TRANSPORTATION SYSTEM TO OPTIMIZE AN OPERATING PARAMETER OF A VEHICLE BASED ON A PHYSIOLOGICAL STATE OF AN OCCUPANT OF THE VEHICLE DETERMINED FROM IMAGES OF A FACE OF THE OCCUPANT
A transportation system to optimize an operating parameter of a vehicle based on a physiological state of an occupant of the vehicle. The transportation system includes a sensor to sense a physiological condition of the occupant and to output data based on the sensed physiological condition. The sensor includes an image capturing device to capture a set of images of a face of the occupant, and an image processing system to produce feature vectors from the set of images. The feature vectors are indicative of an emotional state of the occupant. The transportation system further includes an artificial intelligence system to receive and processes the data to determine an emotional state of the occupant and to optimize, for achieving a favorable emotional state of the occupant, at least one operating parameter of the vehicle in response to the detected emotional state of the occupant.
1 . A transportation system that optimizes an operating parameter of a vehicle based on a physiological state of an occupant of the vehicle, the transportation system comprising:
a sensor that senses a physiological condition of the occupant and that outputs data based on the sensed physiological condition, the sensor including:
an image capturing device that captures a set of images of a face of the occupant; and
an image processing system that produces feature vectors from the set of images, the feature vectors indicative of an emotional state of the occupant; and
an artificial intelligence system that receives and processes the data to determine the emotional state of the occupant and that optimizes, for achieving a favorable emotional state of the occupant, at least one operating parameter of the vehicle in response to the determined emotional state of the occupant.
2 . The transportation system of claim 1 wherein the artificial intelligence system further comprises a first neural network that detects the emotional state of the occupant through recognition of patterns of the feature vectors from the set of images.
3 . The transportation system of claim 2 wherein the first neural network is configured to classify patterns of the feature vectors and to associate the patterns of the feature vectors with emotional states and changes thereto from a training data set.
4 . The transportation system of claim 3 wherein the training data set is sourced from at least one of a stream of data from unstructured data sources, social media sources, wearable devices, in-vehicle sensors, an occupant helmet, an occupant headgear, and an occupant voice system.
5 . The transportation system of claim 2 wherein the feature vectors are indicative of at least one of: the favorable emotional state of the occupant or an unfavorable emotional state of the occupant.
6 . The transportation system of claim 5 wherein the artificial intelligence system further comprises a second neural network that optimizes the at least one operating parameter in response to the determined emotional state for achieving the favorable emotional state of the occupant.
7 . The transportation system of claim 2 , wherein the feature vectors include at least one of: the emotional state of the occupant is changing, the emotional state of the occupant is stable, a rate of change of the emotional state of the occupant, a polarity of change of the emotional state of the occupant, or the emotional state of the occupant is changing to one of an unfavorable state or a favorable state.
8 . The transportation system of claim 1 wherein the at least one operating parameter is adjusted based on a correlation between the emotional state of the occupant and a vehicle operational state.
9 . The transportation system of claim 8 , wherein the at least one operating parameter includes at least one of: a vehicle route, an in-vehicle audio content, a vehicle speed, a proximity to objects along a route, a proximity to other vehicles along the route, or an operation of a powertrain component of the vehicle.
10 . The transportation system of claim 1 wherein the image capturing device captures the set of images from a plurality of perspectives and wherein the image processing system produces the feature vectors from the set of images captured from the plurality of perspectives.
11 . A method of optimizing an operational parameter of a vehicle based on a physiological state of an occupant of the vehicle, the method comprising:
sensing a physiological condition of the occupant and outputting data based on the sensed physiological condition, wherein the sensing includes:
capturing, at an image capturing device, a set of images of a face of the occupant; and
producing, at an image processing system, feature vectors from the set of images, the feature vectors indicative of an emotional state of the occupant;
receiving and processing, at an artificial intelligence system, the data;
determining the emotional state of the occupant based on the processed data; and
optimizing at least one operating parameter of the vehicle in response to the determined emotional state of the occupant for achieving a favorable emotional state of the occupant.
12 . The method of claim 11 , further comprising:
detecting, at a first neural network, the emotional state of the occupant through recognition of patterns of the feature vectors from the set of images.
13 . The method of claim 12 , further comprising:
classifying, at the first neural network, patterns of the feature vectors; and associating the patterns of the feature vectors to emotional states and changes thereto from a training data set.
14 . The method of claim 13 wherein the training data set is sourced from at least one of a stream of data from unstructured data sources, social media sources, wearable devices, in-vehicle sensors, an occupant helmet, an occupant headgear, and an occupant voice system.
15 . The method of claim 12 wherein the feature vectors are indicative of at least one of: the favorable emotional state of the occupant or an unfavorable emotional state of the occupant.
16 . The method of claim 15 , further comprising:
optimizing, at a second neural network, the at least one operating parameter in response to the determined emotional state for achieving the favorable emotional state of the occupant.
17 . The method of claim 12 wherein the feature vectors include at least one of: the emotional state of the occupant is changing, the emotional state of the occupant is stable, a rate of change of the emotional state of the occupant, a polarity of change of the emotional state of the occupant, or the emotional state of the occupant is changing to one of an unfavorable state or a favorable state.
18 . The method of claim 11 wherein the at least one operating parameter is adjusted based on a correlation between the emotional state of the occupant and a vehicle operational state.
19 . The method of claim 18 , wherein the at least one operating parameter includes at least one of: a vehicle route, an in-vehicle audio content, a vehicle speed, a proximity to objects along a route, a proximity to other vehicles along the route, or an operation of a powertrain component of the vehicle.
20 . The method of claim 11 wherein capturing the set of images comprises capturing the set of images from a plurality of perspectives and wherein producing the feature vectors from the set of images comprises producing the feature vectors from the set of images captured from the plurality of perspectives.