A system and method for collecting, processing, storing, or transmitting traffic data. A localized data collection module may retrieve, receive, or intercept traffic data through or from hardware installed in a traffic control cabinet adjacent an intersection or other roadway feature of interest. Data which may have previously been confined to a closed loop traffic control system may be remotely accessible for traffic operations control or monitoring via a network connected server and/or cloud architecture.

A method, apparatus and computer program product are provided to define a strand upstream of a direction based traffic (DBT) link. In a method, a strand is defined upstream of a DBT link. The method includes extending the strand so as to include one or more links upstream of the DBT link. The strand is extended by determining whether a link is to be added to the strand based upon evaluation of a termination criteria. The termination criteria is at least partially based upon a relationship of a function class of the link to the function class of one or more other links. In an instance in which the termination criteria is satisfied, the method ceases further extension of the strand.

A regional dynamic perimeter control method and system for preventing boundary links queuing overflow. The method includes: estimating the number of queuing vehicles of boundary links using a Kalman filtering extension method using traffic flow information, and calculating a maximum of receivable vehicles; dividing the boundary links utilizing an estimated number of each boundary link's queuing vehicles and the maximum number of receivable vehicles obtaining a boundary link set with sufficient storage and a boundary link set with insufficient storage; obtaining a critical accumulation of a region according to a preset Macroscopic Fundamental Diagram (MFD) model of the region, and predicting the estimated region accumulation in a sampling period; and controlling a regional boundary intersection traffic flow operation using a deviation between the predicted and critical accumulation and boundary link sets. Deterioration of regional traffic flow is avoided, and the probability of overflow of boundary links is reduced.

A regional dynamic perimeter control method and system for preventing boundary links queuing overflow. The method includes: estimating the number of queuing vehicles of boundary links using a Kalman filtering extension method using traffic flow information, and calculating a maximum of receivable vehicles; dividing the boundary links utilizing an estimated number of each boundary link's queuing vehicles and the maximum number of receivable vehicles obtaining a boundary link set with sufficient storage and a boundary link set with insufficient storage; obtaining a critical accumulation of a region according to a preset Macroscopic Fundamental Diagram (MFD) model of the region, and predicting the estimated region accumulation in a sampling period; and controlling a regional boundary intersection traffic flow operation using a deviation between the predicted and critical accumulation and boundary link sets. Deterioration of regional traffic flow is avoided, and the probability of overflow of boundary links is reduced.

A method for traffic diversion management in a smart city is provided. The method applied to the management platform includes obtaining a first traffic feature of a target road within a first time period from an object platform through a sensor network platform, wherein the first traffic feature is a feature reflecting a flow situation of the target road, determining a target tidal lane opening scheme of the target road within the first time period based on the first traffic feature, wherein the target tidal lane opening scheme is a scheme for managing an opening time of a tidal lane, a flow direction of the tidal lane, and a number of tidal lanes for the target road, sending the target tidal lane opening scheme to the target object through a sensor network platform, and sending the target tidal lane opening scheme to the user platform through a service platform.

A method for traffic diversion management in a smart city is provided. The method applied to the management platform includes obtaining a first traffic feature of a target road within a first time period from an object platform through a sensor network platform, wherein the first traffic feature is a feature reflecting a flow situation of the target road, determining a target tidal lane opening scheme of the target road within the first time period based on the first traffic feature, wherein the target tidal lane opening scheme is a scheme for managing an opening time of a tidal lane, a flow direction of the tidal lane, and a number of tidal lanes for the target road, sending the target tidal lane opening scheme to the target object through a sensor network platform, and sending the target tidal lane opening scheme to the user platform through a service platform.

The present method permits to get real-time traffic data by the mean of pictures took by a series of georeferenced and synchronized high speed cameras installed on the portions of the road. These pictures and these data will be transferable by a secure means such as 5G or any other fast and secure technology on a server and accessible by cloud computing. Picture processing is carried out by photogrammetric, triangulation and picture recognition approaches in order to extract the position of each vehicle, pedestrian, cyclist or any object and identify its x, y, z coordinates in a local or global referencing system. This method permits to count the flow of traffic (vehicles, pedestrians, etc.) passing through these roads portions, to reproduce the real movements of vehicles, pedestrians and any object moving on a road, make simulations with a computer and intervene remotely in real-time to manage traffic.

A traffic intersection monitoring system and method to ensure a traffic signal is viewable by vehicles, bicyclists, and pedestrians, by measuring the color light intensity of the signal light, and monitoring the orientation of the traffic signal light. Each phase of color is timed and coordinated with traffic counters to generate a real-time status of predicted future traffic signal light color with corresponding traffic volume. The predicted status and traffic counts are published for the use of any applicable subscriber of the traffic intersection monitoring system.

The present disclosure provides a method for controlling a traffic scheduling strategy in a smart city. The method includes obtaining traffic data information in a preset area during a current time period, the traffic data information at least including a speed of at least one vehicle on at least one road, predicting one or more target areas where traffic congestion is likely to occur from the preset area during a next time period based on the traffic data information in the preset area during the current time period, determining whether the traffic scheduling strategy is needed to be switched based on traffic data information in the one or more target areas during the next time period, and in response to determining that the traffic scheduling strategy is needed to be switched, switching a first traffic scheduling strategy to a second traffic scheduling strategy.

One or more devices may obtain traffic data, such as video from intersection cameras, point cloud data from Light Detection and Ranging (or “LiDAR”) sensors, and so on. Metrics may be calculated from the traffic data. For each frame, the metrics may be analyzed to detect whether a near miss/collision occurs between each object in the frame (such as motorized or non-motorized vehicles, pedestrians, and so on) and each of the other objects in the frame. These metrics may be analyzed to evaluate whether or not a group of conditions are met. If the group of conditions are met, a near miss/collision may be detected. This may be recorded in the metrics for the objects involved. In some implementations, one or more indicators may be added to the traffic data and/or to one or more visualizations generated using the metrics, the traffic data, the structured data, and so on.