METHOD FOR CONTROLLING A VEHICLE IN ACCORDANCE WITH PARAMETERS PREFERRED BY AN IDENTIFIED DRIVER

• US 20170217428A1
• Filed: 04/17/2017
• Published: 08/03/2017
• Est. Priority Date: 04/02/2014
• Status: Active Grant

• Current Assignee: Magna Electronics Incorporated (Magna International Incorporated)
• Original Assignee: Magna Electronics Incorporated (Magna International Incorporated)
• Inventors: Tan, Honghao, Tedesco, Brian J.
• Granted Patent: US 9,950,707 B2
• Time in Patent Office: Days
• CPC Class Codes: B60W 10/04 including control of propulsion units
• CPC Class Codes: B60W 10/18 including control of braking systems
• CPC Class Codes: B60W 10/20 including control of steering systems
• CPC Class Codes: B60W 2050/0088 Adaptive recalibration
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2420/408 Radar; Laser, e.g. lidar
• CPC Class Codes: B60W 2540/043 Identity of occupants
• CPC Class Codes: B60W 2540/30 Driving style
• CPC Class Codes: B60W 2552/30 Road curve radius
• CPC Class Codes: B60W 2552/35 Road bumpiness, e.g. potholes
• CPC Class Codes: B60W 2552/40 Coefficient of friction
• CPC Class Codes: B60W 2552/53 Road markings, e.g. lane marker or crosswalk
• CPC Class Codes: B60W 2554/801 Lateral distance
• CPC Class Codes: B60W 2554/802 Longitudinal distance
• CPC Class Codes: B60W 2554/804 Relative longitudinal speed
• CPC Class Codes: B60W 2555/20 Ambient conditions, e.g. wind or rain
• CPC Class Codes: B60W 2556/00 Input parameters relating to data
• CPC Class Codes: B60W 2556/10 Historical data
• CPC Class Codes: B60W 2710/18 Braking system
• CPC Class Codes: B60W 2710/20 Steering systems
• CPC Class Codes: B60W 2720/10 : Longitudinal speed
• CPC Class Codes: B60W 2720/106 : Longitudinal acceleration
• CPC Class Codes: B60W 30/025 : related to comfort of drivers or passengers
• CPC Class Codes: B60W 30/12 : Lane keeping
• CPC Class Codes: B60W 30/14 : Adaptive cruise control
• CPC Class Codes: B60W 30/16 : Control of distance between vehicles, e.g. keeping a distance to preceding vehicle
• CPC Class Codes: B60W 50/0098 : Details of control systems ensuring comfort, safety or stability not otherwise provided for
• CPC Class Codes: G05D 1/0231 : using optical position detecting means position-fixing by using electromagnetic waves other than radio waves, e.g. optical position detecting means G01S5/16

Abstract

A method for controlling a vehicle includes providing a plurality of sensors at an equipped vehicle, capturing, via the plurality of sensors, data, and determining, via processing by a data processor of data captured by at least some of the plurality of sensors, information pertaining to distance to other vehicles present exterior the equipped vehicle. Information is determined pertaining to lane geometry of a lane of a road along which the equipped vehicle is traveling. Information is provided pertaining to at least one of (i) acceleration of the equipped vehicle, (ii) braking of the equipped vehicle and (iii) steering of the equipped vehicle. Information is provided identifying a driver operating the equipped vehicle. Responsive to identification of the driver operating the equipped vehicle, the equipped vehicle is controlled in accordance with a personalized parameter set for the identified driver and in accordance with data processing by the data processor.

Claims

1. A method for controlling a vehicle, said method comprising:

providing a plurality of sensors at an equipped vehicle, the plurality of sensors sensing exterior of the equipped vehicle;

wherein the plurality of sensors comprises an image sensor;

capturing, via the plurality of sensors, data;

providing a data processor at the equipped vehicle for processing data captured by the plurality of sensors;

determining, via processing by the data processor of data captured by at least some of the plurality of sensors, information pertaining to distance to other vehicles present exterior the equipped vehicle;

determining, via processing by the data processor of data captured by at least some of the plurality of sensors, information pertaining to lane geometry of a lane of a road along which the equipped vehicle is traveling;

