Autonomous lane merging system and method

Patent metadata

Field	Value
Publication number	US-2023322267-A1
Application number	US-202217719153-A
Country	US
Kind code	A1
Filing date	Apr 12, 2022
Priority date	Apr 12, 2022
Publication date	Oct 12, 2023
Grant date	—

Abstract

A computer-implemented method of performing an autonomous lane merging of a vehicle. The method includes: identifying one or more objects in a plurality of lanes in the vicinity of the vehicle; identifying one or more gaps among the one or more objects; determining a mode of the vehicle; determining a terminal state of a planned trajectory of the vehicle based on the identified objects, gaps, and the mode of the vehicle; performing a sanity check based on the terminal state of the planned trajectory; generating the planned trajectory of the vehicle if the sanity check passes; providing the planned trajectory to a controller of the vehicle to autonomously move the vehicle according to the planned trajectory.

First claim

What is claimed is:

1 . A computer-implemented method of performing an autonomous lane merging of a vehicle, the method comprising:
identifying one or more objects in a plurality of lanes in the vicinity of the vehicle; identifying one or more gaps among the one or more objects; determining a mode of the vehicle; determining a terminal state of a planned trajectory of the vehicle based on the identified objects, gaps, and the mode of the vehicle; performing a sanity check based on the terminal state of the planned trajectory; generating the planned trajectory of the vehicle if the sanity check passes; providing the planned trajectory to a controller of the vehicle to autonomously move the vehicle according to the planned trajectory.

2 . The computer-implemented method of claim 1 , further comprising validating the planned trajectory before providing the planned trajectory to the controller.

3 . The computer-implemented method of claim 2 , wherein validating the planned trajectory comprises performing speed validation, acceleration validation, curvature validation, and collision check validation.

4 . The computer-implemented method of claim 1 , wherein identifying the one or more objects comprises calculating each object's position in the vehicle's body frame.

5 . The computer-implemented method of claim 1 , wherein identifying the one or more gaps comprises:
sorting the one or more objects into different groups based on a lane ID associated with each object, and sorting the different groups based on longitudinal distance of each different group.

6 . The computer-implemented method of claim 5 , wherein identifying the one or more gaps further comprises:
predicting each object's longitudinal and lateral states for a given time; and calculating the gaps in each lane; and forming different groups of gaps.

7 . The computer-implemented method of claim 1 , wherein the mode of the vehicle comprises one of a velocity-keeping mode, a car-following mode, and a merging mode.

8 . The computer-implemented method of claim 7 , wherein determining the mode of the vehicle comprises:
determining whether a merge signal is initiated by a user of the vehicle; if the merge signal is initiated, entering the merging mode; if the merge signal is not initiated, determining if there is an object observed in front of the vehicle and if a longitudinal velocity of the observed object is less than a target speed; if there is an object observed in front of the vehicle and the longitudinal velocity of the observed object is less than the target speed, entering the car-following mode; if either there is no observed object or the longitudinal velocity of the observed object is no less than the target speed, entering the velocity-keeping mode.

9 . The computer-implemented method of claim 7 , wherein performing a sanity check based on the terminal state of the planned trajectory comprises:
determining that the vehicle is in the velocity-keeping mode; and determining whether a constant maximum acceleration of the vehicle cannot reach the target speed within a maximum sampling time.

10 . The computer-implemented method of claim 7 , wherein performing a sanity check based on the terminal state of the planned trajectory comprises:
determining that the vehicle is in a car-following mode; and calculating a distance from a current position of the vehicle to a target position and a difference in a current velocity of the vehicle and a target velocity.

11 . The computer-implemented method of claim 7 , wherein generating the planned trajectory of the vehicle comprises:
determining that the vehicle is in the vehicle-following mode; and using quartic polynomial to generate the planned trajectory based on a given initial state and a target state.

12 . The computer-implemented method of claim 7 , wherein generating the planned trajectory of the vehicle comprises:
determining that the vehicle is in the car-following mode; and using quintic polynomial to generate the planned trajectory based on a given initial state and a target state.

13 . A vehicle comprising:
one or more sensors configured to detect objects in the vicinity of the vehicle; an object processor configured to identify one or more objects in a plurality of lanes in the vicinity of the vehicle and further configured to identify one or more gaps among the one or more objects; a mode manager configured to determine a mode of the vehicle; a behavior planner configured to determine a terminal state of a planned trajectory of the vehicle based on the identified objects, gaps, and the mode of the vehicle; a sanity check layer configured to perform a sanity check based on the terminal state of the planned trajectory; a trajectory generation module configured to generate the planned trajectory of the vehicle if the sanity check passes; and a controller of the vehicle configured to autonomously move the vehicle according to the planned trajectory.

14 . The vehicle of claim 13 , further comprising:
an anchor point generation module configure to set up a plurality of anchor points associated with each lane for sampling and set a terminal lateral velocity and acceleration of the vehicle to zero.

15 . The vehicle of claim 14 , further comprising:
a vehicle state estimator configured to estimate a state of the vehicle, the state comprising at least one of a velocity, speed, direction, acceleration rate, and decelerate rate of the vehicle.

16 . The vehicle of claim 14 , further comprising:
a trajectory evaluation module configured to validate the planned trajectory before providing the planned trajectory to the controller.

17 . The vehicle of claim 14 , wherein the controller is configured to control the operation of one or more of brakes, steering output, and speed of the vehicle via controlling an actuation system.

18 . The vehicle of claim 14 , wherein the one or more sensors comprise at least one of a camera, a radar, and a LIDAR.

19 . The vehicle of claim 14 , wherein the mode of the vehicle comprises one of a velocity-keeping mode, a car-following mode, and a merging mode.

20 . A highway Autonomous Driver Assistance System (ADAS)
one or more sensors configured to detect objects in the vicinity of the vehicle; a processor; and a non-transitory storage configured to store instructions, which when executed by the processor, cause the processor to perform a method comprising:
identifying one or more objects in a plurality of lanes in the vicinity of the vehicle;
identifying one or more gaps among the one or more objects;
determining a mode of the vehicle;
determining a terminal state of a planned trajectory of the vehicle based on the identified objects, gaps, and the mode of the vehicle;
performing a sanity check based on the terminal state of the planned trajectory;
generating the planned trajectory of the vehicle if the sanity check passes;
providing the planned trajectory to a controller of the vehicle to autonomously move the vehicle according to the planned trajectory.

Assignees

• Faraday&Future Inc

Inventors

• Mei Aohan
• Zhang Chen
• Wang Fan

Classifications

• B60W60/0027 Primary

  using trajectory prediction for other traffic participants · CPC title

• B60W30/18163 Primary

  Lane change; Overtaking manoeuvres · CPC title

• B60W30/16

  Control of distance between vehicles, e.g. keeping a distance to preceding vehicle · CPC title

• B60W30/165

  Automatically following the path of a preceding lead vehicle, e.g. "electronic tow-bar" · CPC title

• B60W2552/10

  Number of lanes · CPC title