Systems and methods for displaying corresponding content for vehicle services using a distributed set of electronic devices are provided. For example, a computer-implemented method includes obtaining data associated with a vehicle service instance. The vehicle service instance is associated with a request for a vehicle service for a user. The method includes determining, based on the data associated with the vehicle service instance, a first advertisement content item for a display device positioned on an exterior of a vehicle assigned to the vehicle service instance and a second advertisement content item for a user device associated with the vehicle service instance. The method includes communicating data that initiates the display of the first advertisement content item for the display device positioned on the exterior of the vehicle and data that initiates the display of the second advertisement content item for the user device.

An autonomous or semi-autonomous vehicle fleet comprising a plurality of autonomous or semi-autonomous vehicles for providing an assortment of items to a customer or a potential customer after such customer or potential customer summons the one or more autonomous or semi-autonomous vehicles in an unstructured open or closed environment. Each autonomous or semi-autonomous vehicle comprises one or more compartments configured to contain and secure the assortment of the items to be selected once the summoned autonomous or semi-autonomous vehicle arrives to a customer or potential customer.

A rider interface for a vehicle includes a data processor configured to facilitate communication between a rider using the rider interface and the vehicle, the vehicle and the rider interface communicating location and orientation of the vehicle. An augmented reality system with a display is disposed to facilitate presenting an augmentation of content in an environment of the rider using the rider interface, the augmentation responsive to a registration of the communicated location and orientation of the vehicle, wherein at least one parameter of the augmentation is determined by machine learning on at least one input relating to at least one of the rider and the rider interface.

A system for transportation includes a vehicle, a rider occupying the vehicle, and a hybrid neural network. The hybrid neural network includes a first neural network to process a sensor input corresponding to the rider to determine an emotional state of the rider, and a second neural network to optimize at least one operating parameter of the vehicle to improve the emotional state of the rider.

A system for transportation includes a vehicle occupied by a rider, an electronic commerce system of the vehicle, and an artificial intelligence system for processing data from an interaction of the rider with the electronic commerce system to classify a rider state and optimizing at least one operating parameter of the vehicle to improve the rider state.

A motorcycle helmet includes a data processor configured to facilitate communication between a rider wearing the helmet and a motorcycle, the motorcycle and the helmet communicating location and orientation of the motorcycle. An augmented reality system with a display is disposed to facilitate presenting an augmentation of content in an environment of a rider wearing the helmet, the augmentation responsive to a registration of the communicated location and orientation of the motorcycle At least one parameter of the augmentation is determined by machine learning on at least one input relating to at least one of the rider and the motorcycle.

A system for transportation includes a vehicle interface for gathering hormonal state data of a rider in the vehicle. The system further includes an artificial intelligence-based circuit that is trained on a set of outcomes related to rider in-vehicle experience and that induces, responsive to the sensed rider hormonal state data, variation in one or more of the user experience parameters to achieve at least one desired outcome in the set of outcomes. The set of outcomes includes at least one outcome that promotes rider safety. The inducing variation includes control of timing and extent of the variation.

A system for transportation includes a vehicle having at least one rider located in the vehicle and a data processing system for taking data from a plurality of social data sources. A hybrid neural network is connected to the data processing system. The system for transportation is to optimize satisfaction of the at least one rider based on processing the data from the plurality of social data sources with the hybrid neural network.

A transportation system includes an artificial intelligence (AI) system for processing a sensory input from a wearable device in a self-driving vehicle to determine an emotional state of a rider and optimizing a vehicle operating parameter to improve the rider emotional state. The AI system includes a recurrent neural network to indicate a change in the emotional state of the rider by a recognition of patterns of emotional state indicative wearable sensor data from a set of wearable sensors worn by the rider. The patterns are indicative of a first degree of a favorable emotional state of the rider and/or a second degree of an unfavorable emotional state of the rider. The AI system further includes a radial basis function neural network to optimize, for achieving a target emotional state of the rider, the vehicle operating parameter in response to the indication of the change in the rider emotional state.

A transportation system includes an artificial intelligence system for processing a sensory input from a wearable device in a self-driving vehicle to determine an emotional state of a rider and optimizing a vehicle operating parameter to improve the rider emotional state. The artificial intelligence system detects the rider emotional state in the self-driving vehicle by recognition of patterns of emotional state indicative data from a set of wearable sensors worn by the rider. The patterns are indicative of at least one of a favorable emotional state and an unfavorable emotional state of the rider. The artificial intelligence system is to optimize, for achieving at least one of maintaining a detected favorable emotional state of the rider and achieving a favorable emotional state of a rider subsequent to a detection of an unfavorable emotional state, the operating parameter of the vehicle in response to the detected emotional state of the rider.