# US 11,897,403 B2 · Group identity-driven system and method for adjusting an adjustable component 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 11,897,403 B2 - Document ID: US11897403B2 - Status: Granted - Kind: B2 - Application number: 17/543,108 - Filed: 2021-12-06 - Published: 2023-06-08 - Granted: 2024-02-13 - Earliest claimed: 2021-12-06 - Assignees: Ford Global Technologies, LLC - Applicants: Ford Global Technologies, LLC - Inventors: David Alfred Ostrowski; Leopoldo Urbina; Akshay Dirisala; Elizabeth Anne Manwell; Austin Kirchner - Web page: https://patentgrep.com/patent/US11897403B2 ## CPC - B60N 2/0268: {using sensors or detectors for adapting the seat or seat part, e.g. to the position of an occupant} - B60R 16/037: for occupant comfort {, e.g. for automatic adjustment of appliances according to personal settings, e.g. seats, mirrors, steering wheel} - B60N 2/0023: {for detection of driver fatigue} - B60N 2/0024: {for identifying, categorising or investigation of the occupant or object on the seat} - B60N 2/0025: {by using weight measurement} - B60N 2/0248: {with memory of positions} - B60N 2/0273: {taking into account user data, e.g. knee height or physical state} - B60N 2/0022: {for sensing anthropometric parameters, e.g. heart rate or body temperature} - B60N 2210/16: Electromagnetic waves - B60N 2210/24: Cameras - B60N 2220/30: using a neural network - B60N: SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR - B60R: VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR ## Abstract Systems and methods are disclosed for supporting and executing automated control of adjustable components of a vehicle based on occupant classification in a group identity database. Methods and systems for generating and employing the group identity database are also disclosed. Occupancy information may be utilized to determine how the group identity database is employed. ## Claims ### Claim 1 A method for controlling at least one adjustable component of a vehicle, the method comprising: detecting one or more personal mobile devices in the vehicle to determine a current occupancy configuration; receiving occupant data via at least one controller, the occupant data including identification information corresponding to at least one occupant of the vehicle; identifying, based on the identification information, a plurality of group identity profiles associated with the identification information via the at least one controller, each of the plurality of group identity profiles corresponding to one of a plurality of occupancy configurations; determining a current group identity profile of the plurality of group identity profiles based on the current occupancy configuration of the plurality of occupancy configurations via the at least one controller, each of the plurality of group identity profiles including occupancy information corresponding to a number of occupants in the vehicle and an identity of the at least one occupant of the vehicle; determining a target position for the at least one adjustable component based on the current group identity profile via the at least one controller; communicating, via an adjustment control system, an instruction to position the at least one adjustable component toward the target position; and adjusting, via the adjustment control system, the at least one adjustable component toward the target position. ### Claim 2 (depends on 1) The method for controlling at least one adjustable component of the vehicle of claim 1, wherein the at least one adjustable component includes at least one of a vehicle seat, a vehicle mirror, a steering column, and a pedal assembly. ### Claim 3 (depends on 1) The method for controlling at least one adjustable component of the vehicle of claim 1, wherein determining the current group identity profile includes referencing a group identity database, wherein the group identity database comprises the plurality of group identity profiles. ### Claim 4 (depends on 1) The method for controlling at least one adjustable component of a vehicle of claim 1, further including: applying a machine learning model that is trained to evaluate demographic information of a user pool and group the at least one occupant with an aligned cohort of individuals from the user pool that have chosen similar settings of the adjustment control system with occupancy configurations that are similar to the current occupancy configuration. ### Claim 5 (depends on 4) The method for controlling at least one adjustable component of a vehicle of claim 4, further comprising: monitoring a manual adjustment made to the at least one adjustable component away from the target position via the at least one controller; and updating the target position based on the manual adjustment via the at least one controller. ### Claim 6 (depends on 1) The method for controlling at least one adjustable component of a vehicle of claim 1, wherein the at least one occupant includes a first occupant and a second occupant, wherein the identification information includes an identity of the first occupant and an identity of the second occupant, wherein the at least one adjustable component includes a first adjustable component associated with the first occupant and a second adjustable component associated with the second occupant, wherein the method further comprises: modifying, via the at least one controller, the target position for the first adjustable component based on the identity of the second occupant and the target position for the second adjustable component. ### Claim 7 (depends on 6) The method for controlling at least one adjustable component of a vehicle of claim 6, wherein the first adjustable component is a vehicle seat of a driver of the vehicle, and the second adjustable component is a vehicle seat of a non-driver passenger of the vehicle. ### Claim 8 A system for controlling at least one adjustable component of a vehicle, the system comprising: at least one positioning actuator for adjusting the at least one adjustable component; an adjustment control system that controls the at least one positioning actuator in response to an instruction; an