A defibrillation system may include a cardiac arrest detector detecting whether cardiac arrest of a passenger has occurred in a state of taking a seat of a self-driving vehicle and fastening a seatbelt of the vehicle; a passenger posture detection device detecting a posture of the passenger; a seat driving device changing the posture of the passenger into another posture in which the passenger lies down based on a detection signal of the passenger posture detection device when the cardiac arrest of the passenger occurs; a heart position detector configured to search for a position of a heart of the passenger; a defibrillation robot to perform a CPR method or a method using an AED on the heart of the passenger; and a controller controlling operation of the seat driving device, the heart position detector, and the defibrillation robot based on detection signals of the cardiac arrest detector and the passenger posture detection device.

This document discloses methods of acquiring a 3D map of an area with multiple heights. The 3D map may include tiles, each of which provides ground height information for one or more of the plurality of levels. A grid corresponding to the 3D map is generated. The grid may divide each of the plurality of tiles into a plurality of cells, The grid may include: (a) a unique index assigned to each of the plurality of cells, in which the unique index is convertible to an index of a tile of the 3D map in which that cell is included, and (b) a plurality of gridlets associated with each of the plurality of cells, wherein a number of the plurality of gridlets associated with a cell is equal to a number of height levels represented by a tile of the 3D map in which that cell is included.

A vehicular driving assist system includes an electronic control unit (ECU). When the equipped vehicle is driving in the autonomous mode, driving of the vehicle is controlled by the ECU without human intervention. When the vehicle is being driven in a non-autonomous mode, a particular driver at least partially drives the vehicle. The vehicular driving assist system learns a driving style of the particular driver and, when the vehicle is being driven in the non-autonomous mode by the particular driver, the system restricts learning of the driving style of the particular driver responsive to determination by the system that the particular driver is (i) driving the vehicle erratically and/or (ii) performing an illegal driving maneuver. When the vehicle is driving in the autonomous mode, and responsive to the particular driver being present in the vehicle, the vehicle drives in accordance with the learned driving style of the particular driver.

A pacification method based on emotion recognition, includes: acquiring at least one of a voice and an image of a user; determining whether the user has abnormal emotion, according to the at least one of the voice and the image of a user; and in response to the user having abnormal emotion, determining a pacification manner according to the emotion of the user, and performing emotional pacification on the user. An apparatus, a device and a storage medium are also provided.

A rider state modification system for improving a state of a rider in a vehicle includes a first neural network that operates to classify a state of the vehicle through analysis of information about the vehicle captured by an Internet-of-things device during operation of the vehicle. The rider state modification system further includes a second neural network that operates to optimize at least one operating parameter of the vehicle based on the classified state of the vehicle, information about a state of a rider occupying the vehicle, and information that correlates vehicle operation with an effect on rider state.

A stopping position control device according to an embodiment includes a sitting position specifying unit configured to specify a sitting position of a user who gets off a vehicle next, the vehicle being subjected to automatic driving control, and a stopping position determination unit configured to determine a stopping position of the vehicle, at which the user gets off the vehicle, corresponding to the sitting position of the user.

A system for transportation includes a vehicle interface for gathering physiological sensed data of a rider in the vehicle. The system includes an artificial intelligence-based circuit that is trained on a set of outcomes related to rider in-vehicle experience and that induces, responsive to the sensed rider physiological data, variation in one or more of the user experience parameters to achieve at least one desired outcome in the set of outcomes. The inducing variation includes control of timing and extent of the variation.

A system for controlling a remote smart parking assist (RSPA) system is provided. The system includes an engine control unit (ECU) that is configured to operate an engine and an RSPA controller that is configured to receive vehicle state information from the ECU regarding whether or not a vehicle system error occurs and, if an error occurs, whether or not the error is an error in which a vehicle is possible to be driven. The RSPA controller is further configured to transmit torque request information to the ECU when the vehicle system error is an error in which the vehicle is possible to be driven.

A control device of a vehicle is provided. The device controls travelling of the vehicle such that the vehicle follows another vehicle based on information received from the other vehicle; and determines whether to allow the vehicle to start to follow another vehicle based on at least one of whether a user of the vehicle is inside the vehicle or an instruction from the user. The processor starts to follow another vehicle in a case where the travel control circuit is allowed to follow the other vehicle.

A system for sorting event data includes an interface and a processor. The interface is configured to receive a small set of video frame data from a vehicle event recorder. The processor is configured to determine that the small set of video frame data indicates to fetch more vehicle event recorder data; determine a categorization based at least in part on the more vehicle event recorder data; and in response to the categorization, route the more vehicle event recorder data to a reviewing queue.