A method of annotating frames of a time sequence of frames captured by at least one travelling vehicle comprises, in a frame processing system: determining a three-dimensional (3D) road model for an area captured in the time sequence of frames; receiving first annotation data denoting a known 3D location of a moving object for a first frame of the time sequence of frames; and automatically generating second annotation data for marking an expected moving object location in at least a second frame of the time sequence of frames, by assuming the moving object moves along an expected path determined from the known 3D location and the 3D road model.

A method of annotating frames of a time sequence of frames captured by at least one travelling vehicle comprises, in a frame processing system: determining a three-dimensional (3D) road model for an area captured in the time sequence of frames; receiving first annotation data denoting a known 3D location of a moving object for a first frame of the time sequence of frames; and automatically generating second annotation data for marking an expected moving object location in at least a second frame of the time sequence of frames, by assuming the moving object moves along an expected path determined from the known 3D location and the 3D road model.

Systems and methods for optimizing traffic flow through an intersection are disclosed. In an embodiment, the method includes receiving positional data indicating a current location of a first vehicle intending to pass through the intersection, receiving directional data indicating an intended direction of the first vehicle through the intersection from the current location, determining, based on the positional data and the directional data, whether an intended path of the first vehicle through the intersection interferes with an alternative path through the intersection, and adjusting a traffic signal at the intersection to decrease an amount of time to pass through the intersection via the alternative path.

Systems and methods for optimizing traffic flow through an intersection are disclosed. In an embodiment, the method includes receiving positional data indicating a current location of a first vehicle intending to pass through the intersection, receiving directional data indicating an intended direction of the first vehicle through the intersection from the current location, determining, based on the positional data and the directional data, whether an intended path of the first vehicle through the intersection interferes with an alternative path through the intersection, and adjusting a traffic signal at the intersection to decrease an amount of time to pass through the intersection via the alternative path.

Systems, methods, and apparatuses for real-time vehicular parking enforcement are provided. The system can include a data processing system (“DPS”) comprising one or more processors and memory. The DPS can receive data captured by one or more cameras. The DPS can detect entry of a vehicle into the facility. The DPS can determine an identification number for the vehicle. The DPS can track the vehicle to a parking spot. The DPS can generate a parking event for the vehicle. The DPS can establish a timer for querying a transaction processing system. The DPS can query the transaction processing system for transaction information associated with the identification number. The DPS can generate a violation event for the vehicle. The DPS can classify the violation event. The DPS can overlay, on a digital map of the facility, an icon on the parking spot that indicates the classification of the violation event.

Systems, methods, and apparatuses for real-time vehicular parking enforcement are provided. The system can include a data processing system (“DPS”) comprising one or more processors and memory. The DPS can receive data captured by one or more cameras. The DPS can detect entry of a vehicle into the facility. The DPS can determine an identification number for the vehicle. The DPS can track the vehicle to a parking spot. The DPS can generate a parking event for the vehicle. The DPS can establish a timer for querying a transaction processing system. The DPS can query the transaction processing system for transaction information associated with the identification number. The DPS can generate a violation event for the vehicle. The DPS can classify the violation event. The DPS can overlay, on a digital map of the facility, an icon on the parking spot that indicates the classification of the violation event.

A method of determining a state of an intersection, an electronic device, and a storage medium, which relate to a field of artificial intelligence technology, and in particular to fields of intelligent transportation technology and computer vision technology. The intersection is formed by a convergence of a plurality of road segments including at least two driving-in road segments, and each driving-in road segment includes at least one sub road segment. The method includes: determining attribute data and traffic data of each sub road segment of each driving-in road segment; determining a traffic condition information of each driving-in road segment based on the attribute data and the traffic data; and determining the state of the intersection based on the traffic condition information of the at least two driving-in road segments.

Techniques for determining predictions on a top-down representation of an environment based on vehicle action(s) are discussed herein. Sensors of a first vehicle (such as an autonomous vehicle) can capture sensor data of an environment, which may include object(s) separate from the first vehicle (e.g., a vehicle or a pedestrian). A multi-channel image representing a top-down view of the object(s) and the environment can be generated based on the sensor data, map data, and/or action data. Environmental data (object extents, velocities, lane positions, crosswalks, etc.) can be encoded in the image. Action data can represent a target lane, trajectory, etc. of the first vehicle. Multiple images can be generated representing the environment over time and input into a prediction system configured to output prediction probabilities associated with possible locations of the object(s) in the future, which may be based on the actions of the autonomous vehicle.

Techniques for determining predictions on a top-down representation of an environment based on vehicle action(s) are discussed herein. Sensors of a first vehicle (such as an autonomous vehicle) can capture sensor data of an environment, which may include object(s) separate from the first vehicle (e.g., a vehicle or a pedestrian). A multi-channel image representing a top-down view of the object(s) and the environment can be generated based on the sensor data, map data, and/or action data. Environmental data (object extents, velocities, lane positions, crosswalks, etc.) can be encoded in the image. Action data can represent a target lane, trajectory, etc. of the first vehicle. Multiple images can be generated representing the environment over time and input into a prediction system configured to output prediction probabilities associated with possible locations of the object(s) in the future, which may be based on the actions of the autonomous vehicle.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a vulnerable road unit (VRU) device may determine that a parameter associated with movement of the VRU device satisfies one or more thresholds indicated in an event reporting configuration. The VRU device may transmit, to a vehicle user equipment device, an indication of an event associated with the VRU device based at least in part on determining that the parameter satisfies the one or more thresholds. Numerous other aspects are provided.