A system, method and non-transitory computer-readable medium for predicting a trip destination of a user based on user behavior learning are provided. Historical behaviors and a target behavior of the user are received from a feature processing layer, and the received historical behaviors and the target behavior are embedded with features including a time and a location to produce a context modeling layer. A user modeling layer is produced by embedding the context modeling layer. A trip destination is predicted based on historical trip data and target trip data in the user modeling layer.

A method, an apparatus and a computer program product for performing reactive ventilation or prevention operations to air pollution in a moving vehicle. The method comprises obtaining a driving path of the vehicle that comprises a future sub-path that the vehicle is expected to arrive to at a future time, an estimated time-window the vehicle is expected to be located thereon, and air pollution data of the driving path that comprises an air pollution level at the future sub-path. In response to predicting, based on the air pollution data and the driving path, that the vehicle is about to encounter air pollution at the future sub-path, a prevention action is performed prior to the vehicle reaching the future sub-path. In response to a determination that the estimated air pollution level is below a threshold, performing a ventilation action while the vehicle is located on the future sub-path.

An air-conditioning control system acquires settlement information on an electronic settlement performed by an occupant D of a vehicle using a mobile terminal via a car-navigation system from the mobile terminal having an electronic settlement function, and controls an air conditioner on the basis of the acquired settlement information. The settlement information includes a commodity purchased by the electronic settlement or a service having a value paid by the electronic settlement, as a settlement target.

Embodiments include a method for pre-conditioning a cabin of a vehicle, the method comprising: collecting, by a climate control system of the vehicle, a set of current conditions related to the vehicle; sending, by the climate control system of the vehicle, to a cloud-based climate control service, the collected set of current conditions related to the vehicle; receiving, by the climate control system of the vehicle from the cloud-based climate control service, a set of pre-conditioning instructions defining operation of the climate control system of the vehicle without input from a user of the vehicle and before the user enters the vehicle; and controlling, by the climate control system of the vehicle, a Heating, Ventilating, and Air Conditioning (HVAC) system of the vehicle based on the received pre-conditioning instructions.

An information processing device that provides a travel route to a destination to an occupant of a vehicle includes a controller. The controller is configured to acquire travel information obtained by another vehicle that travels on a candidate route to the destination set by the occupant from a second point in time prior to a first point in time when the destination is set to the first point in time in relation to traveling of the other vehicle, and to decide the travel route optimal for driving of the vehicle to the destination based on the acquired travel information.

A mechanism is provided for controlling the internal air-quality of a vehicle, including configuring a control policy that controls an internal air-quality of a vehicle and performing an action dictated by the control policy according to a window status of the vehicle.

A method for predicting an arousal level used by a computer of an arousal level prediction apparatus that predicts an arousal level of a user is provided. The method includes obtaining current biological information regarding the user detected by a sensor, and calculating a current arousal level of the user based on the current biological information. The method further includes obtaining current environment information indicating a current environment around the user, and predicting a future arousal level, which is an arousal level a certain period of time later, based on the current arousal level and the current environment information. Based on the predicted future arousal level, the method further issues a notification to the user, or controls an operation of a device.

A method for selecting an autonomous mobility-as-a-service (MAAS) vehicle is presented. The method includes transmitting, to a customer, location information of an autonomous MAAS vehicle within the customer's vicinity. The method also includes transmitting, to the customer, a compartment climate value corresponding to the autonomous MAAS vehicle. The method further includes selecting the autonomous MAAS vehicle based on the compartment climate value, such that the selected autonomous MAAS vehicle navigates to a location of the customer.

A system and method are described for providing an air quality alert to an occupant of a host vehicle. The system includes a communication unit adapted to be mounted in the host vehicle and configured to receive a wireless vehicle-to-x communication comprising an air quality value associated with a geographic area outside the host vehicle. The system also includes a controller adapted to be mounted in the vehicle and provided in communication with the communication unit. The controller is configured to generate an air quality alert control signal operative to provide an air quality alert to the occupant of the host vehicle based on a relationship of the air quality value to an air quality threshold value.

This disclosure describes vehicle climate control systems and methods for more intelligently controlling an occupant comfort level within a vehicle interior in a manner that minimizes energy usage of the vehicle. The climate control system may be automatically controlled in an economical mode (i.e., ECO mode) when certain vehicle conditions are met. For example, the decision to activate the ECO mode of the climate control system may be a function of one or more variables including, but not limited to, vehicle speed, vehicle speed differentials, ambient temperatures, temperature differentials, battery state of charge, predicted low battery state of charge, etc.