providing to the data processor information pertaining to at least one of (i) acceleration of the equipped vehicle, (ii) braking of the equipped vehicle and (iii) steering of the equipped vehicle;

providing to the data processor information identifying a driver operating the equipped vehicle;

responsive to identification of the driver operating the equipped vehicle, controlling the equipped vehicle in accordance with a personalized parameter set for the identified driver and in accordance with data processing by the data processor; and

wherein the provided personalized parameter set comprises at least one parameter selected from the group consisting of (i) how rapidly a vehicle being driven by the identified driver accelerates if a preceding vehicle changes lane and is no longer in the lane along which the vehicle being driven by the identified driver is traveling, (ii) how aggressively a vehicle being driven by the identified driver decelerates after a cut-in by another vehicle into the lane in which the vehicle being driven by the identified driver is traveling, and (iii) how the speed of a vehicle being driven by the identified driver is adjusted responsive to a radius of curvature of an upcoming road curve ahead of the vehicle being driven by the identified driver.

2. The method of claim 1, wherein controlling the equipped vehicle in accordance with the personalized parameter set and in accordance with data processing by the data processor comprises controlling the equipped vehicle responsive to (i) determined information pertaining to distance to other vehicles, (ii) determined information pertaining to lane geometry, and (iii) provided information pertaining to acceleration, braking and steering of the equipped vehicle.

3. The method of claim 1, comprising creating the personalized parameter set for the identified driver by learning, while the identified driver is manually driving a vehicle on a road, at least one parameter indicative of the identified driver'"'"'s preference for operation of or use of at least one accessory or system of the vehicle.

4. The method of claim 3, comprising learning, while the identified driver is manually driving the vehicle on the road, the at least one parameter responsive at least in part to at least one of (i) determined information pertaining to distance to other vehicles, (ii) determined information pertaining to lane geometry, and (iii) provided information pertaining to acceleration, braking and steering of the vehicle.

5. The method of claim 4, wherein the vehicle the driver is manually driving on the road during learning is the equipped vehicle.

6. The method of claim 1, comprising determining, via processing by the data processor of data captured by at least some of the plurality of sensors, information pertaining to an ambient light level at the equipped vehicle.

7. The method of claim 1, comprising determining, via processing by the data processor of data captured by at least some of the plurality of sensors, information pertaining to traffic signs present in the field of sensing of the plurality of sensors.

8. The method of claim 1, comprising determining, via processing by the data processor of data captured by at least some of the plurality of sensors, information pertaining to a road surface characteristic of the road along which the equipped vehicle is traveling.

9. The method of claim 1, wherein the data processor comprises an image processor, and wherein determining information pertaining to lane geometry comprises determining, via processing by the image processor of image data captured by the image sensor, information pertaining to lane geometry of the lane of the road along which the equipped vehicle is traveling.

10. The method of claim 1, wherein determining information pertaining to lane geometry comprises determining, via processing by the data processor of data captured by at least some of the plurality of sensors, information pertaining to a width of the lane of the road along which the equipped vehicle is traveling.

11. The method of claim 1, wherein determining information pertaining to lane geometry comprises determining, via processing by the data processor of data captured by at least some of the plurality of sensors, information pertaining to road curvature ahead of the equipped vehicle.

12. The method of claim 11, wherein the data processor comprises an image processor, and wherein information pertaining to road curvature ahead of the equipped vehicle is established, at least in part, by processing by the image processor of image data captured by the image sensor of the plurality of sensors, and wherein the image sensor comprises a forward viewing image sensor viewing forward of the equipped vehicle, and wherein the forward viewing image sensor is disposed at a windshield of the equipped vehicle and views through the windshield and forwardly in the direction of forward travel of the equipped vehicle.

13. The method of claim 1, comprising processing data received at the data processor to create a personalized parameter set for a particular identified driver based on how the identified driver operates the equipped vehicle during various driving conditions.

14. The method of claim 1, wherein controlling the equipped vehicle in accordance with the personalized parameter set and in accordance with data processing by the data processor comprises controlling the equipped vehicle in a semi-autonomous mode.

15. The method of claim 1, wherein controlling the equipped vehicle in accordance with the personalized parameter set and in accordance with data processing by the data processor comprises controlling the equipped vehicle in an autonomous mode.

