An autonomous vehicle (AV) described herein is configured to receive a pull over location specified by a passenger, and is further configured to refine the pull over location based upon one or more factors, where the factors include computer-readable content from a profile of the passenger, sensor data output by sensor systems of the AV, observed or predicted weather conditions, observed or predicted traffic, and/or observations recently generated by other AVs that belong to the same fleet as the AV.

An apparatus comprising a processor and memory including computer program code, the memory and computer program code configured to, with the processor, enable the apparatus at least to: generate an indication of one or more communication network receiver upload zones for a road data gatherer along a planned route to be travelled by the road data gatherer, the indication determined according to a predetermined upload criterion, which takes account of the bandwidth capacities of communication network receivers along the planned route for the road data gatherer, to specify communication network receivers to be used by the road data gatherer for uploading of road data; and provide the indication to guide uploading of the road data gathered by the road data gatherer.

A terminal is disclosed. The terminal according to an embodiment of the present invention comprises: an output unit for outputting a notification; a storage unit for storing a database; a control unit for controlling the outputting of the notification; and an artificial intelligence unit for acquiring information regarding a user's context, and outputting a notification when the user's context corresponds to information included in the database, wherein the database includes at least one of a user's personal database, a standard activity database, and an accident type database.

Systems, methods, tangible, non-transitory computer-readable media, and devices for configuration of a vehicle compartment are provided. For example, a method can include receiving, by a computing system, occupancy data based in part on one or more states of one or more objects. Based in part on the occupancy data and compartment data, a compartment configuration can be determined for one or more compartments of an autonomous vehicle. The compartment data can be based in part on a state of the one or more compartments. The compartment configuration can specify one or more spatial relations of one or more compartment components associated with the one or more compartments. One or more configuration signals can be generated based in part on the compartment configuration to control the one or more compartments of the autonomous vehicle.

A method for controlling a charge transfer of an electric vehicle using an electric vehicle charging station, a mobile device, and a cloud server is disclosed. The method includes: receiving, at a mobile device, a message for an electric vehicle of a user from the electric vehicle charging station, wherein a user of the mobile device is associated with the electric vehicle to be charged; sending, from the mobile device, the message for the electric vehicle of the user to the cloud server, wherein the charge transfer request relayed from the mobile device includes identification information; in response to a charging control signal being authorized using identification information received from the mobile device, receiving the charging control signal from the cloud server at the mobile device to be forwarded to the electric vehicle charging station, wherein the charging control signal is configured to adjust a charging parameter at the electric vehicle charging station.

Techniques for determining a location and type of traffic-related features and using such features in route planning are discussed herein. The techniques may include determining that sensor data represents a feature such as a traffic light, road segment, building type, and the like. The techniques further include determining a cost of a feature, whereby the cost is associated with the effect of a feature on a vehicle traversing an environment. A feature database can be updated based on features in the environment. A cost of the feature can be used to update costs of routes associated with the location of the feature.

An autonomous electric vehicle comprises a battery electrically connected to the electric motor for powering the electric motor and a battery status prediction module to predict, based on event data from a mobile device of a user of the vehicle, whether the vehicle will be parked at a destination and a time period when the vehicle will be parked. The battery status prediction module predicts a predicted battery status at the end of the time period based on a temperature profile for the time period obtained from a remote weather server. The battery status prediction module determines if the predicted battery status at the end of the time period will have at least a minimum battery capacity to travel a distance to a charging station determined by the battery status prediction module from the destination and a location of the charging station.

An electronic device may include: a communication module comprising communication circuitry, a processor operatively coupled to the communication module, and a memory storing instructions operatively coupled to the processor. The instructions, when executed, may cause the processor to: obtain driving route traffic information of a first driving route of a vehicle connected to the electronic device, analyze the first driving route traffic information and determine a traffic event occurrence requiring a change in a driving route or a driving lane of the vehicle connected to the electronic device, based on the traffic event occurring, determine a severity level of the traffic event based on a driving time increase and an accident risk, and control a display device to display at least one of line change information, lane change information and a traffic sign corresponding to the severity level on a display device.

Disclosed is a method of providing a safe navigation route for travelling. The method comprises receiving, at a graphical user interface of a processor-based user device, a query for a navigation route from a user, comprising a source station and a destination station, determining, at an application server, a plurality of navigation routes between the source station and the destination station, analyzing, at the application server, each of the plurality of navigation routes to compute a safety index associated with each of the plurality of navigation routes, identifying, at the application server, at least one safe navigation route between the source station and the destination station, and rendering, at the graphical user interface, the at least one safe navigation route between the source station and the destination station in response to the query from the user.

A boarding/deboarding point providing system includes a probe vehicle group, a data server, and an on-board unit or a mobile terminal. When vehicle data transmitted from the probe vehicle group are input, the data server extracts a boarding/deboarding point suitable for boarding a vehicle or deboarding a vehicle from the vehicle data, and stores the point while updating the boarding/deboarding point information database. When a request for boarding/deboarding point information is received from the on-board unit or the mobile terminal, the boarding/deboarding point information stored in the boarding/deboarding point information database is searched for a boarding/deboarding point that meets the request conditions, and the search result that includes the boarding/deboarding point is transmitted to the on-board unit or the mobile terminal.