Vehicle manipulation using occupant image analysis
Vehicle manipulation is performed using occupant image analysis. A camera within a vehicle is used to collect cognitive state data including facial data, on an occupant of a vehicle. A cognitive state profile is learned, on a first computing device, for the occupant based on the cognitive state data. The cognitive state profile includes information on absolute time. The cognitive state profile includes information on trip duration time. Voice data is collected and the cognitive state data is augmented with the voice data. Further cognitive state data is captured, on a second computing device, on the occupant while the occupant is in a second vehicle. The further cognitive state data is compared, on a third computing device, with the cognitive state profile that was learned for the occupant. The second vehicle is manipulated based on the comparing of the further cognitive state data.
1. A computer-implemented method for vehicle manipulation comprising:
collecting, using a camera within a vehicle, cognitive state data including facial data, on an occupant of a vehicle;
learning, on a first computing device, a cognitive state profile for the occupant based on the cognitive state data;
capturing, on a second computing device, further cognitive state data on the occupant while the occupant is in a second vehicle;
comparing, on a third computing device, the further cognitive state data with the cognitive state profile that was learned for the occupant; and
manipulating the second vehicle based on the comparing of the further cognitive state data.
2. The method of claim 1 wherein the cognitive state profile includes information on absolute time.
3. The method of claim 2 wherein the absolute time includes time of day, day of week, day of month, or time of year information.
4. The method of claim 1 further comprising collecting voice data and augmenting the cognitive state data with the voice data.
5. The method of claim 4 wherein the voice data includes audio data.
6. The method of claim 4 further comprising evaluating the voice data for timbre, prosody, vocal register, vocal resonance, pitch, loudness, speech rate, or language content.
7. The method of claim 4 wherein the augmenting is based on lexical analysis of the voice data that looks at sentiment.
8. The method of claim 4 wherein the voice data includes non-speech vocalizations.
9. The method of claim 8 wherein the non-speech vocalizations include grunts, yelps, squeals, snoring, sighs, laughter, filled pauses, unfilled pauses, or yawns.
10. The method of claim 1 wherein the occupant is a passenger within the vehicle.
11. The method of claim 10 wherein the vehicle is an autonomous vehicle.
12. The method of claim 1 wherein the vehicle is a semi-autonomous vehicle.
13. The method of claim 1 further comprising performing facial recognition on the occupant.
14. The method of claim 13 further comprising using the cognitive state profile across a fleet of vehicles.
15. The method of claim 1 wherein the vehicle and the second vehicle are a same vehicle.
16. The method of claim 1 wherein the vehicle and the second vehicle are different vehicles.
17. The method of claim 1 wherein the vehicle and the second vehicle are part of a fleet of vehicles.
18. The method of claim 1 wherein the manipulating includes a locking out operation; recommending a break for the occupant; recommending a different route; recommending how far to drive; responding to traffic; adjusting seats, mirrors, climate control, lighting, music, audio stimuli, interior temperature for the second vehicle; brake activation; or steering control.
19. The method of claim 1 wherein the manipulating is based on a make for the second vehicle, a vehicle class for the second vehicle, tires for the second vehicle, a weather pattern, and a traffic pattern.
20. The method of claim 1 further comprising capturing cognitive state data on a second occupant and manipulating the second vehicle based on the cognitive state data for the occupant and the cognitive state data for the second occupant.
21. The method of claim 1 further comprising comparing the further cognitive state data with additional cognitive state profiles learned from additional occupants of additional vehicles.
22. The method of claim 21 wherein the additional cognitive state profiles are selected based on demographics of the occupant.
23. The method of claim 21 wherein the additional cognitive state profiles are selected based on characteristics of the vehicle of the occupant.
24. The method of claim 21 wherein the additional cognitive state profiles are selected based on a route being travelled.
25. A computer program product embodied in a non-transitory computer readable medium for vehicle manipulation, the computer program product comprising code which causes one or more processors to perform operations of:
collecting, using a camera within a vehicle, cognitive state data including facial data, on an occupant of a vehicle;
learning a cognitive state profile for the occupant based on the cognitive state data;
capturing further cognitive state data on the occupant while the occupant is in a second vehicle;
comparing the further cognitive state data with the cognitive state profile that was learned for the occupant; and
manipulating the second vehicle based on the comparing of the further cognitive state data.
26. A computer system for vehicle manipulation comprising:
a memory which stores instructions;
one or more processors attached to the memory wherein the one or more processors, when executing the instructions which are stored, are configured to:
collect, using a camera within a vehicle, cognitive state data including facial data, on an occupant of a vehicle;
learn a cognitive state profile for the occupant based on the cognitive state data;
capture further cognitive state data on the occupant while the occupant is in a second vehicle;
compare the further cognitive state data with the cognitive state profile that was learned for the occupant; and
manipulate the second vehicle based on the comparing of the further cognitive state data.