CPC G05D 1/0022 (2013.01) [B60W 40/08 (2013.01); G01C 21/3438 (2013.01); G01C 21/3461 (2013.01); G01C 21/3469 (2013.01); G01C 21/3617 (2013.01); G05B 13/027 (2013.01); G05D 1/0088 (2013.01); G05D 1/0212 (2013.01); G05D 1/0287 (2013.01); G06F 40/40 (2020.01); G06N 3/045 (2023.01); G06N 3/0418 (2013.01); G06N 3/08 (2013.01); G06N 3/086 (2013.01); G06N 20/00 (2019.01); G06Q 30/0208 (2013.01); G06Q 50/188 (2013.01); G06Q 50/30 (2013.01); G06V 20/59 (2022.01); G06V 20/64 (2022.01); G07C 5/006 (2013.01); G07C 5/008 (2013.01); G07C 5/02 (2013.01); G07C 5/08 (2013.01); G07C 5/0808 (2013.01); G07C 5/0816 (2013.01); G10L 15/16 (2013.01); G10L 25/63 (2013.01); B60W 2040/0881 (2013.01); G05D 2201/0213 (2013.01); G06N 3/02 (2013.01); G06Q 30/0281 (2013.01); G06Q 50/01 (2013.01)] | 25 Claims |
1. A system for transportation, comprising:
an artificial intelligence system for processing a sensory input from one or more sensors in a vehicle to determine an emotional state of a rider in the vehicle and optimizing an operating parameter of the vehicle to improve the emotional state of the rider;
wherein the artificial intelligence system includes:
a recurrent neural network configured to indicate a change in the emotional state of the rider in the vehicle by a recognition of patterns of emotional state indicative sensor data from the one or more sensors that monitor the rider, wherein the patterns are indicative of at least one of a first degree of a favorable emotional state of the rider or a second degree of an unfavorable emotional state of the rider, and wherein the recurrent neural network has one or more perceptrons that mimic human senses to facilitate a determination of the emotional state of the rider based on an extent to which at least one sense of the rider is stimulated; and
a radial basis function neural network configured to optimize, for achieving a target emotional state of the rider, the operating parameter of the vehicle in response to the indication of the change in the emotional state of the rider.
|