AUTONOMOUS VEHICLE CONTROL TRANSITIONING

• US 20170247040A1
• Filed: 03/17/2016
• Published: 08/31/2017
• Est. Priority Date: 02/25/2016
• Status: Abandoned Application

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Miller, Kenneth James, Perkins, William Paul, Kelley, David B.
• Application Number:
  US15/073,093
• Publication Number:
  US 20170247040A1
• 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 2040/0818 Inactivity or incapacity of driver
• CPC Class Codes: B60W 2040/089 Driver voice
• CPC Class Codes: B60W 2050/0075 Automatic parameter input, automatic initialising or calibrating means
• 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 2540/21 Voice
• CPC Class Codes: B60W 2540/22 Psychological state; Stress level or workload
• CPC Class Codes: B60W 2540/223 Posture, e.g. hand, foot, or seat position, turned or inclined
• CPC Class Codes: B60W 2540/225 Direction of gaze
• CPC Class Codes: B60W 2540/229 Attention level, e.g. attentive to driving, reading or sleeping
• CPC Class Codes: B60W 2540/24 Drug level, e.g. alcohol
• CPC Class Codes: B60W 2540/26 Incapacity
• CPC Class Codes: B60W 2556/10 Historical data
• CPC Class Codes: B60W 30/182 Selecting between different operative modes, e.g. comfort and performance modes
• CPC Class Codes: B60W 60/0059 Estimation of the risk associated with autonomous or manual driving, e.g. situation too complex, sensor failure or driver incapacity
• CPC Class Codes: G05D 1/0061 for transition from automatic pilot to manual pilot and vice versa
• CPC Class Codes: G05D 1/0248 in combination with a laser lasers per se H01S

Abstract

Signals are received from a plurality of sources, representing operating characteristics of a vehicle and an environment surrounding the vehicle. A plurality of operational factors are developed based on the signals. The vehicle is controlled according to one of at least three levels of control, including an autonomous, a semi-autonomous, and a manual level of control, based on the operational factors.

Claims

1. A method, comprising:

receiving signals, from a plurality of sources, representing operating characteristics of a vehicle and an environment surrounding the vehicle;

developing a plurality of operational factors based on the signals; and

transitioning control of the vehicle between levels of autonomous control based at least in part on the operational factors.

2. The method of claim 1, wherein the levels of autonomous control include an autonomous, a semi-autonomous, and a manual level of control.

3. The method of claim 1, wherein the operational factors include at least two of a driver readiness factor, a driver alertness factor, an autonomous confidence factor, a driver action probability factor, and a peril factor.

4. The method of claim 1, wherein at least one of the operational factors is determined according to component values from each of a plurality of vehicle data sources.

5. The method of claim 4, wherein developing the operational factors includes weighting the component values.

6. The method of claim 1, wherein the autonomous control includes control of each of vehicle steering, braking, and propulsion by a vehicle computer, semi-autonomous control includes control of at least one of vehicle steering, braking, and propulsion by the vehicle computer, and manual control includes control of none of vehicle steering, braking, and propulsion by the vehicle computer.

7. The method of claim 1, further comprising changing from a first one of the levels of autonomous control to a second one of the levels of autonomous control when at least one of the operational factors exceeds a threshold.

8. The method of claim 1, further comprising actuating at least one of vehicle steering, braking, and propulsion after determining the level of control.

9. The method of claim 1, wherein the operational factors are based in part on historical data.

10. The method of claim 1, wherein at least one of the signals includes data concerning a vehicle occupant.

11. An autonomous vehicle, comprising:

a plurality of sensors and receivers arranged to receive signals, from a plurality of sources, representing operating characteristics of the vehicle and an environment surrounding the vehicle;

a plurality of vehicle control subsystems; and

at least one computing device programmed to develop a plurality of operational factors based on the signals and to transition control of the plurality of subsystems between levels of autonomy based at least in part on the operational factors.

12. The vehicle of claim 11, wherein the levels of autonomous control include an autonomous, a semi-autonomous, and a manual level of control.

13. The vehicle of claim 11, wherein the operational factors include at least two of a driver readiness factor, a driver alertness factor, an autonomous confidence factor, a driver action probability factor, and a peril factor.

14. The vehicle of claim 11, wherein at least one of the operational factors is determined according to component values from each of a plurality of vehicle data sources.

15. The vehicle of claim 11, wherein the autonomous control includes control of each of vehicle steering, braking, and propulsion by a vehicle computer, semi-autonomous control includes control of at least one of vehicle steering, braking, and propulsion by the vehicle computing device, and manual control includes control of none of vehicle steering, braking, and propulsion by the vehicle computing device.

16. The vehicle of claim 11, wherein the controller is programmed to change from a first one of the levels of autonomous control to a second one of the levels of autonomous control when at least one of the operational factors exceeds a threshold.

17. The vehicle of claim 11, wherein the controller is programmed to actuate at least one of vehicle steering, braking, and propulsion after determining the level of control.

18. The vehicle of claim 11, wherein at least one of the signals includes data concerning a vehicle occupant.

19. A method, comprising:

collecting, in a vehicle computer, data concerning a vehicle occupant and data concerning vehicle operations, the data representing operating characteristics of the vehicle and an environment surrounding the vehicle;

developing at least two values for respective vehicle operating factors based at least in part on the data, at least one of the values relating to a state of the vehicle occupant; and

selecting one of at least three levels of control, including an autonomous, a semi-autonomous, and a manual level of control, based on the operational factors.

20. The method of claim 19, wherein the autonomous control includes control of each of vehicle steering, braking, and propulsion by a vehicle computer, semi-autonomous control includes control of at least one of vehicle steering, braking, and propulsion by the vehicle computing device, and manual control includes control of none of vehicle steering, braking, and propulsion by the vehicle computing device.