Disclosed is a method for controlling a display of a vehicle and an electronic device therefor, the method including acquiring display configuration information related to multiple displays in a vehicle, identifying an access right to access a target display which is at least two of the multiple displays, based on the display configuration information, acquiring first source information, generating second source information to be displayed on the target display, from the first source information based on the access right, and controlling to transmit the second source information to the target display.

A method of pairing a sensor node of a transport refrigeration system with a coordinator node using an assisting device in a communication network is provided, the method includes: the assisting device obtains identification information of the sensor node; the assisting device connects with the coordinator node; the assisting device transmits the identification information of the sensor node to the coordinator node for the coordinator node to pair with the sensor node; the assisting device receives pairing status of the sensor node and the coordinator node; and the assisting device indicates the pairing status.

A smart device display for an autonomous vehicle, comprising a first display section that displays an external view of the autonomous vehicle, a second display section that displays vehicle actions that the autonomous vehicle will take and a third display section that displays alternative vehicle actions that an authorized passenger of the autonomous vehicle may select to override the vehicle actions. Such system can also comprise an artificial intelligence module that learns the alternative vehicle actions the authorized passenger selects in various intervention situations, wherein the artificial intelligence module uses machine learning algorithms to decide the best alternative vehicle actions that the authorized passenger is likely to select for similar future situations.

A method to determine a function and status of a human machine interface, HMI, of a vehicle is provided. The method includes receiving, by a processor device of a computing system, a captured image of at least one mechanically actuatable HMI of the vehicle. The method includes determining a target mechanically actuatable HMI of the vehicle in the captured image. The method includes obtaining HMI information about the target mechanically actuatable HMI. The method includes determining, from the vehicle, a current mechanical actuation status of the target mechanically actuatable HMI. The method includes generating an augmented reality image having the HMI information and the current mechanical actuation status of the mechanically actuatable HMI. The method includes sending the augmented reality image to a display device.

The present disclosure provides systems and methods to obtain feedback descriptive of autonomous vehicle failures. In particular, the systems and methods of the present disclosure can detect that a vehicle failure event occurred at an autonomous vehicle and, in response, provide an interactive user interface that enables a human located within the autonomous vehicle to enter feedback that describes the vehicle failure event. Thus, the systems and methods of the present disclosure can actively prompt and/or enable entry of feedback in response to a particular instance of a vehicle failure event, thereby enabling improved and streamlined collection of information about autonomous vehicle failures.

A vehicle control device that controls a vehicle configured to transport a passenger to a destination by autonomous traveling, the vehicle control device includes a vehicle controller configured to control operation of the vehicle, an image display configured to display an image of a periphery of the destination to the passenger via an output device, and a getting-off position detector configured to detect a desired getting-off position designated by the passenger via an input device. The image shows a region where stopping is prohibited, and the vehicle controller is configured to cause the vehicle to stop at the desired getting-off position.

An information processing device includes a first communication unit configured to communicate with a first terminal device, a second communication unit configured to communicate with a second terminal device, and a controller configured to generate an abnormality detection signal when an abnormality is detected based on vehicle information on a vehicle, and determine a position of a user based on a communication state of the first terminal device and the second terminal device possessed by the user. The controller is configured to cause the first communication unit to transmit the abnormality detection signal to the first terminal device when the controller determines that the position of the user is included in a first region, and cause the second communication unit to transmit the abnormality detection signal to the second terminal device when the controller determines that the position of the user is included in a second region.

A vehicle includes a controller, programmed to responsive to detecting a speeding event, generate an alert factor and send an alert to at least one of an in-vehicle output device or an outside-vehicle output device based on the alert factor; and responsive to detecting a user failing to respond, increase the alert factor and send the alert for output based on the increased alert factor.

A vehicle includes a controller, programmed to responsive to detecting a speeding event, generate an alert factor and send an alert to at least one of an in-vehicle output device or an outside-vehicle output device based on the alert factor; and responsive to detecting a user failing to respond, increase the alert factor and send the alert for output based on the increased alert factor.

A method for providing safe-driving information via eyeglasses of a driver of a vehicle is provided. The method includes steps of: a safe-driving information analyzing device, (a) if a visual-dependent driving image, corresponding to a perspective of the driver, from a camera on the eyeglasses, acceleration information and gyroscope information from sensors are acquired, inputting the visual-dependent driving image into a convolution network to generate a feature map, and inputting the feature map into a detection network, a segmentation network, and a recognition network, to allow the detection network to detect an object, the segmentation network to detect lanes, and the recognition network to detect driving environment, inputting the acceleration information and the gyroscope information into a recurrent network to generate status information on the driver and (b) notifying the driver of information on a probability of a collision, lane departure information, and the driving environment, and giving a warning.