The present disclosure provides a method and apparatus for detecting a traffic anomaly, relates to the field of artificial intelligence and specifically to computer vision and deep learning technologies, and can be applied to video analysis scenarios. A specific implementation comprises: acquiring at least two frames of consecutive traffic images; identifying respectively a position of a target vehicle from the at least two frames of consecutive traffic images to obtain a position information set; determining a direction of travel and speed of the target vehicle according to the position information set; and comparing the direction of travel and speed of the target vehicle with a pre-generated vehicle vector field to determine whether the target vehicle is abnormal.

A dynamic platoon formation method under a mixed autonomous vehicles flow is provided. The method implements dynamic platooning by taking into account a fact that a traffic flow is a mixture of HDVs and CAVs. The dynamic platoon formation method includes: selecting lanes as candidate lanes in turn; constructing a decision tree from a current moment to a moment of platoon formation according to the following process: constructing a decision space for each CAV, generating a compatible decision set, selecting and executing a compatible decision, and updating location and speed information of all vehicles; and selecting, according to a predetermined index (including TTP and DTP), an optimal decision sequence as a decision sequence corresponding to the candidate lane.

A dynamic platoon formation method under a mixed autonomous vehicles flow is provided. The method implements dynamic platooning by taking into account a fact that a traffic flow is a mixture of HDVs and CAVs. The dynamic platoon formation method includes: selecting lanes as candidate lanes in turn; constructing a decision tree from a current moment to a moment of platoon formation according to the following process: constructing a decision space for each CAV, generating a compatible decision set, selecting and executing a compatible decision, and updating location and speed information of all vehicles; and selecting, according to a predetermined index (including TTP and DTP), an optimal decision sequence as a decision sequence corresponding to the candidate lane.

The present disclosure relates to a system and method for updating traffic-related infrastructure. The method includes determining average traffic stream speed and average traffic density over a segment of a highway. The method further includes determining, upon analysis of the determined average traffic stream speed and average traffic density over a segment of a highway, an appropriate action in order to update the infrastructure.

The present disclosure relates to a system and method for updating traffic-related infrastructure. The method includes determining average traffic stream speed and average traffic density over a segment of a highway. The method further includes determining, upon analysis of the determined average traffic stream speed and average traffic density over a segment of a highway, an appropriate action in order to update the infrastructure.

A system configured to, and method of, generating and providing a data product using data supplied by a multitude of vehicles that includes receiving a plurality of geographical locations; carrying out a geographical location obfuscation process in order to obtain processed connected vehicle data, wherein the geographical location obfuscation process includes: (i) identifying a road segment based on the received geographical location; (ii) determining an associated road type of the road segment; (iii) determining whether to obfuscate the received geographical location based at least in part on the associated road type; and (iv) when it is determined to obfuscate the received geographical location, obfuscating the received geographical location so as to obtain an obfuscated geographical location, wherein the obfuscated geographical location is included in the processed connected vehicle data; generating the data product using the processed connected vehicle data; and providing the data product to a third party.

A system configured to, and method of, generating and providing a data product using data supplied by a multitude of vehicles that includes receiving a plurality of geographical locations; carrying out a geographical location obfuscation process in order to obtain processed connected vehicle data, wherein the geographical location obfuscation process includes: (i) identifying a road segment based on the received geographical location; (ii) determining an associated road type of the road segment; (iii) determining whether to obfuscate the received geographical location based at least in part on the associated road type; and (iv) when it is determined to obfuscate the received geographical location, obfuscating the received geographical location so as to obtain an obfuscated geographical location, wherein the obfuscated geographical location is included in the processed connected vehicle data; generating the data product using the processed connected vehicle data; and providing the data product to a third party.

A system includes a processor and a memory storing instructions which when executed by the processor configure the processor to receive telemetry data from a vehicle being driven in a road segment, detect lane changes made by the vehicle in the road segment based on the telemetry data, and characterize the road segment and driver behavior based on the lane changes and the telemetry data.

A system includes a processor and a memory storing instructions which when executed by the processor configure the processor to receive telemetry data from a vehicle being driven in a road segment, detect lane changes made by the vehicle in the road segment based on the telemetry data, and characterize the road segment and driver behavior based on the lane changes and the telemetry data.

A speed estimation system includes: a detection module configured to determine bounding boxes of an object moving on a surface in images, respectively, captured using a camera; a solver module configured to, based on the bounding boxes, determine a homography of the surface by solving an optimization problem, where the solver module is not trained; and a speed module configured to, using the homography, determine a speed that the object is moving on the surface.