The present disclosure provides a method and apparatus for detecting a traffic anomaly, a device, a storage medium and a computer program product, relates to the field of artificial intelligence, and specifically to computer vision and deep learning technologies, and can be applied to intelligent transportation scenarios. A specific implementation of the method comprises: acquiring a traffic video stream; performing vehicle detection tracking on the traffic video stream to determine whether there is an abnormally stopped vehicle, wherein a stop with a time length exceeding a preset time length belongs to an abnormal stop; and performing a traffic anomaly classification on a video frame corresponding to the abnormal stop using a decision tree to obtain a traffic anomaly type, if there is the abnormally stopped vehicle, wherein the decision tree is generated based on features for a traffic anomaly detection.

Implementations for an intelligent road barrier (IRB) system can include a plurality of road barriers located along a roadway, and a plurality of IRB kits, each IRB kit being including a set of sensors configured to obtain sensor data representative of at least a portion of a road state of the roadway proximate to the respective road barrier, a data processing unit configured to process at least a portion of the sensor data, a communication unit configured to send at least a portion of the sensor data and to receive sensor data from the one or more other IRB kits, and a state conveyance system configured to convey at least a portion of road state data to one or more vehicles associated with the roadway, the at least a portion of road state data being determined based on the at least a portion of the sensor data.

Methods, systems, and computer-readable storage media for obtaining sensor data captured by one or more sensors that generate data representative of characteristics of a roadway, determining a state of the roadway by processing the sensor data, the state at least partially comprising a first configuration of the roadway, determining, at least partially based on the state, a period of time to deploy a plurality of road barriers on the roadway, and deploying the plurality of road barriers based on the period of time to provide a second configuration comprising at least one dedicated lane.

Provided is a roadside unit including: communication circuitry, which, in operation, receives data transmitted from an on-board unit and transfers the data to a server; and control circuitry, which, in operation, suspends, in a case where the communication circuitry has received an upload resume request for the data from the on-board unit while the data is being transferred to the server, transfer of the upload resume request to the server.

A first roadside network unit is provided. A first transceiver for a first wireless communication network is designed to receive data from a second wireless network unit on a first channel of the first wireless communication network. A processor is designed to provide the received data to a second transceiver for transmission to a third roadside network unit. The second transceiver for a second wireless communication network is designed to transmit the data provided by the processor to the third roadside network unit on a second channel of the second communication network.

An apparatus for recording license plates of vehicles travelling on a road having several adjacent lanes comprises a vehicle classification sensor configured to detect a predetermined shape characteristic of a vehicle or group of vehicles. The apparatus further comprises at least one camera mounted at an elevated point beside one of the lanes and having an angle of aperture covering at least one of said lanes, each lane covered by at least one camera. The vehicle classification sensor is configured to, upon detecting the predetermined shape characteristic on a lane, trigger the camera that covers the lane the predetermined shape characteristic is detected on to record an image of a license plate on the back of the vehicle or group's leading vehicle, respectively, for which the predetermined shape characteristic is detected. The triggered camera is of a lane either adjacent to or at least one lane apart from the lane.

Provided herein is a system and method for a vehicle system on a vehicle. The system comprises a server comprising sensor data of stop points, one or more processors, and a memory storing instructions that, when executed by the one or more processors, cause the system to perform: determining, from the stop points, one or more available stop points; selecting, from the one or more available stop points, a stop point based on a criteria; and stopping the vehicle at the selected stop point.

A system and method for determining a predicted trajectory of a human-driven host vehicle as the human-driven host vehicle approaches a traffic signal. The method includes: obtaining a host vehicle-traffic light distance d.sub.x and a longitudinal host vehicle speed v.sub.x that are each taken when the human-driven host vehicle approaches the traffic signal; obtaining a traffic light signal phase P.sub.t and an traffic light signal timing T.sub.t; obtaining a time of day TOD; providing the host vehicle-traffic light distance d.sub.x, the longitudinal host vehicle speed v.sub.x, the traffic light signal phase P.sub.t, the traffic light signal timing T.sub.t, and the time of day TOD as input into an artificial intelligence (AI) vehicle trajectory prediction application, wherein the AI vehicle trajectory prediction application implements an AI vehicle trajectory prediction model; and determining the predicted trajectory of the human-driven host vehicle using the AI vehicle trajectory prediction application.

A method and an apparatus for pushing vehicle information, a user account server, and user equipment are provided. The method includes: receiving an entry event that is of a vehicle and that is sent by a parking management server, and obtaining geo-fence information of a parking lot managed by the parking management server; obtaining, by a user account server, a user account bound to the license plate number of the vehicle; obtaining a location determining result of user equipment corresponding to the user account; and pushing the entry event of the vehicle to the user equipment when the current location of the user equipment is within a geo-fence range.

An image processing device 10 includes an image interface 18, a memory 19, and a controller 20. The image interface 18 acquires a captured image. The positions of specific feature points in a world coordinate system and reference positions of the specific feature points are stored in the memory 19. The controller 20 detects the specific feature points in the captured image. In a case where discrepancy between the position in the captured image and the reference position is found with regard to a predetermined percentage or more of the specific feature points, the controller 20 recalculates a calibration parameter.