IP Library › Patent Application 16827144
Patent Application
App. No. 16/827,144

SYSTEMS AND METHODS FOR IMPLEMENTING A PREEMPTIVE CONTROL FOR AN AUTONOMOUS VEHICLE TO IMPROVE RIDE QUALITY

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Quick Facts
Patent No.
US None
App. No.
16/827,144
Abstract

Systems, methods, and non-transitory computer-readable media are provided for implementing a preemptive control for an autonomous vehicle to improve ride quality. Data from one or more sensors onboard the autonomous vehicle can be acquired. A surface imperfection of a road can be identified from the data. A next action for the autonomous vehicle can be determined based on the surface imperfection. A signal can be outputted that causes the autonomous vehicle to act in accordance with the next action.

Claims (83)

1 . A computer-implemented method for preemptive control of a vehicle to improve ride quality comprising:

determining, by a computing system onboard the vehicle, based on a high definition map, an imperfection on a road ahead of the vehicle;

detecting, by the computing system, based on data collected by at least one sensor onboard the vehicle, the imperfection on the road ahead;

determining, by the computing system, a next action of the vehicle based on the imperfection; and

synchronizing a timing of the next action to a predicted arrival time at the imperfection.

2 . The computer-implemented method of claim 1 , wherein the synchronizing a timing of the next action to a predicted arrival time comprises synchronizing a timing of the next action to counteract a predicted consequence resulting when the vehicle is predicted to arrive at the imperfection.

3 . The computer-implemented method of claim 1 , wherein determining the next action of the vehicle based on the imperfection comprises:

determining, based on the high definition map, a lane of the road ahead on which the imperfection is located;

determining that the vehicle is on the lane on which the imperfection is located;

determining, based on the high definition map and the data collected by the at least one sensor, a size of the imperfection; and

changing a speed of the vehicle in response to the size of the imperfection.

4 . The computer-implemented method of claim 3 , wherein changing the speed of the vehicle in response to the size of the imperfection comprises:

determining that the size of the imperfection is below a threshold size; and

accelerating the vehicle prior to reaching the imperfection.

5 . The computer-implemented method of claim 3 , wherein changing the speed of the vehicle in response to the size of the imperfection comprises:

determining that the size of the imperfection exceeds a threshold size; and

decelerating the vehicle prior to reaching the imperfection.

6 . The computer-implemented method of claim 1 , wherein determining the next action of the vehicle based on the imperfection comprises:

determining, based on the high definition map, a lane of the road ahead on which the imperfection is located;

determining that the vehicle is on the lane on which the imperfection is located;

acquiring, through the data collected by the at least one sensor, a traffic density of a neighboring lane next to the lane the vehicle is on;

determining, based on the traffic density, a safety of the vehicle changing to the neighboring lane; and

directing the vehicle to change lanes from the lane to the neighboring lane prior to reaching the imperfection, based on the determined safety.

7 . The computer-implemented method of claim 6 , wherein determining a safety of the vehicle changing to the neighboring lane comprises:

determining, based on the at least one sensor, the neighboring lane is free of moving vehicles within a predetermined distance of the vehicle; and

in response to determining that the neighboring lane is free of moving vehicles within a predetermined distance, determining that the safety satisfies a safety condition.

8 . The computer-implemented method of claim 1 , wherein determining the next action of the vehicle based on the imperfection comprises:

determining, based on the high definition map, a lane of the road ahead on which the imperfection is located;

determining that the vehicle is on the lane on which the imperfection is located;

acquiring, through the data collected by the at least one sensor, a traffic density of a neighboring lane next to the lane the vehicle is on;

determining, based on the traffic density, a safety of the vehicle changing to the neighboring lane;

determining, based on the high definition map and the data collected by the at least one sensor, a size of the imperfection; and

changing a speed of the vehicle based on the size of the imperfection.

9 . The computer-implemented method of claim 1 , further comprising:

determining, based on the high definition map and the data collected by the least one sensor, an inclination or declination of the road ahead;

changing a speed of the vehicle in anticipation of the inclination or declination.

10 . The computer-implemented method of claim 1 , wherein the at least one sensor onboard the vehicle includes at least one of LiDAR, radar, or camera.

