A target identification method includes receiving target detection information for a current target from a device, and acquiring target state information of multiple reference targets. A degree of matching between the target detection information and the target state information of each of the multiple reference targets is determined; and the current target is associated with a corresponding reference target having a best degree of matching amongst the multiple reference targets.

System and methods for determining traffic violation hotspots based on roadway feature and/or sensor data. Traffic violation hotspots include, for example areas where traffic violations are more likely to occur such as traffic light jumping, wrong way driving, over speeding, not wearing seatbelt, avoiding stop signs and red lights, distracted driving, passing other vehicles in a no-passing zone, among others. Embodiments further provide predictions for traffic accidents hotspots based on the presence or absence of the traffic violation hotspots.

A method of processing data for a driving automation system, the method comprising steps of: obtaining image data from a camera of an autonomous vehicle, AV; image processing the image data to obtain a vehicle registration mark, VRM, of another vehicle within the surrounding area of the AV; looking up the VRM in a vehicle information database to obtain information indicative of the make, the model and the date of manufacture of the other vehicle; looking up information indicative of the make, the model and the date of manufacture of the other vehicle in a vehicle dimensions database to obtain at least one dimension of the other vehicle; and updating a context of the autonomous vehicle based on said at least one dimension of the other vehicle.

Systems and methods are provided for remotely detecting a status associated with an autonomous vehicle and generating control actions in response to such detections. In one example, a computing system can access a third-party communication associated with an autonomous vehicle. The computing system can determine, based at least in part on the third-party communication, a predetermined identifier associated with the autonomous vehicle. The computing system can determine, based at least in part on the third-party communication, a status associated with the autonomous vehicle, and transmit one or more control messages to the autonomous vehicle based at least in part on the predetermined identifier and the status associated with the autonomous vehicle.

The present disclosure is directed to a computer-assisted or autonomous driving (CA/AD) vehicle with a controller to control one or more light emitters to produce a light pattern that uniquely identify the vehicle. It may also be directed to a system to receive image data from one or more video cameras located in a location vicinity of the CA/AD vehicle emitting a pattern of light, and to analyze the received image data to determine a physical location of the vehicle.

A vehicle control system for providing information to support an overtaking maneuver by a first vehicle, the vehicle control system includes: a processing circuitry adapted to be operatively connected to a traffic view camera and configured to: receive image data of at least one other vehicle in traffic by the traffic view camera; determine, based on the image data of the at least one other vehicle in traffic, overtaking support data indicative of at least one gap in the traffic suitable for an overtaking maneuver; and provide the overtaking support data to the first vehicle for supporting an overtaking maneuver by the first vehicle.

The present disclosure relates to identifying vehicles using wireless device identifiers. In accordance with aspects of the present disclosure, a system for identifying vehicles in a parking structure includes a camera configured to capture images of an area in the parking structure where the camera captures an image containing one or more vehicle(s), a detector configured to scan for wireless device identifiers in the area, and a processing system including an electronic storage. The processing system is configured to execute instructions to access the image containing the vehicle(s) in the area and access one or more wireless device identifier(s) scanned by the detector in the area, process the image containing the vehicle(s) to extract one or more license plate identifier(s) corresponding to the vehicle(s), and store in the electronic storage at least one record associating the license plate identifier(s) with the wireless device identifier(s).

Aspects presented herein may enable vehicle UE(s) to transmit warning message(s) to one or more pedestrian UEs without receiving P2V transmissions from the one or more pedestrian UEs. In one aspect, a first UE determines one or more configuration parameters for a plurality of second UEs, the one or more configuration parameters including an identification parameter, the identification parameter being associated with a time period. The first UE determines, based on the identification parameter for at least one second UE of the plurality of second UEs, whether to transmit a warning message to the at least one second UE. The first UE transmits, based on determining to transmit the warning message, the warning message to the at least one second UE, the warning message including an ID for the at least one second UE, the ID for the at least one second UE being based on the identification parameter.

Embodiments relate to systems, methods and computer readable media for parking monitoring in an urban area by image processing operations. Embodiments perform parking monitoring by capturing images of an urban area, comparing captured images with reference images to determine location and parking conditions. Embodiments processes captured images to detect licence plates, vehicles or parking signs to determine compliance of vehicles with parking conditions.

To realize an apparatus and a method for receiving a recognition level of an own vehicle from another vehicle and/or an infrastructure facility and performing control to improve a recognition level. A recognition level of the own vehicle calculated by another vehicle or the infrastructure facility is received, and control for improvement of a recognition level of the own vehicle is executed in accordance with the received recognition level. As the control for improvement of a recognition level of the own vehicle, any process is executed among: (a) a process of reducing a traveling speed or stopping; (b) a process of turning on a light; and (c) a process of changing transmission information from the own vehicle. As the process of changing transmission information, a process of adding, to the transmission information, vehicle location information, vehicle speed information, vehicle size information, or reference marker position information is executed.