A method performed in an Internet of Vehicles data transmission system is provided in the present disclosure, where the Internet of Vehicles data transmission system includes a plurality of clusters and at least one road-side unit connected to the Internet, each cluster includes at least one on-board unit, and the at least one on-board unit includes a cluster head on-board unit, and the method includes: transmitting data in the on-board unit to one of the at least one road-side unit, via the cluster head on-board unit of the cluster where the on-board unit belongs. An on-board unit and an Internet of Vehicles data transmission system are further provided.

A control device in one aspect of the present disclosure includes a vehicle information acquisition unit, an obstacle information acquisition unit, and a sudden braking detection unit, and controls a warning information transmission unit to transmit, to an other vehicle, warning information including obstacle information when a sudden braking is performed by a subject vehicle. When receiving the warning information from the other vehicle, a target vehicle determination unit confirms that the other vehicle is a warning target vehicle, and a risk calculation unit calculates a collision risk of the subject vehicle to collide with an obstacle, and a collision avoidance unit performs a collision avoidance control according to the calculated collision risk.

A control device in one aspect of the present disclosure includes a vehicle information acquisition unit, an obstacle information acquisition unit, and a sudden braking detection unit, and controls a warning information transmission unit to transmit, to an other vehicle, warning information including obstacle information when a sudden braking is performed by a subject vehicle. When receiving the warning information from the other vehicle, a target vehicle determination unit confirms that the other vehicle is a warning target vehicle, and a risk calculation unit calculates a collision risk of the subject vehicle to collide with an obstacle, and a collision avoidance unit performs a collision avoidance control according to the calculated collision risk.

A method includes, by a processor, acquiring number of persons information that indicates a number of users, including users who ride in vehicles, who depart from a facility at each of a predetermined time period, weather information for each predetermined time period, and vehicle information relating to vehicles traveling in a periphery of the facility, determining traffic jam status that indicates absence/presence of a traffic jam on a road located in a vicinity of the facility in the predetermined time period, by using the vehicle information; and generating a learned model for predicting a traffic jam of a road by machine learning using, as teaching data, the number of persons information, the weather information, and the traffic jam status that is associated with the number of persons information and the weather information.

A method includes, by a processor, acquiring number of persons information that indicates a number of users, including users who ride in vehicles, who depart from a facility at each of a predetermined time period, weather information for each predetermined time period, and vehicle information relating to vehicles traveling in a periphery of the facility, determining traffic jam status that indicates absence/presence of a traffic jam on a road located in a vicinity of the facility in the predetermined time period, by using the vehicle information; and generating a learned model for predicting a traffic jam of a road by machine learning using, as teaching data, the number of persons information, the weather information, and the traffic jam status that is associated with the number of persons information and the weather information.

A vehicle control apparatus estimates a speed of a surrounding object of a vehicle using a relative speed of the surrounding object, and thus, it is possible to prevent malfunction of the ADAS function and collision of the vehicle with the surrounding object even when the speed of the surrounding object cannot be measured. The vehicle control apparatus controls the vehicle by distinguishing whether a position of the vehicle is a parking lot, and thus, it is possible to prevent the malfunction of the ADAS.

A vehicle control apparatus estimates a speed of a surrounding object of a vehicle using a relative speed of the surrounding object, and thus, it is possible to prevent malfunction of the ADAS function and collision of the vehicle with the surrounding object even when the speed of the surrounding object cannot be measured. The vehicle control apparatus controls the vehicle by distinguishing whether a position of the vehicle is a parking lot, and thus, it is possible to prevent the malfunction of the ADAS.

The system for tracking and reporting toll road usage in real time disclosed herein may track tolling points, tolling segments, and toll assessments across multiple technologies to provide a single system that may be used universally. The system for tracking and reporting toll road usage in real time may comprise a plurality of sensors installed in a vehicle, or in a standalone module that may be installed in a vehicle, in combination with a central database for aggregating and processing the sensed information. The various sensors may include, for example, GPS-based location devices, RFID transponders and detectors, short-range wireless technology devices, inertial measurement devices, occupancy sensors, cameras, and lost mode trackers.

The system for tracking and reporting toll road usage in real time disclosed herein may track tolling points, tolling segments, and toll assessments across multiple technologies to provide a single system that may be used universally. The system for tracking and reporting toll road usage in real time may comprise a plurality of sensors installed in a vehicle, or in a standalone module that may be installed in a vehicle, in combination with a central database for aggregating and processing the sensed information. The various sensors may include, for example, GPS-based location devices, RFID transponders and detectors, short-range wireless technology devices, inertial measurement devices, occupancy sensors, cameras, and lost mode trackers.

A method of determining whether one or more navigable elements of a navigable network within a geographic area are still affected by a precipitation weather event. A quantity parameter is associated with each segment of an electronic map representing the navigable network and indicates the amount of precipitation remaining on the navigable element or portion thereof represented by the segment. The value of the quantity parameter increases in the presence of any precipitation weather event, and decreases ac cording to a predefined function with respect to time in the absence of any such precipitation weather event. A speed of travel of one or more devices along the navigable element or portion thereof represented by a segment is determined and compared to an expected speed of travel for the segment; the value of the quantity parameter being decreased based on the comparison. The value of quantity parameter can be used to generate weather events and/or attribute the cause of a congestion event as being the precipitation weather event.