Autonomous vehicle park-and-go scenario design

Patent metadata

Field	Value
Publication number	US-11577758-B2
Application number	US-202016734146-A
Country	US
Kind code	B2
Filing date	Jan 3, 2020
Priority date	Jan 3, 2020
Publication date	Feb 14, 2023
Grant date	Feb 14, 2023

Abstract

In one embodiment, when an autonomous driving vehicle (ADV) is parked, the ADV can determine, based on criteria, whether to operate in an open-space mode or an on-lane mode. The criteria can include whether the ADV is within a threshold distance and threshold heading relative to a vehicle lane. If the criteria are not satisfied, then the ADV can enter the open-space mode. While in the open-space mode, the ADV can maneuver it is within the threshold distance and the threshold heading relative to the vehicle lane. In response to the criteria being satisfied, the ADV can enter and operate in the on-lane mode for the ADV to resume along the vehicle lane.

First claim

What is claimed is:

1. A computer-implement method performed by an autonomous driving vehicle (ADV), the method comprising:
determining whether a set of criteria are satisfied based on sensor data obtained from a plurality of sensors, the set of criteria including whether the ADV is within a threshold distance and threshold heading relative to a vehicle lane;
in response to the set of criteria not being satisfied, beginning an operation in an open-space mode, including adjusting a position of the ADV via one or more forward and backward movements, and continuing to operate in the open-space mode until the ADV is positioned within the threshold distance and the threshold heading relative to the vehicle lane;
in response to determining that the set of criteria has been satisfied, operating in an on-lane mode, wherein during the open-space mode, an optimization algorithm is applied to maximize a distance between the ADV and one or more obstacles wherein the optimization algorithm includes a cost function that maximizes the distance between the ADV and the one or more obstacles while penalizing a deviation of the ADV from a final location and a final header that satisfies the set of criteria; and
in the on-lane mode, resuming autonomous driving along the vehicle lane.

2. The method of claim 1 , wherein during the open-space mode, the ADV predicts a future location of the one or more obstacles.

3. The method of claim 1 , wherein the on-lane mode and open-space mode are exclusive to each other, and during the on-lane mode, ADV controls limit the ADV to traveling along a trajectory over the vehicle lane and during the open-space mode, the ADV controls are removed allowing the ADV to travel freely off the vehicle lane.

4. The method of claim 1 , wherein the set of criteria further includes whether an obstacle impedes a path of the ADV in reaching the vehicle lane.

5. The method of claim 1 , wherein if all the criteria are satisfied when the ADV is stationary at a current location off the vehicle lane, the ADV enters the on-lane mode without entering the open-space mode.

6. The method of claim 1 , wherein the vehicle lane is a lane in a parking lot, or a traffic lane.

7. The method of claim 1 , wherein a current position of the ADV is parallel, perpendicular, or oblique with respect to the vehicle lane.

8. The method of claim 1 , wherein the distance threshold is approximately 5 meters.

9. The method of claim 1 , wherein the heading threshold is approximately 20 degrees.

10. A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor, cause the processor to perform operations of operating an autonomous driving vehicle (ADV), the operations comprising:
determining whether a set of criteria are satisfied based on sensor data obtained from a plurality of sensors, the set of criteria including whether the ADV is within a threshold distance and threshold heading relative to a vehicle lane;
in response to the set of criteria not being satisfied, beginning an operation in an open-space mode, including adjusting a position of the ADV via one or more forward and backward movements, and continuing to operate in the open-space mode until the ADV is positioned within the threshold distance and the threshold heading relative to the vehicle lane;
in response to determining that the set of criteria has been satisfied, operating in an on-lane mode, wherein during the open-space mode, an optimization algorithm is applied to maximize a distance between the ADV and one or more obstacles wherein the optimization algorithm includes a cost function that maximizes the distance between the ADV and the one or more obstacles while penalizing a deviation of the ADV from a final location and a final header that satisfies the set of criteria; and
in the on-lane mode, resuming autonomous driving along the vehicle lane.

11. The machine-readable medium of claim 10 , wherein during the open-space mode, the ADV predicts a future location of the one or more obstacles.

12. The machine-readable medium of claim 10 , wherein the on-lane mode and open-space mode are exclusive to each other, and during the on-lane mode, ADV controls limit the ADV to traveling along a trajectory over the vehicle lane and during the open-space mode, the ADV controls are removed allowing the ADV to travel freely off the vehicle lane.

13. The machine-readable medium of claim 10 , wherein the set of criteria further include whether an obstacle impedes a path of the ADV in reaching the vehicle lane.

14. The machine-readable medium of claim 10 , wherein if all the criteria are satisfied when the ADV is stationary at the current location off the vehicle lane, the ADV enters the on-lane mode without entering the open-space mode.

15. The machine-readable medium of claim 10 , wherein the vehicle lane is a lane in a parking lot, or a traffic lane.

16. The machine-readable medium of claim 10 , wherein a current position of the ADV is parallel, perpendicular, or oblique with respect to the vehicle lane.

17. The machine-readable medium of claim 10 , wherein the distance threshold is approximately 5 meters.

18. The machine-readable medium of claim 10 , wherein the heading threshold is approximately 20 degrees.

19. A data processing system, comprising:
a processor; and
a memory coupled to the processor storing instructions, which when executed by the processor, cause the processor to perform operations of operating an autonomous driving vehicle (ADV), the operations including
determining whether a set of criteria are satisfied based on sensor data obtained from a plurality of sensors, the set of criteria including whether the ADV is within a threshold distance and threshold heading relative to a vehicle lane;
in response to the set of criteria not being satisfied, beginning an operation in an open-space mode, including adjusting a position of the ADV via one or more forward and backward movements, and continuing to operate in the open-space mode until the ADV is positioned within the threshold distance and the threshold heading relative to the vehicle lane;
in response to determining that the set of criteria has been satisfied, operating in an on-lane mode, wherein during the open-space mode, an optimization algorithm is applied to maximize a distance between the ADV and one or more obstacles wherein the optimization algorithm includes a cost function that maximizes the distance between the ADV and the one or more obstacles while penalizing a deviation of the ADV from a final location and a final header that satisfies the set of criteria; and
in the on-lane mode, resuming autonomous driving along the vehicle lane.

20. The system of claim 19 , wherein during the open-space mode, the ADV predicts a future location of the one or more obstacles.

21. The system of claim 19 , wherein wherein the on-lane mode and open-space mode are exclusive to each other, and during the on-lane mode, ADV controls limit the ADV to traveling along a trajectory over the vehicle lane and during the open-space mode, the ADV controls are removed allowing the ADV to travel freely off the vehicle lane.

Assignees

• Baidu Usa Llc

Inventors

• Jiang Shu
• Tao Jiaming
• Zhou Jinyun
• Luo Qi
• Miao Jinghao
• Hu Jiangtao
• Xu Jiaxuan
• Wang Yu

Classifications

• B60W2554/80

  Spatial relation or speed relative to objects · CPC title

• B60W30/18163

  Lane change; Overtaking manoeuvres · CPC title

• B60W2552/53

  Road markings, e.g. lane marker or crosswalk · CPC title

• B60W50/08

  Interaction between the driver and the control system · CPC title

• B60W30/06

  Automatic manoeuvring for parking · CPC title