16. The method of claim 1, wherein controlling the equipped vehicle in accordance with the personalized parameter set and in accordance with data processing by the data processor comprises controlling the equipped vehicle while an adaptive cruise control system of the equipped vehicle is activated.

17. The method of claim 16, wherein the data processor comprises an image processor, and wherein distance of the equipped vehicle behind a leading vehicle ahead of the equipped vehicle is established, at least in part, by processing by the image processor of image data captured by the image sensor of the plurality of sensors, and wherein the image sensor comprises a forward viewing image sensor viewing forward of the equipped vehicle, and wherein the forward viewing image sensor is disposed at a windshield of the equipped vehicle and views through the windshield and forwardly in the direction of forward travel of the equipped vehicle.

18. The method of claim 17, wherein the personalized parameter set comprises a preferred target following distance for the adaptive cruise control system to use in establishing a distance of the equipped vehicle behind a leading vehicle ahead of the equipped vehicle.

19. The method of claim 18, comprising adjusting the preferred target following distance to maintain a safe following distance.

20. The method of claim 1, wherein the personalized parameter set comprises an acceleration preference of the identified driver and a deceleration preference of the identified driver.

21. The method of claim 1, wherein controlling the equipped vehicle in accordance with the personalized parameter set comprises at least one of (i) controlling a lane keep assist system of the equipped vehicle in accordance with the personalized parameter set, (ii) controlling a lane departure warning system of the equipped vehicle in accordance with the personalized parameter set and (iii) controlling a lane centering system of the equipped vehicle in accordance with the personalized parameter set.

22. The method of claim 21, comprising generating an alert or adjusting the steering of the equipped vehicle responsive to a threshold level movement of the equipped vehicle towards a lane marker or out of a lane in which the equipped vehicle is traveling.

23. The method of claim 1, wherein the personalized parameter set comprises a plurality of parameters, and wherein said method comprises selecting an appropriate one of the plurality of parameters responsive to a determined driving condition of the equipped vehicle.

24. The method of claim 23, wherein the determined driving condition comprises a determined one of a daytime driving condition and a nighttime driving condition.

25. The method of claim 24, wherein the determined driving condition comprises a determined one of a dry driving condition, a rain driving condition and a snow driving condition.

26. The method of claim 1, wherein the personalized parameter set comprises parameters for different driving conditions, and wherein the different driving conditions at least comprise different road conditions of a road travelled along by a vehicle driven by the identified driver.

27. The method of claim 1, wherein the image sensor comprises a forward viewing image sensor viewing forward of the equipped vehicle.

28. The method of claim 27, wherein the forward viewing image sensor is disposed at a windshield of the equipped vehicle and views through the windshield and forwardly in the direction of forward travel of the equipped vehicle.

29. The method of claim 1, wherein providing a plurality of sensors comprises providing a plurality of radar sensors at the equipped vehicle.

30. The method of claim 1, wherein providing a plurality of sensors comprises providing a plurality of image sensors at the equipped vehicle.

31. A method for controlling a vehicle, said method comprising:

providing a plurality of sensors at an equipped vehicle, the plurality of sensors sensing exterior of the equipped vehicle;

wherein the plurality of sensors comprises an image sensor and at least one sensor selected from the group consisting of a radar sensor and a lidar sensor;

capturing, via the plurality of sensors, data;

providing a data processor at the equipped vehicle for processing data captured by the plurality of sensors;

determining, via processing by the data processor of data captured by at least some of the plurality of sensors, information pertaining to distance to other vehicles present exterior the equipped vehicle;

determining, via processing by the data processor of data captured by at least the image sensor of the plurality of sensors, information pertaining to road curvature ahead of the equipped vehicle;

providing to the data processor information pertaining to at least one of (i) acceleration of the equipped vehicle, (ii) braking of the equipped vehicle and (iii) steering of the equipped vehicle;

providing to the data processor information identifying a driver operating the equipped vehicle;

responsive to identification of the driver operating the equipped vehicle, controlling the equipped vehicle in accordance with a personalized parameter set for the identified driver and in accordance with data processing by the data processor; and

wherein the provided personalized parameter set comprises at least one parameter selected from the group consisting of (i) how rapidly a vehicle being driven by the identified driver accelerates if a preceding vehicle changes lane and is no longer in the lane along which the vehicle being driven by the identified driver is traveling, (ii) how aggressively a vehicle being driven by the identified driver decelerates after a cut-in by another vehicle into the lane in which the vehicle being driven by the identified driver is traveling, and (iii) how the speed of a vehicle being driven by the identified driver is adjusted responsive to a radius of curvature of an upcoming road curve ahead of the vehicle being driven by the identified driver.

