5 results about "Traffic count" patented technology

The invention provides a double-end cooperative network-on-chip flow control method and device and electronic equipment, and the method comprises the steps: receiving first flow counting information synchronously transmitted by a destination end through a rapid signal, and determining second flow counting information of a source end, the source end and the destination end are respectively a starting node and an ending node of a complete link in the network-on-chip; estimating the link state of the network-on-chip according to the first flow counting information and the second flow counting information; and controlling the flow injection rate of the source end according to the link state. According to the method, counting information synchronization of a source end and a destination end is realized by utilizing the characteristics of low cost and high speed of a control signal in the network-on-chip, so that the link state of the network-on-chip is accurately estimated, the process ensures that no obvious flow accumulation exists on a path, bandwidth resource waste caused by excessive speed limitation is avoided, and the link state of the network-on-chip is accurately estimated. Quicker and more accurate flow management is supported; and more timely and accurate flow regulation is realized.

Disclosed herein is an Artificial Intelligence (AI) based system and method of estimating traffic count The method comprises capturing at least one traffic scene in a Field of View (FoV) of an edge device. Further, the method comprises detecting presence of one or more objects within the at least one traffic scene by analyzing at least one frame of the at least one traffic scene, using an object detection process. Furthermore, the method comprises tracking the one or more of detected objects by analyzing at least one consecutive frame with respect to the one or more detected objects until the one or more of detected objects exits the FoV. Thereafter, the method comprises estimating the traffic count based on the tracking of the one or more detected objects.

Provided are a route generation device, a vehicle control device, and a vehicle route distribution system capable of making an emergency vehicle reach a destination without delay. Provided on a server (100) that generates and distributes route information are a route generation unit (101) that generates route information from map information and destination information of a vehicle, a route information storage unit (102) that saves the route information, a general vehicle traffic count calculation unit (104) that calculates the number of general vehicles traveling on a travel route of an emergency vehicle, and an emergency vehicle travel lane generation unit (105) that generates travel lane information that determines whether a lane on which the emergency vehicle travels passes a current travel lane, an opposite lane, or a middle between the travel lane and the opposite lane.

A vehicle mileage estimation method based on remote sensing imagery and deep learning includes: constructing a self-labeled dataset by dividing high-resolution satellite images into grid cells; estimating vehicle density using a YOLO-based deep learning model, which achieves multi-scale feature fusion through a three-layer pyramid network for accurate vehicle detection; abstracting the urban road network as a graph structure and employing a cross-temporal graph neural network (CrossGraphNet) to build a model of the relationship between vehicle density and speed for accurate speed prediction; and training a semi-supervised graph neural network vehicle mileage estimation model using traffic count data from ground monitoring stations as ground truth. This model combines vehicle density and speed data with road topology relationships and uses a message passing algorithm to accurately estimate vehicle mileage. This invention overcomes the limitations of traditional methods, effectively improves the efficiency and accuracy of traffic monitoring, and provides strong data support for traffic management and planning.

We disclose a vehicle-infrastructure interaction system and method using a distributed optical fiber sensing (DFOS) system that operates using pre-deployed optical fiber communication cables buried alongside or near highways / roads. It provides a continuous stream of information about vehicle traffic 24 / 7 at multiple locations, requiring only a single optical sensor cable to detect / monitor multiple target locations and multiple lanes. This single optical sensor cable measures multiple relevant vehicle information (multi-parameters), such as vehicle speed, wheelbase, number of axles, and tire pressure. This information can be advantageously used to obtain secondary information, such as vehicle weight, as well as overall information about the vehicle fleet, such as traffic congestion and freight volume. Unlike simple traffic counts, our approach can provide counts grouped by vehicle type and load weight. The high temporal sampling rate of distributed acoustic sensing and a dedicated peak detection algorithm for reliably extracting timing information provide accurate measurements.