# US 2026/0062001 A1 · Methods for controlling the driving operation of a vehicle > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2026/0062001 A1 - Document ID: US20260062001A1 - Status: Published application - Kind: A1 - Application number: 19/313,356 - Filed: 2025-08-28 - Published: 2026-03-05 - Earliest claimed: 2024-08-29 - Applicants: Cariad SE; Robert Bosch GmbH - Inventors: Jonas Klandt - Web page: https://patentgrep.com/patent/US20260062001A1 ## CPC - B60W 30/0956: {the prediction being responsive to traffic or environmental parameters} - B60W 30/06: Automatic manoeuvring for parking - B60W 30/09: Taking automatic action to avoid collision, e.g. braking and steering - G06V 10/764: using classification, e.g. of video objects - G06V 20/58: Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads - B60W 2420/403: Image sensing, e.g. optical camera - B60W 2554/60: Traversable objects, e.g. speed bumps or curbs - B60W: CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract The disclosure relates to a method for controlling a driving operation of a vehicle. According to the method, sensor data of a monitoring area in front of the vehicle is captured and environmental images of an environment of the vehicle are captured. Based on the sensor data and the environmental images, objects are optically identified and classified into known objects and unknown objects. A degree of passability is associated with the known objects. The unknown objects are further processed by input of their pictures into a computing unit configured with the degree of passability of objects. The unknown objects are identified and a degree of passability is associated with them. This degree of passability for the unknown objects is provided to a control unit and the driving operation of the vehicle is controlled by it by using the degree of passability of the objects and the unknown objects. ## Claims ### Claim 1 A method for controlling a driving operation of a vehicle, the method comprising: capturing sensor data of a monitoring area in front of the vehicle in a driving direction by way of at least one sensor of the vehicle; optically capturing environmental images of an environment of the vehicle by way of at least one camera of the vehicle; optically identifying relevant objects in front of the vehicle in the driving direction based on the sensor data and the environmental images; classifying the relevant objects based on the sensor data and/or based on a picture of one or more of the relevant objects into known relevant objects and into unknown relevant objects; associating a degree of passability with the known relevant objects, wherein the degree of passability is stored in a control unit; further processing the unknown relevant objects by inputting a picture of each of the unknown relevant objects into a computing unit that estimates the degree of passability of objects, identifying the unknown relevant objects and associating the degree of passability for the unknown relevant objects by the computing unit and providing the degree of passability for the unknown relevant objects to the control unit, and controlling the driving operation of the vehicle by the control unit using the degree of passability of the known relevant objects and the unknown relevant objects. ### Claim 2 (depends on 1) The method according to claim 1, further comprising: generating point clouds representing objects by the at least one sensor of the vehicle as the sensor data or based on the sensor data. ### Claim 3 (depends on 1) The method according to claim 1, wherein the computing unit is configured with a number of model parameters characterizing the degree of passability of objects. ### Claim 4 (depends on 1) The method according to claim 1, wherein the computing unit adopts, from a master unit comprising a plurality of model parameters, a processing procedure of the master unit in determining the degree of passability of objects and the computing unit applies the processing procedure in the further processing of the unknown relevant objects. ### Claim 5 (depends on 4) The method according to claim 4, wherein, in the further processing of the unknown relevant objects by the computing unit, only the picture of each of the unknown relevant objects is input into the computing unit configured with the model parameters characterizing the degree of passability of objects and imitating the processing procedure of the master unit. ### Claim 6 (depends on 5) The method according to claim 5, wherein, in the further processing of the unknown relevant objects, a uniform and non-divided picture of each of the unknown relevant objects is input into the computing unit. ### Claim 7 (depends on 1) The method according to claim 1, wherein the driving operation of the vehicle is controlled by the control unit by using the degree of passability of the known relevant objects and the unknown relevant objects, and wherein the driving operation includes an evasive maneuver of the vehicle and/or a parking operation of the vehicle. ### Claim 8 (depends on 1) The method according to claim 1, wherein the degree of passability associated with each relevant object of the relevant objects indicates whether the relevant object is passable or not passable. ### Claim 9 An assistance system of a vehicle, the assistance system comprising: at least one control unit; at least one sensor system including at least one sensor that, in operation, generates sensor data; at least one camera that, in operation, generates environmental images; and a computing unit that, in operation, determines degree of passability of objects, wherein the computing unit, in operation, optically identifies relevant objects in front of the vehicle in a driving direction based on the sensor data and the environmental images; classifies the relevant objects based on the sensor data and/or based on a picture of one or more of the relevant objects into known relevant objects and into unknown relevant objects; associates a degree of passability with the known relevant objects, wherein the degree of passability is stored in a control unit; further processes the unknown relevant objects by inputting a picture of each of the unknown relevant objects into a computing unit that estimates the degree of passability of objects, identifies the unknown relevant objects and associating the degree of passability for the unknown relevant objects by the computing unit and providing the degree of passability for the unknown relevant objects to the control unit, and controls a driving operation of the vehicle using the degree of passability of the known relevant objects and the unknown relevant objects. ### Claim 10 (depends on 9) A vehicle comprising: the assistance system according to claim 9.