Method for determining passable area in planning a path of autonomous driving vehicles

Patent metadata

Field	Value
Publication number	US-11442450-B2
Application number	US-201916711118-A
Country	US
Kind code	B2
Filing date	Dec 11, 2019
Priority date	Dec 11, 2019
Publication date	Sep 13, 2022
Grant date	Sep 13, 2022

Abstract

According to one embodiment, in response to determining that an obstacle blocks at least a portion of a current lane in which an ADV is driving, an obstacle boundary of the obstacle is determined based on the size and shape of the obstacle. A lane configuration is determined based on map data of a map corresponding to a road associated with the lanes. A passing lane boundary that can be utilized by the ADV is determined based on the lane configuration of the road and the obstacle boundary of the obstacle. A passable area is calculated within the passing lane boundary based on a size of the ADV. The passable area is utilized by the ADV to pass the obstacle without collision. Thereafter, a trajectory is planned within the passable area boundary to control the ADV to pass the obstacle.

First claim

What is claimed is:

1. A computer-implemented method of operating an autonomous driving vehicle (ADV), the computer-implemented method comprising:
in response to determining that an obstacle is blocking at least a portion of a current lane in which an ADV is driving, determining an obstacle boundary of the obstacle;
determining a lane configuration of a road within which the current lane is located based on map data of a map corresponding to the road, wherein the lane configuration comprises a number of lanes within the road and a lane type of each of the number of lanes;
determining a passing lane boundary of a passing lane that can be utilized by the ADV based on the lane configuration of the road and the obstacle boundary of the obstacle;
calculating a passable area boundary within the passing lane boundary based on a size of the ADV, wherein the passable area boundary is utilized by the ADV to pass the obstacle without collision; and
planning a trajectory within the passable area boundary to control the ADV to pass the obstacle.

2. The computer-implemented method of claim 1 , further comprising:
determining whether the obstacle is a static obstacle; and
in response to determining that the obstacle is a static obstacle, determining the obstacle boundary based on a size and a shape of the obstacle.

3. The computer-implemented method of claim 1 , further comprising:
determining whether the obstacle is a dynamic obstacle;
in response to determining that the obstacle is a dynamic obstacle, predicting a moving trajectory of the obstacle; and
determining the obstacle boundary based on the moving trajectory of the obstacle.

4. The computer-implemented method of claim 1 , wherein determining the passing lane boundary comprises adjusting a current lane boundary of the current lane by subtracting at least a portion of the obstacle boundary that is within the current lane boundary.

5. The computer-implemented method of claim 4 , wherein determining the passable area boundary within the passing lane boundary comprises reducing a passing lane width of the passing lane based on a vehicle width of the ADV.

6. The computer-implemented method of claim 5 , wherein the passing lane width is reduced by a half of the vehicle width of the ADV.

7. The computer-implemented method of claim 5 , wherein determining the lane boundary that can be utilized by the ADV comprises:
determining whether the lane type of the current lane allows the ADV to enter an adjacent lane in order to pass the obstacle based on a set of traffic rules; and
expanding the passing lane boundary from the current lane boundary of the current lane to the adjacent lane, in response to determining that the adjacent lane can be utilized by the ADV.

8. The computer-implemented method of claim 7 , wherein determining the lane type of the current lane comprises whether a lane line of the current lane includes a dash line, wherein the ADV is allowed to enter the adjacent lane if the lane line includes a dash line.

9. The computer-implemented method of claim 1 , further comprising:
determining a lane curve of the passing lane; and
adjusting the passing lane boundary based on the lane curve of the passing lane and a-a vehicle boundary of the ADV, such that the vehicle boundary of the ADV does not reach a road curb of the road when the ADV drives through the lane curve of the passing lane.

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:
in response to determining that an obstacle is blocking at least a portion of a current lane in which an ADV is driving, determining an obstacle boundary of the obstacle;
determining a lane configuration of a road within which the current lane is located based on map data of a map corresponding to the road, wherein the lane configuration comprises a number of lanes within the road and a lane type of each of the number of lanes;
determining a passing lane boundary of a passing lane that can be utilized by the ADV based on the lane configuration of the road and the obstacle boundary of the obstacle;
calculating a passable area boundary within the passing lane boundary based on a size of the ADV, wherein the passable area boundary is utilized by the ADV to pass the obstacle without collision; and
planning a trajectory within the passable area boundary to control the ADV to pass the obstacle.

11. The non-transitory machine-readable medium of claim 10 , wherein the operations further comprise:
determining whether the obstacle is a static obstacle; and
in response to determining that the obstacle is a static obstacle, determining the obstacle boundary based on a size and a shape of the obstacle.

12. The non-transitory machine-readable medium of claim 10 , wherein the operations further comprise:
determining whether the obstacle is a dynamic obstacle;
in response to determining that the obstacle is a dynamic obstacle, predicting a moving trajectory of the obstacle; and
determining the obstacle boundary based on the moving trajectory of the obstacle.

13. The non-transitory machine-readable medium of claim 10 , wherein determining the passing lane boundary comprises adjusting a current lane boundary of the current lane by subtracting at least a portion of the obstacle boundary that is within the current lane boundary.

14. The non-transitory machine-readable medium of claim 13 , wherein determining the passable area boundary within the passing lane comprises reducing a passing lane width of the passing lane based on a vehicle width of the ADV.

15. The non-transitory machine-readable medium of claim 14 , wherein the passing lane width is reduced by a half of the vehicle width of the ADV.

16. The non-transitory machine-readable medium of claim 14 , wherein determining the lane boundary that can be utilized by the ADV comprises:
determining whether the lane type of the current lane allows the ADV to enter an adjacent lane in order to pass the obstacle based on a set of traffic rules; and
expanding the passing lane boundary from the current lane boundary of the current lane to the adjacent lane, in response to determining that the adjacent lane can be utilized by the ADV.

17. The non-transitory machine-readable medium of claim 16 , wherein determining the lane type of the current lane comprises whether a lane line of the current lane includes a dash line, wherein the ADV is allowed to enter the adjacent lane if the lane line includes a dash line.

18. A data processing system, comprising:
a processor; and
a memory coupled to the processor to store instructions, which when executed by the processor, cause the processor to perform operations, the operations including:
in response to determining that an obstacle is blocking at least a portion of a current lane in which an autonomous driving vehicle (ADV) is driving, determining an obstacle boundary of the obstacle,
determining a lane configuration of a road within which the current lane is located based on map data of a map corresponding to the road, wherein the lane configuration comprises a number of lanes within the road and a lane type of each of the number of lanes,
determining a passing lane boundary of a passing lane that can be utilized by the ADV based on the lane configuration of the road and the obstacle boundary of the obstacle,
calculating a passable area boundary within the passing lane boundary based on a size of t

Assignees

• Baidu Usa Llc
• Baidu Com Times Tech Beijing Co Ltd

Inventors

• Yao Dongchun
• Zhu Fan
• Lv Leibing
• Xu Xin
• Yu Ning

Classifications

• G06V20/58

  Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads · CPC title

• B60W30/12

  Lane keeping · CPC title

• G06V20/588

  Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road · CPC title

• B60W30/09

  Taking automatic action to avoid collision, e.g. braking and steering · CPC title

• G01C21/3492

  employing speed data or traffic data, e.g. real-time or historical (traffic control systems for road vehicles involving transmission of navigation instructions to the vehicle G08G1/0968) · CPC title