Method of non-stop passage of signal-controlled intersections using dynamic signs and computer vision

A Traffic Management System for Minimization of Intersection Traffic Congestion: Case Bengkong Junction, Batam

“…In dealing with Traffic congestion problems, one of the steps that can be taken is to identify roads, including road capacity, traffic volume, and degree of saturation. Of course, a specific method is used to identify a road so that the results are more accurate, precise, and efficient (Gorodokin et al, 2020). A public road is designated and used for public traffic with residents around the area building road barriers such as unloading cargo, unloading pairs, establishing speed bumps on roads, and having many time delays in roads that have an impact on the effectiveness of development.…”

Forecasting the Amount of Traffic-Related Pollutant Emissions by Neural Networks

“…We received a continuous data stream from a street video surveillance camera with a large viewing angle and a stable video stream (25 frames per second), supporting a 1920 × 1,080 resolution. We trained and modified the YOLOv4 convolutional neural network to collect data on traffic parameters, such as the number, trajectory, speed, and idle time of vehicles (Figure 1) (Gorodokin et al, 2020;Shepelev et al, 2020;Winter et al, 2021;Shepelev et al, 2022).…”

Assessing the Traffic Capacity of Urban Road Intersections

“…Increasing the traffic capacity of the road network (RN) with highdensity traffic flows (TF) is one of the main priorities for road traffic organization in large cities. The most effective solution to this problem is to introduce traffic signal synchronization at intersections (Saha et al, 2019;Gorodokin et al, 2020;Patel et al, 2015). The development and widespread use of artificial intelligence methods, fuzzy logic, and computer vision has made it possible to obtain real-time data on the parameters of the TF (speed, types of vehicles, and their number) (Dai et al, 2020;Gu et al, 2020;Shen et al, 2020;Shepelev et al, 2020;Shepelev et al, 2021;Wang et al, 2022;Zhou et al, 2021).…”