A device and a method for predicting traffic information are provided. The traffic information predicting device may include a data calculating device configured to derive inter-vehicle spacings, inter-vehicle head spacings, and a vehicle density using a plurality of sensors mounted on a vehicle, and a predicting device configured to derive travel speed data corresponding to the vehicle density and predict traffic information.

A communication device capable of communicating with an external device in accordance with states of an operator and a movable apparatus includes: a riding determination unit configured to determine whether an operator is riding a movable apparatus; and a communication unit configured to transmit a message including attribute information indicating the movable apparatus to another device when the riding determination unit determines that the operator is in a first state in which the operator is riding the movable apparatus, and to transmit a message including attribute information indicating a pedestrian to the other device when the riding determination unit determines that the operator is in a second state in which the operator is not riding the movable apparatus and is operating the movable apparatus.

Techniques are described for vehicle activity information collection and analysis. A vehicle activity information unit in a vehicle generates vehicle activity information including video data that is captured by interior and/or exterior camera(s) on the vehicle. The vehicle activity information can also include sensor data generated by an accelerometer, a compass, a temperature sensor, a Global Positioning System module, and/or other sensor(s). The vehicle activity information can also include audio data generated by at least one microphone. In some implementations, at least a portion of the vehicle activity information is collected during a period of time that includes an event (e.g., an accident). The information is stored in data storage with an association between the information and the event, and is processed to generate performance data associated with a driver of the vehicle. The performance data can be presented through a user interface to the driver or other(s).

A method of determining real-time tax and/or subsidy information includes obtaining, from an operator, trip-related information regarding a trip and determining a target objective associated with trip routing at a time of receipt of the trip-related information. The method includes obtaining additional information from one or more additional data sources based on the target objective and the trip-related information, determining, based on the trip-related information and the additional information, a tax or subsidy associated with the trip, and providing information indicative of the tax or subsidy to the operator.

A detection device and an indoor navigation system are provided. The detection device includes two detection modules each including a sound receiver for receiving sound from a peripheral object and a signal converting circuit that is electrically coupled to the sound receiver and that is configured to convert input signal from the sound receiver into a target spectrogram. The two spectrograms from the signal converting circuits have a time/phase difference, and at least one wireless earphone includes a storage unit and a judging circuit that is electrically coupled to the storage unit and the two signal converting circuits. The judging circuit is configured to compare any target spectrogram with basic spectrograms of the storage unit so as to determine which kind of objects the peripheral object is, and is configured to obtain an instant position of the peripheral object by the time/phase difference.

Provided is an information processing method of determining the influence of the event on the traffic condition, and this method includes a first link setting step of setting a link, related to an occurrence position of the event, as a target link, a determining step of determining a degree of influence of the event on the traffic condition of the target link, and a second link setting step of setting a link adjacent to the target link as a new target link based on a determination result of the determining step, in which the processing in the determining step is performed on the target link specified in the second link setting step.

In an example, a method receives vehicle data for a plurality of vehicles associated with a geographic region. The method determines, based on the vehicle data, a connected vehicle status of the geographic region. The connected vehicle status reflects an estimated number of connected vehicles in the geographic region at a point in time. The method determines, based on the estimated number of connected vehicles, one or more vehicle functions to be deployed by a server associated with the geographic region. The method deploys, by the server, the one or more vehicle functions.

Techniques are providing for situationally-dependent service prioritization in a CV2X network. An example method of prioritizing data packets with a mobile device includes determining a range to a waypoint, determining an estimated time of arrival at the waypoint, computing a priority value based at least in part on the estimated time of arrival at the waypoint, and generating a data packet based on the priority value.

A method of analyzing traffic by a system includes receiving sequential location measurements from users of the system, mapping the received sequential location measurements to a digital map and determining traffic information for a first time period based on mapped sequential location measurements corresponding to the first time period. A system may include a database configured to store sequential location measurements received from users of the system and a processor configured to extract sequential location measurements from the database and determine traffic information for a first period based on the extracted sequential location measurements. The sequential location measurements include periodic times and associated coordinates.

A method for predicting energy consumption of a vehicle using a statistical model. The method includes (i) predicting a set of future input vectors for the vehicle at defined time intervals corresponding to a plurality of future points in time based on a subset of a plurality of reference input vectors previously generated at the defined time intervals at a plurality of previous points in time, (ii) predicting a change in the energy level of the vehicle at the future points in time using a processor and the statistical model, and (iii) providing results corresponding to the predicted change in the energy level to an output unit of the vehicle. The change in the energy level comprises a function of corresponding future input vectors and an associated weighting vector. The change in the energy level is predicted based on a regression analysis of the energy level associated with each of the reference input vectors.