occupancy detection system that detects one or more personal mobile devices in the vehicle to determine a current occupancy configuration of the vehicle; at least one controller: that receives occupant data, the occupant data including identification information corresponding to at least one occupant of the vehicle; that identifies, based on the identification information, a plurality of group identity profiles associated with the identification information, each of the plurality of group identity profiles corresponding to one of a plurality of occupancy configurations; that determines a current group identity profile of the plurality of group identity profiles based on the current occupancy configuration of the plurality of occupancy configurations; that determines a target position for the at least one adjustable component based on the current group identity profile; and that communicates, via the adjustment control system, the instruction to position the at least one adjustable component toward the target position. ### Claim 9 (depends on 8) The system for controlling at least one adjustable component of a vehicle of claim 8, wherein the at least one controller adjusts the at least one adjustable component toward the target position. ### Claim 10 (depends on 9) The system for controlling at least one adjustable component of the vehicle of claim 9, wherein the at least one adjustable component includes at least one of a vehicle seat, a vehicle mirror, a steering column, and a pedal assembly. ### Claim 11 (depends on 8) The system for controlling at least one adjustable component of the vehicle of claim 8, wherein the at least one controller applies a machine learning model that is trained to evaluate demographic information of a user pool and group the at least one occupant with an aligned cohort of individuals from the user pool that have chosen similar settings of the adjustment control system with occupancy configurations that are similar to the current occupancy configuration. ### Claim 12 (depends on 11) The system for controlling at least one adjustable component of the vehicle of claim 11, wherein the machine learning model is further trained to determine anxiety data corresponding to a projected anxiety of the at least one occupant based on the occupancy information wherein determining the tar et position data is further based on the anxiety data. ### Claim 13 (depends on 8) The system for controlling at least one adjustable component of the vehicle of claim 8, wherein the at least one controller comprises a controller on a personal mobile device of the at least one occupant and a local controller of the vehicle. ### Claim 14 (depends on 8) The system for controlling at least one adjustable component of the vehicle of claim 8, wherein the at least one controller: monitors a manual adjustment made to the at least one adjustable component away from the target position; and updates the target position based on the manual adjustment. ### Claim 15 (depends on 8) The system for controlling at least one adjustable component of the vehicle of claim 8, wherein the at least one controller determining the current group identity profile includes the at least one controller referencing a group identity database, wherein the group identity database comprises the plurality of group identity profiles. ### Claim 16 (depends on 8) The system for controlling at least one adjustable component of the vehicle of claim 8, wherein the at least one occupant includes a first occupant and a second occupant, wherein the identification information includes an identity of the first occupant and an identity of the second occupant, wherein the at least one adjustable component includes a first adjustable component associated with the first occupant and a second adjustable component associated with a second occupant, wherein the at least one controller further modifies the target position for the first adjustable component based on the identity of the second occupant and the target position for the second adjustable component. ### Claim 17 (depends on 16) The system for controlling at least one adjustable component of the vehicle of claim 16, wherein the first adjustable component is a vehicle seat of a driver of the vehicle, and the second adjustable component is a vehicle seat of a non-driver passenger. ### Claim 18 A system for controlling at least one adjustable component of a vehicle, the system comprising: an adjustment control system that controls at least one positioning actuator in response to an instruction to adjust the at least one adjustable component; an occupancy detection system that detects one or more personal mobile devices in the vehicle to determine a current occupancy configuration; and a group identity database that applies a machine learning model trained to: predict a current group identity profile corresponding to the current occupancy configuration, wherein the current group identity profile includes occupancy information corresponding to a number of occupants in the vehicle and an identity of at least one occupant of the vehicle, wherein the current group identity profile is predicted based on another group identity profile having at least one characteristic similar to the occupancy data; and determine, based on the current group identity profile, target position data corresponding to a target position for the at least one adjustable component; and at least one controller: that receives, from the group identity database, the target position data for the at least one adjustable component; and that communicates, via the adjustment control system, the instruction to position the at least one adjustable component toward the target position based on the target position data. ### Claim 19 (depends on 18) The system for controlling at least one adjustable component of the vehicle of claim 18, wherein the machine learning model is further trained to: determine anxiety data corresponding to a projected anxiety of the at least one occupant based on the occupancy information, wherein determining the target position data is further based on the anxiety data.