Provided herein is a computer system for creating driving challenges for drivers. The computer system may include a processor in communication with a memory device, and the processor may be programmed to: (i) receive driving data associated with a driver, (ii) generate a first model that models the driving data associated with the driver, (iii) calculate a predicted driving score for the driver based at least in part upon the first model, (iv) generate a second model that predicts a confidence of the predicted driving score, (v) calculate a confidence value of the predicted driving score, wherein the confidence value is a squared error of the predicted driving score, and (vi) generate at least one driving challenge for the driver based at least in part upon the predicted driving score and the confidence value for that predicted driving score.

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.

An update management apparatus for a vehicle includes: a first cooperative controller configured to first determine whether a vehicle controller is updatable based on a state of a low-voltage battery at a predetermined interval during vehicle driving; a management controller configured to receive a first determination result from the first cooperative controller, and when the vehicle controller is updatable, to request user approval during ignition-off of the vehicle, to update the vehicle controller; and a second cooperative controller configured to display an approval window for the user approval.

An update management apparatus for a vehicle includes: a first cooperative controller configured to first determine whether a vehicle controller is updatable based on a state of a low-voltage battery at a predetermined interval during vehicle driving; a management controller configured to receive a first determination result from the first cooperative controller, and when the vehicle controller is updatable, to request user approval during ignition-off of the vehicle, to update the vehicle controller; and a second cooperative controller configured to display an approval window for the user approval.

Computing systems for vehicle diagnostics are provided. In accordance with some aspects, a computing system may receive, from a vehicle (e.g., from a computing device installed in and/or at the vehicle), a diagnostic code generated by an on-board diagnostic (OBD) system of the vehicle. The computing system may determine an issue with the vehicle based on the diagnostic code and may determine, based on the issue, a remedial action for addressing the issue and a timeframe for performing the remedial action. The computing system may store data identifying the issue, the remedial action, and the timeframe in a record associated with the vehicle.

Provided is a notification control apparatus for a vehicle configured to determine, based on surrounding information and an operation state of an operation unit, whether there exists a possibility that an own vehicle turns toward a specific direction while an oncoming vehicle is approaching, to determine, when affirmative determination is made, based on vehicle information including at least one of a steering input value or presence/absence of a brake operation and a vehicle speed, whether a possibility that the own vehicle completes crossing of an opposing lane or an intersection after elapse of a reference period is high, and when affirmative determination is made, to execute the notification control when a virtual passing period required for the own vehicle to virtually pass the oncoming vehicle is a lower limit period or longer and an upper limit period or shorter, the upper limit period being the reference period or shorter.

Provided is a notification control apparatus for a vehicle configured to determine, based on surrounding information and an operation state of an operation unit, whether there exists a possibility that an own vehicle turns toward a specific direction while an oncoming vehicle is approaching, to determine, when affirmative determination is made, based on vehicle information including at least one of a steering input value or presence/absence of a brake operation and a vehicle speed, whether a possibility that the own vehicle completes crossing of an opposing lane or an intersection after elapse of a reference period is high, and when affirmative determination is made, to execute the notification control when a virtual passing period required for the own vehicle to virtually pass the oncoming vehicle is a lower limit period or longer and an upper limit period or shorter, the upper limit period being the reference period or shorter.