Abstract: A system comprises an image sensor with a field of view of an exterior of a vehicle; a human machine interface (HMI) in the vehicle arranged to display images based on data from the image sensor; and a first computer that includes a processor and a memory. The first computer is programmed to provide data from the image sensor to a machine learning program that outputs a bounding box around an object; cause the bounding box around the object to be displayed via the HMI; and transmit object data including an inputted label identifying the object to a second computer that is remote from the vehicle.

Abstract: A profile for an occupant is stored. The profile includes a plurality of clusters of sitting positions for the occupant in a seat and classifications of respective clusters as preferred or nonpreferred. Respective clusters are classified as preferred or nonpreferred based on sitting scores for the respective sitting positions in that cluster. A higher sitting score increases a likelihood of the classification being preferred. A series of pressure maps indicating a respective series of sitting positions of the occupant in the seat are received. The pressure maps include a current pressure map. One of the sitting positions is assigned to one of the clusters that is classified as preferred in response to the sitting score of that sitting position being greater than a threshold score. A physical configuration of the seat is adjusted in response to the current sitting position being in one of the clusters that is classified as nonpreferred.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to receive a series of pressure maps indicating a respective series of sitting positions of an occupant in a seat, wherein the pressure maps include a current pressure map; update a profile of the occupant based on the pressure maps, wherein the profile includes a plurality of clusters of sitting positions and classifications of the clusters as preferred or nonpreferred, and updating the profile includes sorting one of the sitting positions into one of the clusters that is classified as preferred in response to the occupant remaining in that sitting position for greater than a threshold time; and adjust a physical configuration of the seat in response to the current sitting position being in one of the clusters that is classified as nonpreferred.

Abstract: A system comprises an image sensor with a field of view of an exterior of a vehicle; a human machine interface (HMI) in the vehicle arranged to display images based on data from the image sensor; and a first computer that includes a processor and a memory. The first computer is programmed to provide data from the image sensor to a machine learning program that outputs a bounding box around an object; cause the bounding box around the object to be displayed via the HMI; and transmit object data including an inputted label identifying the object to a second computer that is remote from the vehicle.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to receive a series of pressure maps indicating a respective series of sitting positions of an occupant in a seat, wherein the pressure maps include a current pressure map; update a profile of the occupant based on the pressure maps, wherein the profile includes a plurality of clusters of sitting positions and classifications of the clusters as preferred or nonpreferred, and updating the profile includes sorting one of the sitting positions into one of the clusters that is classified as preferred in response to the occupant remaining in that sitting position for greater than a threshold time; and adjust a physical configuration of the seat in response to the current sitting position being in one of the clusters that is classified as nonpreferred.