IP Library › Granted Patent US 11,054,829
Granted Patent B2
US 11,054,829 · App. 16/037,908 · Granted Jul 6, 2021

Multimodal motion planning framework for autonomous driving vehicles

Inventors: Yajia Zhang (Sunnyvale, CA); Dong Li (Sunnyvale, CA); Liangliang Zhang (Sunnyvale, CA); Kecheng Xu (Sunnyvale, CA); Jiaming Tao (Sunnyvale, CA); Yifei Jiang (Sunnyvale, CA); Qi Luo (Sunnyvale, CA); Jiangtao Hu (Sunnyvale, CA); Jinghao Miao (Sunnyvale, CA)
Assignee: BAIDU USA LLC
G05D1/0088G01C21/3446G05D1/0212G05D2201/0213
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Quick Facts
Patent No.
US 11,054,829
App. No.
16/037,908
Granted
Jul 6, 2021
Kind
B2
Abstract

Methods and systems for multimodal motion planning framework for autonomous driving vehicles are disclosed. In one embodiment, driving environment data of an autonomous vehicle is received, where the environment data includes a route segment. The route segment is segmented into a number of route sub-segments. A specific driving scenario is assigned to each of the route sub-segments, where each specific driving scenario is included in a set of driving scenarios. A first motion planning algorithm is assigned according to a first assigned driving scenario included in the set of driving scenarios. The first motion planning algorithm is invoked to generate a first set of trajectories. The autonomous vehicle is controlled based on the first set of trajectories.

Claims (74)

1. A computer-implemented method for operating an autonomous vehicle, comprising:

receiving driving environment data of the autonomous vehicle;

segmenting a route segment on which the autonomous vehicle travels into a plurality of route sub-segments;

assigning a specific driving scenario to each of the plurality of route sub-segments based on the received driving environment data, wherein each specific driving scenario is included in a set of driving scenarios, the set of driving scenarios including a parking lot scenario and an unmapped scenario;

assigning a first motion planning algorithm to operate the autonomous vehicle along a first route sub-segment according to a first assigned driving scenario included in the set of driving scenarios;

invoking the first motion planning algorithm to generate a first set of trajectories; and

controlling the autonomous vehicle based on the first set of trajectories.

2. The method of claim 1 , further comprising:

assigning a second motion planning algorithm to operate the autonomous vehicle along a second route sub-segment according to a second assigned driving scenario included in the set of driving scenarios;

invoking the second motion planning algorithm to generate a second set of trajectories; and

controlling the autonomous vehicle based on the second set of trajectories.

3. The method of claim 2 , wherein assigning a specific driving scenario to each of the plurality of route sub-segments comprises:

assigning the first driving scenario to the first route sub-segment, and

assigning the second driving scenario to the second route sub-segment,

wherein the first route sub-segment and the second route sub-segment are included in the plurality of route sub-segments.

4. The method of claim 3 , wherein assigning a specific driving scenario to each of the plurality of route sub-segments further comprises:

assigning a third driving scenario to a third route sub-segment, and

assigning a fourth driving scenario to a fourth route sub-segment,

wherein the third route sub-segment and the fourth route sub-segment are included in the plurality of route sub-segments.

5. The method of claim 3 , further comprising:

generating the first assigned driving scenario when the autonomous vehicle is operated to travel on the first route sub-segment; and

generating the second assigned driving scenario when the autonomous vehicle is operated to travel on the second route sub-segment.

6. The method of claim 1 , wherein the specific driving scenario is assigned based on map and route information included in the driving environment data.

7. The method of claim 1 , wherein the set of driving scenarios further includes an urban scenario and a highway scenario.

8. A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor, cause the processor to perform operations, the operations comprising:

receiving driving environment data of an autonomous vehicle;

segmenting a route segment on which the autonomous vehicle travels into a plurality of route sub-segments;

assigning a specific driving scenario to each of the plurality of route sub-segments based on the received driving environment data, wherein each specific driving scenario is included in a set of driving scenarios, the set of driving scenarios including a parking lot scenario and an unmapped scenario;

assigning a first motion planning algorithm to operate the autonomous vehicle along a first route sub-segment according to a first assigned driving scenario included in the set of driving scenarios;

invoking the first motion planning algorithm to generate a first set of trajectories; and

controlling the autonomous vehicle based on the first set of trajectories.

