Adaptive cruise control system

• US 10,239,526 B2
• Filed: 03/30/2015
• Issued: 03/26/2019
• Est. Priority Date: 03/30/2015
• Status: Active Grant

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations LLC (General Motors Company)
• Inventors: Durgin, William F., Berman, Cody D., Francisco, Justin K., Moretti, Brunno L.
• Primary Examiner(s): Black, Thomas G
• Assistant Examiner(s): Smith-Stewart, Demetra R
• Application Number:
  US14/672,624
• Publication Number:
  US 20160288789A1
• Time in Patent Office: 1,457 Days
• Field of Search: None
• CPC Class Codes: B60W 20/00 Control systems specially adapted for hybrid vehicles hybrid vehicle design, B60K6/00; electric vehicles B60L
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2554/801 Lateral distance
• CPC Class Codes: B60W 2555/60 Traffic rules, e.g. speed limits or right of way
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 30/143 Speed control B60W30/16 takes precedence
• CPC Class Codes: B60W 30/16 Control of distance between vehicles, e.g. keeping a distance to preceding vehicle
• CPC Class Codes: B60W 30/18154 Approaching an intersection
• CPC Class Codes: G01S 19/14 specially adapted for specific applications
• CPC Class Codes: G01S 2013/9321 Velocity regulation, e.g. cruise control

Abstract

Systems and processes are provided for adaptive cruise control. The process includes receiving information about a distance between vehicle and a traffic signal, receiving information about a state of the traffic signal, and determining whether to adjust the speed of the vehicle based upon the distance between the vehicle and the traffic signal and the state of the traffic signal.

Claims

1. An adaptive cruise control system for a vehicle, the system comprising:

an external object calculation module (EOCM), the EOCM comprising a processor coupled to a memory and an interface, the memory including instructions for improving a fuel efficiency of the vehicle;

a plurality of object detection sensors; and

a communication module having a vehicle to vehicle portion (V2V) configured to sense information from at least one other vehicle in a traffic queue and a vehicle to infrastructure portion (V2I) configured to sense information from an infrastructure element, wherein the EOCM receives data indicating at least one of a state of a traffic signal, and a duration of time that a traffic signal has been in a particular state from the V2I portion and receives data indicating a number of other vehicles in the traffic queue in front of the vehicle from the V2V portion, and is configured to automatically and adaptively adjust the speed of the vehicle by selecting an acceleration or deceleration method from a plurality of methods based on an analysis of the received data to improve the fuel efficiency of the vehicle, wherein the plurality of methods includes a method that changes an operating mode of a hybrid system, a method that shuts down an engine of the vehicle, a method that uses regenerative braking, and a method that uses friction brakes.

2. The adaptive cruise control system of claim 1, the V2I further configured to determine the state of a traffic signal.

3. The adaptive cruise control system of claim 1, the V2I further configured to determine the duration of time that a traffic signal has been in a particular state.

4. The adaptive cruise control system of claim 1, the V2V portion comprising at least one of a radar, a camera, a GPS, or a sonar.

5. The adaptive cruise control system of claim 1, the EOCM further configured to communicate with at least one of a body control module, an engine control module, and a transmission control module to improve the fuel efficiency of the vehicle.

6. The adaptive cruise control system of claim 1, the EOCM further configured to communicate with at least one of a traction power inverter module and a battery state manager to improve the fuel efficiency of the vehicle.

7. An external object calculation module (EOCM) for improving the fuel efficiency of a vehicle, the EOCM comprising:

a computer processor;

a memory, the memory coupled to the computer processor, the memory including instructions for improving the fuel efficiency of the vehicle; and

an interface coupled to the computer processor, wherein the computer processor is configured to receive, via the interface, information about a total number of other vehicles in a traffic queue in front of the vehicle (V2V data) and information about the state of a traffic signal (V2I data), wherein the processor is configured to process the instructions stored in the memory based upon an analysis of the V2V data and the V2I data to select an acceleration or deceleration method from a plurality of methods to improve the fuel efficiency of a vehicle within which the EOCM is situated, wherein the plurality of methods includes a method that changes an operating mode of a hybrid system, a method that shuts down an engine of the vehicle, a method that uses regenerative braking, and a method that uses friction brakes.

8. The EOCM of claim 7, the V2I data further comprising information about the distance between the vehicle to an infrastructure object.

9. The EOCM of claim 8, wherein the state of the traffic signal is one of green, yellow, or red.

10. The EOCM of claim 7, wherein the processor is configured to process the instructions based upon a duration of the state of the traffic signal to determine whether to accelerate or decelerate the speed of a vehicle to which the EOCM is coupled.

11. The EOCM of claim 7, wherein the processor is configured to process the instructions based upon a duration of the state of the traffic signal to determine whether to adjust the speed of a vehicle to which the EOCM is coupled, the state of the traffic signal being at least one of green, yellow, or red.

12. The EOCM of claim 7, the V2V data further comprising a distance between a vehicle to which the EOCM is coupled and the traffic signal.

13. The EOCM of claim 12, the distance based upon a traffic queue.

14. A process for adaptively adjusting a speed of a vehicle, the process comprising:

receiving, by a computer processor, information about a total number of other vehicles in a traffic queue in front of the vehicle;

receiving, by the computer processor, information about a state of the traffic signal;

selecting, by the processor, an acceleration or deceleration method from a plurality of methods based on the total number of other vehicles in the traffic queue, wherein the plurality of methods includes a method that changes an operating mode of a hybrid system, a method that shuts down an engine of the vehicle, a method that uses regenerative braking, and a method that uses friction brakes; and

determining, by the computer processor, whether to accelerate or decelerate the speed of the vehicle based upon the state of the traffic signal and the selected acceleration or deceleration method.

15. The process of claim 14, wherein the state of the traffic signal is one of green, yellow, or red.

16. The process of claim 14, further comprising determining, by the computer processor, whether to accelerate or decelerate the speed of the vehicle based upon a duration of time that the traffic signal has been in the state.