehicle to steer the vehicle in accordance with the steering-model, whereby the vehicle is steered in a manner similar to how the operator manually steers the vehicle.

2. The system in accordance with claim 1, wherein the steering-model outputs a desired-angle of steering-wheels to steer the vehicle when the operator does not manually steer the vehicle.

3. The system in accordance with claim 1, wherein the steering-model is characterized by a binary-vector composed of a plurality of bits indicative of parameters of the steering-model.

4. The system in accordance with claim 3, wherein the binary-vector includes a parameter indicative of a weather-condition.

5. The system in accordance with claim 4, wherein the weather-condition includes sunny, cloudy, foggy, rainy, snowy, windy, and temperature.

6. The system in accordance with claim 3, wherein the binary-vector includes a parameter indicative of a vehicle-state.

7. The system in accordance with claim 6, wherein the vehicle-state includes lane-position, lateral-acceleration, longitudinal-acceleration, vehicle-speed, and the steering-angle.

8. The system in accordance with claim 3, wherein the binary-vector includes a parameter indicative of a vehicle-specification.

9. The system in accordance with claim 8, wherein the vehicle-specification includes vehicle-size, vehicle-mass, steering-response-time, and engine-power.

10. The system in accordance with claim 3, wherein the binary-vector includes a parameter indicative of an object-characteristic.

11. The system in accordance with claim 10, wherein the object-characteristic includes object-location, object-vector, object-classification, and lane-position.

12. The system in accordance with claim 3, wherein the binary-vector includes parameters indicative of a weather-condition, a vehicle-state, a vehicle-specification, and an object-characteristic.