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.

Aspects of the disclosure provide a computer-implemented method and system for the assignment of roadside assistance service providers such as tow trucks to distressed vehicles/drivers requiring roadside assistance. The methods and systems may include a roadside assistance service provider system with a collection module, an assignment module, and a feedback module. The collection module collects roadside assistance service provider information and historical statistics from real-world information and stores the information in a database that may then be analyzed using particular rules and formulas. The assignment module assigns particular roadside assistance service providers to particular distressed vehicles/drivers based on one or more characteristics. The feedback module may provide near real-time cues to the tow truck driver's mobile device, such as alerting when the amount of time spent on a task exceeds a predefined threshold, flagging high priority tasks/assignments, providing a step-by-step checklist for the repair.

The present technology relates to an information processing apparatus, an information processing method, and a program that allow a sensing time of a sensor to be easily and accurately determined. An information processing apparatus includes a control circuit that outputs a control signal for controlling a sensing timing of a sensor, a counter that updates a counter value in a predetermined cycle, and an addition circuit that adds, to sensor data output from the sensor, sensing time information including a first counter value, a second counter value, and a GNSS (Global Navigation Satellite System) time in a GNSS. The first counter value is obtained when the control signal is output from the control circuit, and the second counter value is obtained when a pulse signal synchronous with the GNSS time is output from a GNSS receiver. The present technology can be applied to, for example, a vehicle-mounted camera.

Systems and methods for an On-Demand Autonomy (ODA) service. The system includes a set of functional modules enabled for ODA service activities disposed in a follower vehicle (Fv) in communication with an ODA server that includes a user request module configured to receive request information from the Fv from the ODA server, and to process and communicate the request information to the schedule module; the schedule module configured to coordinate an arrival time information with the ODA server for pickup of the Fv based on the request information, and communicate the arrival time information to the schedule execution module; the schedule execution module configured to direct the Fv to a pickup point based on the arrival time information, and communicate the pickup point to the indication module; and the indication module configured to provide alerts to vehicles in the vicinity of the pickup of the Fv via the ODA service.

An apparatus for performing an over-the-air (OTA) update for a vehicle includes a display that displays at least one message for the OTA update of the vehicle, and a controller that generates the at least one message displayed based on at least one condition for the vehicle.

A supervisory control system is disclosed that provides an operator situational awareness interface use with monitoring a plurality of automated vehicles (AVs). The system is configured to: generate a map of a geographical area of interest; obtain location data and perceived risk data for a plurality of AVs in the geographical area; generate a vehicle icon corresponding to each AV; position the vehicle icon for each AV on the map based on the location data for a corresponding AV; apply a color coding to each vehicle icon based on a perceived risk level for a corresponding AV; and signal a display device to display an AV fleet map graphic that includes the color coded vehicle icons positioned on the map. The controller may be further configured to: generate an AV servicing queue graphic that displays vehicle icons in an order based on a determined servicing priority.

This disclosure is generally directed to systems and methods for providing a software sensor in a vehicle. In an example embodiment, a determination is made regarding the availability of a feature upgrade to a vehicle and a request may be made (to a cloud computer, for example), for obtaining the feature upgrade. The cloud computer provides an emulation software module based on emulating a first sensor that is unavailable in the vehicle. The feature upgrade may be installed in the vehicle by executing the emulation software module and by use of a second sensor that is available in the vehicle. In an example implementation, the second sensor available in the vehicle is a type of hardware sensor such as, for example, a camera, and the first sensor that is emulated is a different type of hardware sensor such as, for example, an air quality sensor.

A control apparatus includes a controller configured to acquire, based on whether a vehicle selected by a user has an accident history, at least one piece of change information indicating a change in performance of the vehicle before and after an accident and output the acquired change information.

The present invention provides a robust and effective solution to an entity or an organization by allowing to visualize the flow of automotive data signals from a source system to a sink system with different metric signals at each step and creating a mechanism for creating automotive signal quality marker (ASQM) for high quality automotive data signals by determining high value data parameters, inter-parameter correlation, data quality variation with trip duration, and frequency of data collection/distribution across datasets. The quality criterion thus developed is applied to data generated from a plurality of data sources. The ASQM may be calculated by converting the developed automotive data signals quality criterion into a numeric value on a specified scale. It can be used by all stakeholders in the value chain for consistent measurement of automotive data signals quality.