A behavior prediction system predicts human behaviors based on environment-aware information such as camera movement data and geospatial data. The system receives sensor data of a vehicle reflecting a state of the vehicle at a given time and a given location. The system determines a field of concern in images of a video stream and determines one or more portions of images of the video stream that correspond to the field of concern. The system may apply different levels of processing powers to objects in the images based on whether an object is in the field of concern. The system then generates features of objects and identify VRUs from the objects of the video stream. For the identified VRUs, the system inputs a representation of the VRUs and the features into a machine learning model, and outputs from the machine learning model a behavioral risk assessment of the VRUs.

A parking control system for an autonomous vehicle is provided. The parking control system includes a parking control device configured to monitor a location and movement of an autonomous vehicle which enters a parking lot, based on a 3D electronic map, calculate a driving trajectory to a parking space selected by a driver of the autonomous vehicle based on sensor data collected from various sensor in the parking lot and vehicle information received from the autonomous vehicle, and provide information about the calculated driving trajectory to the autonomous vehicle. The autonomous vehicle travels to the parking space based on the driving trajectory received from the parking control device and parks in the parking space.

A method, apparatus and computer program product are provided to determine lane status confidence indicators of lane status predictions such as closures and/or shifting. Lane statuses and corresponding confidence indicators are determined based on probe data, such as probe data collected from vehicle and/or mobile devices traveling along a road segment. Probe data may be partitioned into clusters and compared to partitioned subsets of the probe data. Cluster stability for the segment and corresponding lane status confidence indicators can be determined based on the comparison. Accordingly, determinations of whether to transmit predicted lane statuses to another system, service, and/or user device may be made.

Disclosed are techniques for wireless communication. In an aspect, a vehicle communications system of a vehicle comprises a vehicle controller with a wireless communications interface capable of providing wireless coverage in a plurality of vehicle regions, and a set of relay devices that are each communicatively coupled to the vehicle controller and are each capable of providing wireless coverage in at least one of the plurality of vehicle regions. In a further aspect, the vehicle controller transitions between first and second modes of communication based in part upon a traffic condition.

The present disclosure provides a method and system for selecting an optimal edge computing node in an Internet of vehicle (IoV) environment. The method includes: acquiring and analyzing properties of computing tasks of a vehicle in the IoV environment; acquiring and analyzing properties of different edge computing nodes; computing matching degrees between the properties of the computing tasks and the properties of the nodes; analyzing computing demands of different tasks, and assigning weights to different types of matching degrees; and selecting a node having an optimal sum for products of the matching degrees and the weights as an optimal edge computing node to compute each of the computing tasks of the vehicle.

At least one nearby vehicle may be extracted from a vehicle vicinity image collected by a sensor equipped in the target vehicle. Lane recognition information representing which one position a position of the extracted nearby vehicle corresponds to with respect to the target vehicle, and/or vehicle position information representing a relative distance from the target vehicle to the nearby vehicle may be identified. An attention degree of the nearby vehicle may be calculated based on a speed of the nearby vehicle calculated from the relative distance and a vehicle speed of the target vehicle, the vehicle position information of the nearby vehicle, the relative distance of the nearby vehicle, the speed of the target vehicle, or any combination thereof. An alarm for the nearby vehicle may be displayed on a screen according to the calculated attention.

A method for perception-sharing between similarly-situated vehicles that are traveling on a portion of a roadway that is equipped with an intelligent vehicle highway system is described, and includes executing, in a multi-access edge computing cluster in communication with a roadside unit disposed to monitor a roadway, an application-layer routine. The application-layer routine includes collecting real-time data associated with a plurality of objects from each of the similarly-situated vehicles, predicting motion of each of the plurality of objects based upon the real-time data, object-matching the motion of each of the plurality of objects, and executing fusion of the plurality of objects based upon the object-matching of the motion of each of the plurality of objects. Locations of the similarly-situated vehicles traveling on the roadway are identified based upon the fusion of the plurality of objects. The locations are communicated to one of the similarly-situated vehicles.

A sensor network comprises at least one lateral optical fiber and at least one longitudinal optical fiber. The lateral fiber comprises optical sensors coupled to a pavement in a transverse orientation relative to a direction of vehicle travel along the pavement. The longitudinal fiber comprises optical sensors coupled to the pavement in a longitudinal orientation relative to the direction of vehicle travel. The optical sensors are configured to produce wavelength shift signals comprising one or more lateral strain signals associated with the lateral fiber and one or more tangential strain signals associated with the longitudinal fiber. A processor is operatively coupled to the sensor network and configured to determine a weight of vehicles moving along the pavement based on the lateral and tangential strain signals. A transmitter is operatively coupled to the processor and configured to transmit the weight of vehicles to a predetermined location.

A method for adjusting control parameters of a traffic management system in a presence of one or more incidents on a network includes junctions in a tree format, and at a lowest level of a tree comprise a group of associated junctions using coordinated timing, wherein each junction is associated with a weight as a function of its height within its tree, and wherein a junction with a highest weight in each tree comprises a lead junction for receiving timing information for its group of associated junctions.

Disclosed are systems and methods relating to providing corridor metrics based on road network data and telematic data.