32. The method of claim 31, wherein controlling the equipped vehicle in accordance with the personalized parameter set and in accordance with data processing by the data processor comprises controlling the equipped vehicle responsive to (i) determined information pertaining to distance to other vehicles, (ii) determined information pertaining to lane width, (iii) determined information pertaining to road curvature and (iv) provided information pertaining to acceleration, braking and steering of the equipped vehicle.

33. The method of claim 31, comprising creating the personalized parameter set for the identified driver by learning, while the identified driver is manually driving a vehicle on a road, at least one parameter indicative of the identified driver'"'"'s preference for operation of or use of at least one accessory or system of the vehicle.

34. The method of claim 33, comprising learning, while the identified driver is manually driving the vehicle on the road, the at least one parameter responsive at least in part to at least one of (i) determined information pertaining to distance to other vehicles, (ii) determined information pertaining to lane geometry, and (iii) provided information pertaining to acceleration, braking and steering of the vehicle.

35. The method of claim 34, wherein the vehicle the driver is manually driving on the road during learning is the equipped vehicle.

36. The method of claim 31, wherein the data processor comprises an image processor, and wherein distance of the equipped vehicle behind a leading vehicle ahead of the equipped vehicle is established, at least in part, by processing by the image processor of image data captured by the image sensor of the plurality of sensors, and wherein the image sensor comprises a forward viewing image sensor viewing forward of the equipped vehicle, and wherein the forward viewing image sensor is disposed at a windshield of the equipped vehicle and views through the windshield and forwardly in the direction of forward travel of the equipped vehicle.

37. The method of claim 31, comprising determining, via processing by the data processor of data captured by at least some of the plurality of sensors, information pertaining to an ambient light level at the equipped vehicle.

38. The method of claim 31, comprising determining, via processing by the data processor of data captured by at least some of the plurality of sensors, information pertaining to traffic signs present in the field of sensing of the plurality of sensors.

39. The method of claim 31, comprising determining, via processing by the data processor of data captured by at least some of the plurality of sensors, information pertaining to a road surface characteristic of the road along which the equipped vehicle is traveling.

40. The method of claim 31, comprising determining, via processing by the data processor of data captured by at least the image sensor of the plurality of sensors, information pertaining to distance to other vehicles present exterior the equipped vehicle.

41. The method of claim 31, comprising determining, via processing by the data processor of data captured by at least the image sensor of the plurality of sensors, information pertaining to a width of the lane of the road along which the equipped vehicle is traveling.

42. A method for controlling a vehicle, said method comprising:

providing a plurality of sensors at an equipped vehicle, the plurality of sensors sensing exterior of the equipped vehicle;

wherein the plurality of sensors comprises an image sensor;

capturing, via the plurality of sensors, data;

providing a data processor at the equipped vehicle for processing data captured by the plurality of sensors;

determining, via processing by the data processor of data captured by at least some of the plurality of sensors, information pertaining to distance to other vehicles present exterior the equipped vehicle;

determining, via processing by the data processor of data captured by at least the image sensor of the plurality of sensors, information pertaining to lane geometry of a lane of the road along which the equipped vehicle is traveling;

providing to the data processor information pertaining to at least one of (i) acceleration of the equipped vehicle, (ii) braking of the equipped vehicle and (iii) steering of the equipped vehicle;

providing to the data processor information identifying a driver operating the equipped vehicle;

responsive to identification of the driver operating the equipped vehicle, controlling the equipped vehicle in accordance with a personalized parameter set for the identified driver and in accordance with data processing by the data processor;

