A method for monitoring operation of at least one electrical load for a vehicle. A comparison of an actual value of an operating parameter with four threshold values is performed. A monitoring signal is also generated dependent on a result of the comparison, the monitoring signal being generated with a first signal characteristic if the actual value lies between the first threshold value and the third threshold value or between the second threshold value and the fourth threshold value, or being generated with a second signal characteristic if the actual value lies above the third threshold value or below the fourth threshold value. The first signal characteristic effects activation of at least one safety function that maintains an active operating state of the at least one electrical load. The second signal characteristic effects deactivation of the at least one electrical load.

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 for fault detection is adapted for a vehicle display fault detection system. The vehicle display fault detection system includes a vehicle system and a display system. The method for fault detection includes following steps: detecting whether a first state of the display system is abnormal or not; when the first state is abnormal, the display system is configured to generate a fault detection signal; classifying to generate a control signal according to the fault detection signal; and adjusting the first state of the display system to a second state.

An embodiment system for mild hybrid starter and generator (MHSG) failure diagnosis of a mild hybrid vehicle includes a data detection part configured to detect data for determining whether to activate a catalyst, and a controller configured to determine whether there is an MHSG failure using a deviation between a required torque and an actual operating torque of an MHSG after determining whether catalyst activation is needed and whether to start a stage of the MHSG failure diagnosis based on the data detected by the data detection part.

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.

Systems and methods are disclosed with respect to using a blockchain for managing the subrogation claim process related to a vehicle accident, in particular, determining fault as part of the subrogation process. An exemplary embodiment may include receiving an electronic notification of a vehicle collision; receiving sensor data (such as telematics, image, audio, vehicle operational, or other sensor data) related to the vehicle collision; determining a percentage of fault of the vehicle collision for one or more vehicles, vehicle systems, and/or drivers based upon, at least in part, analysis of the sensor data collected; and creating a blockchain for the vehicle collision with one or more links to the sensor image data and an indication of the percentage of fault(s) determined to facilitate blockchain-based claim handling.

In one aspect, an example method includes (a) determining, via a thermal conductivity sensor of an automobile damage detection device, one or more thermal conductivities at one or more locations on an automobile; (b) transmitting, via a network interface of the automobile damage detection device, a request for anticipated thermal conductivity data from an automobile claims system, wherein the anticipated thermal conductivity data corresponds to anticipated thermal conductivities at the one or more locations on the automobile; (c) in response to transmitting the request, receiving, via the network interface from the automobile claims system, the anticipated thermal conductivity data; and (d) in response to receiving, from the automobile claims system, the anticipated thermal conductivity data, displaying, via a graphical user interface, a graphical representation of the determined one or more thermal conductivities and the anticipated thermal conductivity data.

A method and a device for providing an operating state of a sensor of a vehicle. The method includes detecting first environment data values using the sensor, the first environment data values representing an environment of the vehicle, receiving second environment data values, which represent the environment of the vehicle, the second environment data values being detected by an infrastructure sensor system, determining the operating state of the sensor as a function of the first and the second environment data values, and providing the operating state of the sensor.

A method of controlling an autonomous vehicle and an electronic device are provided, which relate to a field of artificial intelligence technology, and in particular to a field of autonomous driving technology. The method includes: acquiring a vehicle state configuration information from a cloud; enabling a task receiving function of the vehicle, in response to the vehicle state configuration information indicating that the vehicle is in an automatic operation state; acquiring a task information from the cloud in response to the task receiving function being enabled; and controlling the vehicle according to the task information.