A method of executing a charging plan for at least one vehicle in a transportation system includes: receiving, at a charging infrastructure control system, operational state and energy consumption information for a plurality of network-enabled vehicles; predicting a geolocation of one or more vehicles of the plurality of network-enabled vehicles in a geographic region; allocating the one or more vehicles of the plurality of network-enabled vehicles to charging infrastructure in the geographic region; and optimizing, at an artificial intelligence system, a parameter of the charging plan based on the prediction of the geolocation of the one or more vehicles in the geographic region.

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 a movement sensor to detect physical actions of the vehicle occupant. The transportation system further includes a real-time control system to receive and process the data to determine an emotional state of the occupant based on the detected physical actions 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.

A method of optimizing a state of a rider of a vehicle. The method includes: receiving data from a wearable sensor worn by the rider of the vehicle indicative of an emotional state of the rider; comparing the data received from the wearable sensor to stored wearable sensor data in which quantitative patterns present in the stored sensor data are labelled as emotional states; determining a pattern of an emotional state based on the data received from the wearable sensor and the comparison to the stored wearable sensor data; detecting a change in emotional state of the rider based on a detected change in the data received from the wearable sensor indicative of a change in the emotional state of the rider; and adjusting an operational parameter of the vehicle in real time in response to the detected change in the emotional state of the rider.

A system may collect human operator interactions with a vehicle control system interface operatively connected to a vehicle, and may collect vehicle response and operating conditions associated at least contemporaneously with the human operator interaction. Environmental information is collected contemporaneously with the human operator interaction. An artificial intelligence system is trained to control the vehicle with an optimized margin of safety while mimicking the human operator, the training including instructing the artificial intelligence system to take input from an environment data collection module about instances of environmental information associated with the contemporaneously collected vehicle response and operating conditions, where the optimized margin of safety is achieved by training the artificial intelligence system to control the vehicle based on a set of human operator interaction data collected from interactions of an expert human vehicle operator and a set of outcome data from a set of vehicle safety events.

A system may receive social data from a plurality of social data sources. A system may process the social data using semantic analysis to detect keywords in the social data indicative of a group transportation need. A system may identify a plurality of individuals who share a group transportation need. A system may predict the group transportation need using a neural network trained to predict transportation needs based on the detected keywords. A system may provide a transportation recommendation based on the prediction.

A method of altering an operating state of a transportation system may include: receiving social data from a plurality of social data sources about at least one occupant of a vehicle of the transportation system; analyzing, at a first neural network, the social data and associating the social data with a route plan for the vehicle occupied by the at least one occupant; predicting, by the first neural network, an effect on a satisfaction of the at least one occupant based on the route plan of the vehicle through an analysis of the social data; and altering, by the first neural network, a route plan of the transportation system responsive to the predicted effect.

A system for improving a state of a rider in a vehicle includes at least one Internet-of-Things (IoT) device and an artificial intelligence system. The at least one IoT device in disposed in the environment of the vehicle, the at least one IoT device to sense and output data based on at least one of: a state of the rider, a state of the vehicle environment, or a state of the vehicle. The artificial intelligence system for processing the data output by the at least one IoT device to determine a determined state of the vehicle and to improve the at least one operating parameter of the vehicle to improve the state of the rider based on the determined state of the vehicle.

A method of operating a vehicle in a transportation system includes: receiving data collected for each of a set of users based on interactions of the set of users with a user interface of the vehicle including at least one of a vehicle data system, a vision system, and a connected system; performing robotic process automation on the interactions; learning changes in driving style using an artificial intelligence system based on the robotic process automation; and undertaking an action within the vehicle on behalf of the user based on the learned changes in driving style.

A system may include an artificial intelligence system for processing data output by at least one Internet-of-Things device associated with the vehicle, wherein the at least one Internet-of-Things device is configured to sense and output data based on at least one of: a state of the rider, a state of the vehicle environment, or a state of the vehicle, and wherein the artificial intelligence system is configured to determine a determined state of the vehicle and to adjust the at least one operating parameter of the vehicle to improve the state of the rider based on the determined state of the vehicle.

An information sharing system with a display screen and a network computing system is disclosed. The display screen may be capable of either being manually moved by a person or move automatically under its own power. The apparatus also includes a power system, a communication subsystem, a memory and a computing device. The communication subsystem communicates with the computing device, the network computing system, and the memory. The network computing system has an end-user display screen. The network computing system is configured to receive media and media secondary information, associate the media and media secondary information to a unique identifier, and show the media and the unique identifier on the display screen. The networking computing system is further configured to receive the unique identifier and an end-user account, and then show the media secondary information on the end-user display screen.