wherein the provided personalized parameter set comprises at least one parameter selected from the group consisting of (i) how rapidly a vehicle being driven by the identified driver accelerates if a preceding vehicle changes lane and is no longer in the lane along which the vehicle being driven by the identified driver is traveling, (ii) how aggressively a vehicle being driven by the identified driver decelerates after a cut-in by another vehicle into the lane in which the vehicle being driven by the identified driver is traveling, and (iii) how the speed of a vehicle being driven by the identified driver is adjusted responsive to a radius of curvature of an upcoming road curve ahead of the vehicle being driven by the identified driver;

wherein controlling the equipped vehicle in accordance with the personalized parameter set and in accordance with data processing by the data processor comprises controlling the equipped vehicle while an adaptive cruise control system of the equipped vehicle is activated; and

wherein the personalized parameter set comprises a preferred target following distance for the adaptive cruise control system to use in establishing a distance of the equipped vehicle behind a leading vehicle ahead of the equipped vehicle.

43. The method of claim 42, wherein controlling the equipped vehicle in accordance with the personalized parameter set and in accordance with data processing by the data processor comprises controlling the equipped vehicle responsive to (i) determined information pertaining to distance to other vehicles, (ii) determined information pertaining to lane geometry, and (iii) provided information pertaining to acceleration, braking and steering of the equipped vehicle.

44. The method of claim 42, comprising creating the personalized parameter set for the identified driver by learning, while the identified driver is manually driving a vehicle on a road, at least one parameter indicative of the identified driver'"'"'s preference for operation of or use of at least one accessory or system of the vehicle.

45. The method of claim 44, comprising learning, while the identified driver is manually driving the vehicle on the road, the at least one parameter responsive at least in part to at least one of (i) determined information pertaining to distance to other vehicles, (ii) determined information pertaining to lane geometry, and (iii) provided information pertaining to acceleration, braking and steering of the vehicle.

46. The method of claim 45, wherein the vehicle the driver is manually driving on the road during learning is the equipped vehicle.

47. The method of claim 42, wherein controlling the equipped vehicle in accordance with the personalized parameter set and in accordance with data processing by the data processor comprises controlling the equipped vehicle while an adaptive cruise control system of the equipped vehicle is activated.

48. The method of claim 47, wherein the personalized parameter set comprises a preferred target following distance for the adaptive cruise control system to use in establishing a distance of the equipped vehicle behind a leading vehicle ahead of the equipped vehicle.

49. The method of claim 48, comprising adjusting the preferred target following distance to maintain a safe following distance.

50. The method of claim 42, comprising generating an alert or adjusting the steering of the equipped vehicle responsive to a threshold level movement of the equipped vehicle towards a lane marker or out of a lane in which the equipped vehicle is traveling.

51. The method of claim 42, wherein providing a plurality of sensors comprises providing a plurality of radar sensors at the equipped vehicle.

52. The method of claim 42, wherein providing a plurality of sensors comprises providing a plurality of image sensors at the equipped vehicle.

53. The method of claim 42, wherein the personalized parameter set comprises an acceleration preference of the identified driver and a deceleration preference of the identified driver.

54. The method of claim 42, wherein controlling the equipped vehicle in accordance with the personalized parameter set comprises at least one of (i) controlling a lane keep assist system of the equipped vehicle in accordance with the personalized parameter set, (ii) controlling a lane departure warning system of the equipped vehicle in accordance with the personalized parameter set and (iii) controlling a lane centering system of the equipped vehicle in accordance with the personalized parameter set.

55. The method of claim 42, wherein the personalized parameter set comprises a preferred target following distance to maintain a predetermined safe following distance for a particular determined driving condition.

56. The method of claim 42, wherein the data processor comprises an image processor, and wherein distance of the equipped vehicle behind a leading vehicle ahead of the equipped vehicle is established, at least in part, by processing by the image processor of image data captured by the image sensor of the plurality of sensors, and wherein the image sensor comprises a forward viewing image sensor viewing forward of the equipped vehicle, and wherein the forward viewing image sensor is disposed at a windshield of the equipped vehicle and views through the windshield and forwardly in the direction of forward travel of the equipped vehicle.

57. The method of claim 56, wherein determining information pertaining to lane geometry comprises determining, via processing by the image processor of image data captured by the image sensor, information pertaining to lane geometry of the lane of the road along which the equipped vehicle is traveling.