ADAPTIVE CRUISE CONTROL SYSTEM AND METHOD

• US 20150203108A1
• Filed: 01/17/2014
• Published: 07/23/2015
• Est. Priority Date: 01/17/2014
• Status: Active Grant

• Current Assignee: FCA US LLC (Stellantis NV)
• Original Assignee: FCA US LLC (Stellantis NV)
• Inventors: Buckley, Stephen J., Loria, Nathan, Bliss, Michael J., Wellman, Douglas D., Chiapetta, Adam C.
• Granted Patent: US 9,266,536 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B60W 2050/0075 Automatic parameter input, automatic initialising or calibrating means
• CPC Class Codes: B60W 2540/043 Identity of occupants
• CPC Class Codes: B60W 2540/229 Attention level, e.g. attentive to driving, reading or sleeping
• CPC Class Codes: B60W 2556/10 Historical data
• CPC Class Codes: B60W 30/16 Control of distance between vehicles, e.g. keeping a distance to preceding vehicle
• CPC Class Codes: B60W 30/17 with provision for special action when the preceding vehicle comes to a halt, e.g. stop and go
• CPC Class Codes: B60W 50/0098 Details of control systems ensuring comfort, safety or stability not otherwise provided for

Abstract

Methods and systems for implementing personalized driver assistance features such as adaptive cruise control, adaptive cruise control with stop and go, and forward collision warning. The methods and systems collect specific vehicle data and then calculate values that populate a histogram representing driver habits and tendencies regarding following and stopping distances in relation to objects ahead of the vehicle. The methods and systems utilize the histogram data to provide the driver with a personalized driver assistance features.

Claims

1. A method of controlling at least one driver assistance feature of a vehicle, said method comprising:

determining, by a processor, if the at least one driver assistance feature is associated with stored learned driver specific data;

performing the at least one driver assistance feature based on the learned driver specific data if it is determined that the at least one driver assistance feature is associated with stored learned driver specific data; and

performing the at least one driver assistance feature based on vehicle specific data if it is determined that the at least one driver assistance feature is not associated with stored learned driver specific data.

2. The method of claim 1, wherein the at least one driver assistance feature comprises at least one of an adaptive cruise control feature, an adaptive cruise control with stop and go feature or a forward collision warning feature.

3. The method of claim 1, wherein performing the at least one driver assistance feature based on the learned driver specific data comprises at least one of implementing a driver learned stopping distance when stopping the vehicle, implementing a driver learned following distance when the vehicle is moving or implementing a driver learned forward collision warning when the vehicle is approaching an object in the vehicle'"'"'s path.

4. The method of claim 3, wherein performing the at least one driver assistance feature based on the learned driver specific data further comprises loading the learned driver specific data based on detecting a type of key fob used with the vehicle.

5. The method of claim 3, wherein performing the at least one driver assistance feature based on the learned driver specific data further comprises loading the learned driver specific data based on detecting that a predetermined button was pressed within the vehicle.

6. The method of claim 3, wherein performing the at least one driver assistance feature based on the learned driver specific data further comprises using a driver learned acceleration profile to accelerate the vehicle from a stopped position.

7. The method of claim 3, wherein performing the at least one driver assistance feature based on the learned driver specific data further comprises using a driver learned deceleration profile to decelerate the vehicle when the vehicle is moving and approaching an object.

8. The method of claim 1, further comprising:

determining, by the processor, if a cellular phone call is in progress or if at least one in-vehicle button or switch has been activated; and

modifying the performing steps by using adjusted learned driver specific data or vehicle specific data if it is determined that a cellular phone call is in progress or if at least one in-vehicle button or switch has been activated.

9. The method of claim 1, wherein the vehicle specific data is modified based on data gathered from other vehicles.

10. The method of claim 1, wherein the learned driver specific data is obtained during use of the vehicle when no driver assistance feature is enabled and an object has been detected in the vehicle'"'"'s path.

11. The method of claim 10, wherein the learned driver specific data comprises a plurality of average following distances and a plurality of average time gaps, each average following distance and average time gap being associated with a respective vehicle speed.

12. An engine system of a vehicle, said system comprising:

an engine having a control signal input for receiving control signals from a control module;

at least one sensing system; and

a controller connected to the at least one sensing system and the control module, said controller adapted to;

determine if the at least one driver assistance feature is associated with stored learned driver specific data,

perform the at least one driver assistance feature based on the learned driver specific data if it is determined that the at least one driver assistance feature is associated with stored learned driver specific data, and

perform the at least one driver assistance feature based on vehicle specific data if it is determined that the at least one driver assistance feature is not associated with stored learned driver specific data.

13. The system of claim 12, wherein the at least one driver assistance feature comprises at least one of an adaptive cruise control feature, an adaptive cruise control with stop and go feature or a forward collision warning feature.

14. The system of claim 12, wherein the controller performs the at least one driver assistance feature based on the learned driver specific data comprises at least one of implementing a driver learned stopping distance when stopping the vehicle, implementing a driver learned following distance when the vehicle is moving or implementing a driver learned forward collision warning when the vehicle is approaching an object in the vehicle'"'"'s path.

15. The system of claim 14, wherein the controller loads the learned driver specific data based on detecting a type of key fob used with the vehicle or that a predetermined button was pressed within the vehicle.

16. The system of claim 14, wherein the controller uses a driver learned acceleration profile to accelerate the vehicle from a stopped position.

17. The system of claim 14, wherein the controller uses a driver learned deceleration profile to decelerate the vehicle when the vehicle is moving and approaching an object.

18. The system of claim 12, wherein the controller is further adapted to:

determine if a cellular phone call is in progress or if at least one in-vehicle button or switch has been activated; and

modify the performance of the at least one driver assistance feature by using adjusted learned driver specific data or vehicle specific data if it is determined that a cellular phone call is in progress or if at least one in-vehicle button or switch has been activated.

19. The system of claim 12, wherein the learned driver specific data is obtained during use of the vehicle when no driver assistance feature is enabled and an object has been detected in the vehicle'"'"'s path.

20. The system of claim 12, wherein the learned driver specific data comprises a plurality of average following distances and a plurality of average time gaps, each average following distance and average time gap being associated with a respective vehicle speed.