9. The non-transitory machine-readable medium of claim 8 , wherein the operations further comprise:

assigning a second motion planning algorithm to operate the autonomous vehicle along a second route sub-segment according to a second assigned driving scenario included in the set of driving scenarios;

invoking the second motion planning algorithm to generate a second set of trajectories; and

controlling the autonomous vehicle based on the second set of trajectories.

10. The non-transitory machine-readable medium of claim 9 , wherein assigning a specific driving scenario to each of the plurality of route sub-segments comprises:

assigning the first driving scenario to the first route sub-segment, and

assigning the second driving scenario to the second route sub-segment,

wherein the first route sub-segment and the second route sub-segment are included in the plurality of route sub-segments.

11. The non-transitory machine-readable medium of claim 10 , wherein assigning a specific driving scenario to each of the plurality of route sub-segments further comprises:

assigning a third driving scenario to a third route sub-segment, and

assigning a fourth driving scenario to a fourth route sub-segment,

wherein the third route sub-segment and the fourth route sub-segment are included in the plurality of route sub-segments.

12. The non-transitory machine-readable medium of claim 10 , wherein the operations further comprise:

generating the first assigned driving scenario when the autonomous vehicle is operated to travel on the first route sub-segment; and

generating the second assigned driving scenario when the autonomous vehicle is operated to travel on the second route sub-segment.

13. The non-transitory machine-readable medium of claim 8 , wherein the specific driving scenario is assigned based on map and route information included in the driving environment data.

14. The non-transitory machine-readable medium of claim 8 , wherein the set of driving scenarios further includes an urban scenario and a highway scenario.

15. 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

receiving driving environment data of an autonomous vehicle;

segmenting a route segment on which the autonomous vehicle travels into a plurality of route sub-segments;

assigning a specific driving scenario to each of the plurality of route sub-segments based on the received driving environment data, wherein each specific driving scenario is included in a set of driving scenarios, the set of driving scenarios including a parking lot scenario and an unmapped scenario;

assigning a first motion planning algorithm to operate the autonomous vehicle along a first route sub-segment according to a first assigned driving scenario included in the set of driving scenarios;

invoking the first motion planning algorithm to generate a first set of trajectories; and

controlling the autonomous vehicle based on the first set of trajectories.

16. The data processing system of claim 15 , wherein the operations further include:

assigning a second motion planning algorithm to operate the autonomous vehicle along a second route sub-segment according to a second assigned driving scenario included in the set of driving scenarios;

invoking the second motion planning algorithm to generate a second set of trajectories; and

controlling the autonomous vehicle based on the second set of trajectories.

17. The data processing system of claim 16 , assigning a specific driving scenario to each of the plurality of route sub-segments comprises:

assigning the first driving scenario to the first route sub-segment, and

assigning the second driving scenario to the second route sub-segment,

wherein the first route sub-segment and the second route sub-segment are included in the plurality of route sub-segments.

18. The data processing system of claim 17 , wherein assigning a specific driving scenario to each of the plurality of route sub-segments further comprises:

assigning a third driving scenario to a third route sub-segment, and

assigning a fourth driving scenario to a fourth route sub-segment,

wherein the third route sub-segment and the fourth route sub-segment are included in the plurality of route sub-segments.

19. The data processing system of claim 17 , wherein the operations further include:

generating the first assigned driving scenario when the autonomous vehicle is operated to travel on the first route sub-segment; and

generating the second assigned driving scenario when the autonomous vehicle is operated to travel on the second route sub-segment.

20. The data processing system of claim 15 , wherein the specific driving scenario is assigned based on map and route information included in the driving environment data.

21. The data processing system of claim 15 , wherein the set of driving scenarios further includes an urban scenario and a highway scenario.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 18, 2018
From: ZHANG, YAJIA; LI, DONG; ZHANG, LIANGLIANG; XU, KECHENG; TAO, JIAMING; JIANG, YIFEI; LUO, QI; HU, JIANGTAO; MIAO, JINGHAO
To: BAIDU USA LLC
Reel/Frame 046383/0315 →
Continuity (1)
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