11 . A computing system for preemptive control of a vehicle to improve ride quality comprising:

one or more processors; and

a memory storing instructions that, when executed by the one or more processor, causes the computer system to perform a method comprising:

determining, based on a high definition map, an imperfection on a road ahead of the vehicle;

detecting, through data collected by at least one sensor onboard the vehicle, the imperfection on the road ahead;

determining a next action of the vehicle based on the imperfection; and

synchronizing a timing of the next action to a predicted arrival time at the imperfection.

12 . The computing system of claim 11 , wherein determining the next action of the vehicle based on the imperfection comprises:

determining, based on the high definition map, a lane of the road ahead on which the imperfection is located;

determining that the vehicle is on the lane on which the imperfection is located;

determining, based on the high definition map and the data collected by the at least one sensor, a size of the imperfection; and

changing a speed of the vehicle in response to the size of the imperfection.

13 . The computing system of claim 12 , wherein changing the speed of the vehicle in response to the size of the imperfection comprises:

determining that the size of the imperfection is below a threshold size; and

accelerating the vehicle prior to reaching the imperfection.

14 . The computing system of claim 12 , wherein changing the speed of the vehicle in response to the size of the imperfection comprises:

determining that the size of the imperfection exceeds a threshold size; and

decelerating the vehicle prior to reaching the imperfection.

15 . The computing system of claim 11 , wherein determining the next action of the vehicle based on the imperfection comprises:

determining, based on the high definition map, a lane of the road ahead on which the imperfection is located;

determining that the vehicle is on the lane on which the imperfection is located;

acquiring, through the data collected by the at least one sensor, a traffic density of a neighboring lane next to the lane the vehicle is on;

determining, based on the traffic density, a safety of the vehicle changing to the neighboring lane; and

directing the vehicle to change lanes from the lane to the neighboring lane prior to reaching to the imperfection, based on the determined safety.

16 . A non-transitory computer-readable medium comprising instructions that, when executed by one or more processors, cause a computer system for preemptive control of an vehicle to perform a method comprising:

determining, based on a high definition map, an imperfection on a road ahead of the vehicle;

detecting, through data collected by at least one sensor onboard the vehicle, the imperfection on the road ahead;

determining a next action of the vehicle based on the imperfection; and

synchronizing a timing of the next action to a predicted arrival time at the imperfection.

17 . The non-transitory computer-readable medium of claim 16 , wherein determining the next action of the vehicle based on the imperfection comprises:

determining, based on the high definition map, a lane of the road ahead on which the imperfection is located;

determining that the vehicle is on the lane on which the imperfection is located;

determining, based on the high definition map and the data collected by the at least one sensor, a size of the imperfection; and

changing a speed of the vehicle in response to the size of the imperfection.

18 . The non-transitory computer-readable medium of claim 17 , wherein changing the speed of the vehicle in response to the size of the imperfection comprises:

determining that the size of the imperfection is below a threshold size; and

accelerating the vehicle prior to reaching the imperfection.

19 . The non-transitory computer-readable medium of claim 17 , wherein changing the speed of the vehicle in response to the size of the imperfection comprises:

determining that the size of the imperfection is below a threshold size; and

accelerating the vehicle prior to reaching the imperfection.

20 . The non-transitory computer-readable medium of claim 16 , wherein determining the next action of the vehicle based on the imperfection comprises:

determining, based on the high definition map, a lane of the road ahead on which the imperfection is located;

determining that the vehicle is on the lane on which the imperfection is located;

acquiring, through the data collected by the at least one sensor, a traffic density of a lane adjacent to the lane the vehicle is on;

determining, based on the traffic density, a safety of the vehicle changing to the neighboring lane; and

directing the vehicle to change lanes from the lane to the neighboring lane prior to reaching to the imperfection, based on the determined safety.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 23, 2020
From: HOU, JIE
To: PONY.AI, INC.
Reel/Frame 053857/0131 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 31, 2020
From: YU, XIANG; LOU, TIANCHENG; PENG, JUN; DENG, NENGXIU
To: PONY.AI, INC.
Reel/Frame 053373/0114 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 31, 2020
From: PONY.AI, INC.
To: PONY AI INC.
Reel/Frame 053374/0083 →