A system for transportation includes a vehicle having a user interface, and a robotic process automation system wherein a set of data is captured for each user in a set of users as each user interacts with the user interface, and wherein an artificial intelligence system is trained using the set of data to interact with the vehicle to automatically undertake actions with the vehicle on behalf of the user.

A system for transportation includes a vehicle having a user interface, and a robotic process automation system wherein a set of data is captured for each user in a set of users as each user interacts with the user interface, and wherein an artificial intelligence system is trained using the set of data to interact with the vehicle to automatically undertake actions with the vehicle on behalf of the user.

A method of optimizing an operating state of a vehicle includes classifying, using a first neural network of a hybrid neural network, social media data sourced from a plurality of social media sources as affecting a transportation system. The method further includes predicting, using a second neural network of the hybrid neural network, one or more effects of the classified social media data on the transportation system. The method further includes optimizing, using a third neural network of the hybrid neural network, a state of at least one vehicle of the transportation system, wherein the optimizing addresses an influence of the predicted one or more effects on the at least one vehicle.

A method of optimizing an operating state of a vehicle includes classifying, using a first neural network of a hybrid neural network, social media data sourced from a plurality of social media sources as affecting a transportation system. The method further includes predicting, using a second neural network of the hybrid neural network, one or more effects of the classified social media data on the transportation system. The method further includes optimizing, using a third neural network of the hybrid neural network, a state of at least one vehicle of the transportation system, wherein the optimizing addresses an influence of the predicted one or more effects on the at least one vehicle.

A method for deactivating an automated driving mode of a vehicle involves automatically terminating the automated driving mode if, due to a manual steering torque acting on the steering wheel of the vehicle, a system steering torque generated by a control system of an assistance system for automated driving mode in terms of amount is exceeded by a predetermined first value if at least one hand of a vehicle user is detected on the steering wheel of the vehicle, is exceeded by a predetermined second value if neither of the vehicle user's hands is detected on the steering wheel, or is exceeded by a predetermined third value if it is determined that the vehicle user is distracted from the driving situation, or if it is determined that there is a lateral collision risk for the vehicle and the manual steering torque of the vehicle user is acting in the direction of the collision risk.

A method for deactivating an automated driving mode of a vehicle involves automatically terminating the automated driving mode if, due to a manual steering torque acting on the steering wheel of the vehicle, a system steering torque generated by a control system of an assistance system for automated driving mode in terms of amount is exceeded by a predetermined first value if at least one hand of a vehicle user is detected on the steering wheel of the vehicle, is exceeded by a predetermined second value if neither of the vehicle user's hands is detected on the steering wheel, or is exceeded by a predetermined third value if it is determined that the vehicle user is distracted from the driving situation, or if it is determined that there is a lateral collision risk for the vehicle and the manual steering torque of the vehicle user is acting in the direction of the collision risk.

The present disclosure provides system and methods for a vehicle infotainment system (VIS) to monitor physiological parameters of occupants of a vehicle. The VIS also monitors vehicle operating parameters. The VIS is able to detect when an occupant is experiencing a physiological condition and correlates the physiological condition to one or more vehicle operating parameters. In response to detecting a physiological condition and to determining the correlation, the VIS causes an action to occur in order to mitigate the physiological condition and/or to seek assistance for the physiological condition.

The present disclosure provides system and methods for a vehicle infotainment system (VIS) to monitor physiological parameters of occupants of a vehicle. The VIS also monitors vehicle operating parameters. The VIS is able to detect when an occupant is experiencing a physiological condition and correlates the physiological condition to one or more vehicle operating parameters. In response to detecting a physiological condition and to determining the correlation, the VIS causes an action to occur in order to mitigate the physiological condition and/or to seek assistance for the physiological condition.

A method comprises receiving, at a vehicle system of a vehicle, sensor data from one or more sensors; detecting an object based on the sensor data; determining whether a dynamic map maintained by a remote computing device includes the detected object; upon determination that the dynamic map includes the detected object, determining a remaining time-to-live associated with the detected object based on data associated with the dynamic map; and transmitting data about the detected object to the remote computing device if the determined remaining time-to-live associated with the detected object is less than a predetermined threshold time.

A method comprises receiving, at a vehicle system of a vehicle, sensor data from one or more sensors; detecting an object based on the sensor data; determining whether a dynamic map maintained by a remote computing device includes the detected object; upon determination that the dynamic map includes the detected object, determining a remaining time-to-live associated with the detected object based on data associated with the dynamic map; and transmitting data about the detected object to the remote computing device if the determined remaining time-to-live associated with the detected object is less than a predetermined threshold time.