US 12,589,768 B2Granted

Path determination for autonomous vehicle parking

AssigneeAptiv Technologies AG

InventorsTanto Sugiarto, Mateusz Orlowski, Wojciech Turlej

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Abstract

A method of determining a movement path for a vehicle includes determining a set of adjacent nodes with respect to a current node. The method includes determining, via a neural network, a subsequent path node and determining whether a path based on the subsequent path node connects a source to a goal node. The method includes, in response to a determination that the path based on the subsequent path node does not connect the source node to the goal node, determining an alternative subsequent path node, and determining, via the neural network, a second path based on the alternative subsequent path node. The method includes, in response to a determination that the path based on the subsequent path node connects the source to the goal node, selecting the path based on the subsequent path node as the movement path, and executing a set of actions associated with the movement path.

Claims24

Dependent claims

A method of determining a movement path for a vehicle from a source node to a goal node, the source node corresponding to a current position and a current orientation of the vehicle, the goal node corresponding to a goal position and a goal orientation of the vehicle, and the goal node being defined with respect to the source node, the method comprising:

determining a set of adjacent nodes, wherein each node of the set of adjacent nodes represents movement of the vehicle with respect to a current node;
determining a set of costs associated with the set of adjacent nodes;
determining a path-starting node based on a current node by:
determining, via a neural network, a predicted node based on the current node, wherein the predicted node represents movement of the vehicle with respect to the current node;
and
selecting the predicted node as the path-starting node;
determining, via the neural network, a first set of path nodes based on the path-starting node;
determining whether a path defined by the first set of path nodes connects the source node to the goal node;
in response to a determination that the path defined by the first set of path nodes does not connect the source node to the goal node:
determining an alternative path-starting node based on a lowest cost node of the set of adjacent nodes, and
determining, via the neural network, a second set of path nodes based on the alternative path-starting node, and
in response to a determination that the path defined by the first set of path nodes connects the source node to the goal node:
selecting the first set of path nodes as the movement path, and
executing a set of actions associated with the movement path.

11 more elements

A system of determining a movement path for a vehicle from a source node to a goal node, the source node corresponding to a current position and a current orientation of the vehicle, the goal node corresponding to a goal position and a goal orientation of the vehicle, and the goal node being defined with respect to the source node, the system comprising:

memory hardware;
and
processor hardware communicatively coupled to the memory hardware, wherein the processor hardware is configured to:
determine a set of adjacent nodes, wherein each node of the set of adjacent nodes represents movement of the vehicle with respect to a current node;
determine a set of costs associated with the set of adjacent nodes;
determine a path-starting node based on a current node by:
determining, via a neural network, a predicted node based on the current node, wherein the predicted node represents movement of the vehicle with respect to the current node;
and
selecting the predicted node as the path-starting node;
determine, via the neural network, a first set of path nodes based on the path-starting node;
determine whether a path defined by the first set of path nodes connects the source node to the goal node;
in response to a determination that the path defined by the first set of path nodes does not connect the source node to the goal node:
determine an alternative path-starting node based on a lowest cost node of the set of adjacent nodes, and
determine, via the neural network, a second set of path nodes based on the alternative subsequent path-starting node, and
in response to a determination that the path defined by the first set of path nodes connects the source node to the goal node:
select the first set of path nodes as the movement path, and
execute a set of actions associated with the movement path.

14 more elements

Dependencies are inferred from the claim text.

Facts

Application: 18/590,375Filed 28 Feb 2024
Published: US 2025/0269873 A128 Aug 2025
Granted: 31 Mar 2026
Term ends: Not estimatedThe source records don’t support an estimate.

Classification18 codes

B60W 60/0011
Planning or execution of driving tasks: involving control alternatives for a single driving scenario, e.g. planning several paths to avoid obstacles
B60T 7/12
Brake-action initiating means: for automatic initiation; for initiation not subject to will of driver or passenger
B60W 10/04
Conjoint control of vehicle sub-units of different type or different function: including control of propulsion units
B60W 10/18
Conjoint control of vehicle sub-units of different type or different function: including control of braking systems