DATA-DRIVEN PREDICTION-BASED SYSTEM AND METHOD FOR TRAJECTORY PLANNING OF AUTONOMOUS VEHICLES

• US 20190072973A1
• Filed: 09/07/2017
• Published: 03/07/2019
• Est. Priority Date: 09/07/2017
• Status: Active Grant

• Current Assignee: TuSimple, Inc. (TuSimple Holdings, Inc.)
• Original Assignee: Tusimple
• Inventors: SUN, Xing, LIN, Wutu, LIU, Liu, MA, Kai-Chieh, XUAN, Zijie, ZHAO, Yufei
• Granted Patent: US 10,649,458 B2
• Time in Patent Office: Days
• CPC Class Codes: B62D 15/025 Active steering aids, e.g. helping the driver by actively influencing the steering system after environment evaluation B62D1/28 takes precedence
• CPC Class Codes: B62D 15/0255 Automatic changing of lane, e.g. for passing another vehicle
• CPC Class Codes: B62D 15/026 combined with automatic distance control, i.e. electronic tow bar
• CPC Class Codes: B62D 15/0265 Automatic obstacle avoidance by steering
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G05D 1/0221 involving a learning process
• CPC Class Codes: G08G 1/166 for active traffic, e.g. moving vehicles, pedestrians, bikes

Abstract

A data-driven prediction-based system and method for trajectory planning of autonomous vehicles are disclosed. A particular embodiment includes: generating a first suggested trajectory for an autonomous vehicle; generating predicted resulting trajectories of proximate agents using a prediction module; scoring the first suggested trajectory based on the predicted resulting trajectories of the proximate agents; generating a second suggested trajectory for the autonomous vehicle and generating corresponding predicted resulting trajectories of proximate agents, if the score of the first suggested trajectory is below a minimum acceptable threshold; and outputting a suggested trajectory for the autonomous vehicle wherein the score corresponding to the suggested trajectory is at or above the minimum acceptable threshold.

Claims

1. A system comprising:

a data processor; and

a trajectory planning module, executable by the data processor, the trajectory planning module being configured to perform a data-driven prediction-based trajectory planning operation for autonomous vehicles, the trajectory planning operation being configured to;

generate a first suggested trajectory for an autonomous vehicle;

generate predicted resulting trajectories of proximate agents using a prediction module;

score the first suggested trajectory based on the predicted resulting trajectories of the proximate agents;

generate a second suggested trajectory for the autonomous vehicle and generate corresponding predicted resulting trajectories of proximate agents, if the score of the first suggested trajectory is below a minimum acceptable threshold; and

output a suggested trajectory for the autonomous vehicle wherein the score corresponding to the suggested trajectory is at or above the minimum acceptable threshold.

2. The system of claim 1 wherein the data-driven prediction-based trajectory planning operation includes machine learnable components.

3. The system of claim 1 wherein the output suggested trajectory is dependent upon the predicted resulting trajectories of proximate agents.

4. The system of claim 1 wherein the data-driven prediction-based trajectory planning operation is configured to generate the predicted resulting trajectories and their confidence values, or to generate a trajectory distribution of proximate agents.

5. The system of claim 1 wherein the prediction module is configured to retain information corresponding to predicted trajectories of proximate agents as mathematical or data representations.

6. The system of claim 1 wherein the suggested trajectory is output to a vehicle control subsystem causing the autonomous vehicle to follow the output suggested trajectory.

7. A method comprising:

generating a first suggested trajectory for an autonomous vehicle;

generating predicted resulting trajectories of proximate agents using a prediction module;

scoring the first suggested trajectory based on the predicted resulting trajectories of the proximate agents;

generating a second suggested trajectory for the autonomous vehicle and generating corresponding predicted resulting trajectories of proximate agents, if the score of the first suggested trajectory is below a minimum acceptable threshold; and

outputting a suggested trajectory for the autonomous vehicle wherein the score corresponding to the suggested trajectory is at or above the minimum acceptable threshold.

8. The method of claim 7 including causing a machine to implement a learnable prediction module.

9. The method of claim 7 wherein the output suggested trajectory is dependent upon the predicted resulting trajectories of proximate agents.

10. The method of claim 7 including generating the predicted resulting trajectories and their confidence values, or generating a trajectory distribution of proximate agents.

11. The method of claim 7 including causing the prediction module to retain information corresponding to predicted trajectories of proximate agents as mathematical or data representations.

12. The method of claim 7 including outputting the suggested trajectory to a vehicle control subsystem causing the autonomous vehicle to follow the output suggested trajectory.

13. A non-transitory machine-usable storage medium embodying instructions which, when executed by a machine, cause the machine to:

generate a first suggested trajectory for an autonomous vehicle;

generate predicted resulting trajectories of proximate agents using a prediction module;

score the first suggested trajectory based on the predicted resulting trajectories of the proximate agents;

generate a second suggested trajectory for the autonomous vehicle and generate corresponding predicted resulting trajectories of proximate agents, if the score of the first suggested trajectory is below a minimum acceptable threshold; and

output a suggested trajectory for the autonomous vehicle wherein the score corresponding to the suggested trajectory is at or above the minimum acceptable threshold.

14. The non-transitory machine-usable storage medium of claim 13 wherein the instructions are further configured to enable machine learning.

15. The non-transitory machine-usable storage medium of claim 13 wherein the output suggested trajectory is dependent upon the predicted resulting trajectories of proximate agents.

16. The non-transitory machine-usable storage medium of claim 13 wherein the instructions are further configured to generate the predicted resulting trajectories and their confidence values, or to generate a trajectory distribution of proximate agents.

17. The non-transitory machine-usable storage medium of claim 13 wherein the prediction module is configured to retain information corresponding to predicted trajectories of proximate agents as mathematical or data representations.

18. The non-transitory machine-usable storage medium of claim 13 wherein the suggested trajectory is output to a vehicle control subsystem causing the autonomous vehicle to follow the output suggested trajectory.