An embodiment takes the form of a system that obtains application-usage data from a personal mobile device of a vehicle operator of a vehicle. The application-usage data reflects a usage, during operation of the vehicle, of an application on the personal mobile device. The system identifies a vehicle feature, of the vehicle, that provides a vehicle functionality similar to an application functionality provided by the application on the personal mobile device, and performs a comparison of the obtained application-usage data with feature-usage data. The feature-usage data reflects a usage, during operation of the vehicle, of the identified vehicle feature. The system determines, based on the comparison, a usage preference for the application during operation of the vehicle over the identified vehicle feature.

A site recommendation method, an electronic device, and a readable storage medium are provided, which relate to the field of automatic driving. The method includes: determining, in response to a query request of a user terminal for a target position, a target site recommended to a target user within a specified range of the target position, wherein the target site includes a site that the target user is interested in under a specified travel condition; and sending the target site to the user terminal.

An information processing apparatus includes a controller. The controller determines, based on a preference of a user of a vehicle that enters a parking lot adjacent to a complex facility having a plurality of shops and a plurality of facility entrances, a shop to be used by the user from among the plurality of shops. The controller determines an entrance to be used by the user from among the plurality of facility entrances based on a position of the shop to be used, and outputs a position of the entrance to be used to the vehicle.

Example methods, apparatus, and articles of manufacture to capture and compress telematics data are disclosed herein. An example computer-implemented method, executed by a processor, to represent telematics data includes identifying, with the processor, a physical intersection of roads, identifying, with the processor, virtual lines crossing the roads, assigning, with the processor, ordinals to the virtual lines, representing, with the processor, a physical traversal through the physical intersection captured in first telematics data by a pair of the ordinals, and storing the pair of the ordinals in second compressed telematics data.

Embodiments of the present disclosure provide a method and apparatus for generating information. A method may include: determining, according to received positioning request information, visiting information for a target area of interest, the visiting information including location information of at least one visiting point; determining, according to the location information of the at least one visiting point, a visiting point distribution map including the at least one visiting point; performing grid division on the visiting point distribution map, to obtain a first grid map including at least one grid; and generating, based on the first grid map, outline information for the target area of interest.

A vehicle navigation apparatus is provided. The apparatus includes a vehicle sensor positioned in a front or a rear of a vehicle, the vehicle sensor configured to recognize surrounding information and road information of the vehicle, and a processor configured to identify destination information requested by a user of the vehicle, identify location information of the vehicle through the vehicle sensor, identify the recognized surrounding information and the recognized road information of the vehicle, and identify information about a route according to the identified destination information by controlling the vehicle to identify information about a bus station within a range specified based on the location information of the vehicle and bus information, calculating a degree of congestion of the route, and displaying the calculated degree of congestion through a display device.

The present disclosure provides methods, devices and systems for route deviation quantification and vehicular route learning based thereon. In some examples, there is provided a method for route deviation quantification of a suggested route. The method comprises: obtaining a ground truth route based on a filtered trajectory, the filtered trajectory including an inferred location of origin and an inferred location of destination; obtaining a suggested route generated based on the inferred location of origin and the inferred location of destination; quantifying a deviation of the suggested route from the ground truth route by calculating an off course ratio based on a combined length of road segments in the suggested route that are matched to corresponding road segments in the ground truth route and a combined length of road segments in the ground truth route.

A driving assistance device, including an automated driving switch; an emergency button; and a controller configured to provide either automated driving in which travel is performed along a current travel path of a host vehicle or automated stopping in response to manipulation by a driver of the automated driving switch or of the emergency button.

A method of generating a personalised recommendation of points of interest (POIs) for a user involves generating a route between an origin and a destination. A search area of a predetermined size is defined for each of a plurality of waypoints along the route. Personalisation data for the user is obtained from one or more social media websites. The POIs present within each search area are identified and descriptive data relating to attributes of each of the identified POIs is obtained. The POIs in each search area are then ranked based on at least a comparison of the personalisation data and the descriptive data relating to the respective POIs. A subset of the identified POIs is next selected for inclusion in the POI recommendation for each search area based on the determined ranking. A POI recommendation including the selected POIs is then displayed to the user.

Some embodiments of the invention provide a novel prediction engine that (1) can formulate predictions about current or future destinations and/or routes to such destinations for a user, and (2) can relay information to the user about these predictions. In some embodiments, this engine includes a machine-learning engine that facilitates the formulation of predicted future destinations and/or future routes to destinations based on stored, user-specific data. The user-specific data is different in different embodiments. In some embodiments, the stored, user-specific data includes data about any combination of the following: (1) previous destinations traveled to by the user, (2) previous routes taken by the user, (3) locations of calendared events in the user's calendar, (4) locations of events for which the user has electronic tickets, and (5) addresses parsed from recent e-mails and/or messages sent to the user. In some embodiments, the prediction engine only relies on user-specific data stored on the device on which this engine executes. Alternatively, in other embodiments, it relies only on user-specific data stored outside of the device by external devices/servers. In still other embodiments, the prediction engine relies on user-specific data stored both by the device and by other devices/servers.