Embodiments described herein relate to predicting the utilization of electric vehicle (EV) charge points. Methods may include: receiving an indication of a plurality of candidate locations for EV charge points; determining static map features of the plurality of candidate locations; inputting the plurality of candidate locations and static map features into a machine learning model, where the machine learning model is trained on existing EV charge point locations, existing EV charge point static map features, and existing EV charge point utilization; determining, based on the machine learning model, a predicted utilization of an EV charge point at the plurality of candidate locations; and generating a representation of a map including the plurality of candidate locations, where candidate locations of the plurality of candidate locations are visually distinguished based on a respective predicted utilization of an EV charge point at the candidate locations.

Systems and methods for communicating information related to a wearable device are disclosed. Exemplary information includes audio information.

A processing apparatus includes a control unit. The control unit is configured to acquire facility information containing an advertisement or publicity on a facility located along a travel route that a vehicle is scheduled to travel or a facility located within a predetermined range from the travel route, and, while the vehicle is traveling along the travel route, process an image of a first facility associated with the facility information or an image of a second facility present around the first facility based on the facility information and display the image of the first facility or the image of the second facility on a display provided in the vehicle.

An approach is provided for providing mobility insight data related to shared vehicles for a point of interest (POI). The approach involves retrieving shared vehicle data for the POI. The shared vehicle data indicates one or more shared vehicle events that have occurred, that are occurring at a given time, or a combination thereof within a threshold proximity of the POI. The approach also involves processing the shared vehicle data to determine mobility insight data. The mobility insight data includes a shared vehicle usage pattern, a shared vehicle availability pattern, or a combination thereof under one or more contexts for travel to or from the POI. The approach further involves presenting the mobility insight data in a location-based user interface.

A method for assisting selection of an accommodation by an accommodation search system includes receiving user credentials from a user device; receiving trip parameters from the user device; determining a basic list of accommodations that correspond with the trip parameters; determining one or more factors that apply to each individual accommodation of the basic list of accommodations; applying a weight value to each of the one or more factors that apply to each individual accommodation of the basic list of accommodations; aggregating the weight values of the one or more factors that apply to each individual accommodation to determine an aggregate weighted score for each individual accommodation of the basic list of accommodations; sorting the basic list of accommodations into a sorted list of accommodations based on the aggregate weighted score for each individual accommodation; and providing the sorted list of accommodations to the user device for viewing by a user.

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

An apparatus and method for providing a layer-based service with improved information accessibility are disclosed, and the method for providing a layer-based service with improved information accessibility according to an embodiment of the present application includes the operations of obtaining manipulation information and interface information for a target service, building an accessible layer corresponding to the target service by improving information accessibility associated with a user interface and a user experience of the target service based on the manipulation information and the interface information, and providing the target service based on the accessible layer.

A vehicle provides information on a plurality of chargers that charge a battery mounted on the vehicle. The vehicle includes a navigation screen and an ECU. The ECU controls the navigation screen to show a map and to show a plurality of icons corresponding to the plurality of chargers at corresponding positions of the plurality of chargers on the map. The ECU controls the navigation screen to show the plurality of icons to allow identification of a charging type to which each of the plurality of chargers is adapted and magnitude of electric power that can be output under the charging type.

A method determines an anticipated occupation of charging points and a charging strategy for a specified route. The method provides traffic data which is representative for the current traffic density on the route specified. An anticipated occupation of charging points along the specified route can be determined on the basis of the traffic data. A charging strategy can be determined on the basis of the traffic data and the determined anticipated occupation of charging points. The provision of information regarding a charging strategy to a driver allows the time required for the specified route to be reduced.

A movement assistance device guides a user to a meeting location for meeting a vehicle. The movement assistance device calculates a first required time until the vehicle arrives at the meeting location, and a plurality of routes from the user's current location to the meeting location. The movement assistance device calculates a second required time for the user to arrive at the meeting location from the user's current location for each route. The movement assistance device then determines the route associated with the second required time as a route via which the vehicle could be met on time when a second required time is the same as or shorter than the first required time. The movement assistance device then causes the communication device to output information that indicates the route or routes determined to be the route or routes via which the vehicle could be met on time.