Sep 20, 2018 · This paper presents the development of a vision-based system for microscopic road traffic scene analysis and understanding using computer vision and computational intelligence techniques. The...

Sep 22, 2021 · In this paper, we focus on two common traffic monitoring tasks, congestion detection, and speed detection, and propose a two-tier edge computing based model that takes into account of both the limited computing capability in cloudlets and the unstable network condition to the TMC.

This repository tackles traffic congestion in smart cities using computer vision. The system automatically detects and classifies vehicles, analyzes traffic density, and dynamically adjusts traffic lights - all to optimize traffic flow!

This chapter discusses traffic flow analysis in the context of technologies for intelligent transportation systems (ITS) from three important perspectives. First, we look at traffic flow from a transport engineering perspective so as to set the context in terms of the application domain.

Traffic analysis system using computer vision project paper proposes the video based data for vehicle detection and counting systems based on the computer vision. In most Transportation Systems cameras are installed in fixed locations. Vehicle detection is the most important requirement in traffic analysis part.

Jul 5, 2023 · Computer vision techniques can analyze traffic patterns, vehicle density, and speed to detect congestion hotspots and provide real-time alerts for traffic management. By analyzing the movement of vehicles over time, computer vision algorithms can estimate vehicle trajectories.

Using deep learning and computer vision techniques, this study suggests a new way to monitor and detect traffic in real-time. Using cutting-edge object detection techniques and convolutional neural networks (CNNs), the suggested system can reliably identify and follow moving objects in traffic camera footage.

Apr 15, 2025 · A traffic flow prediction algorithm incorporating deep learning and principal component analysis to enhance junction control [18] considers the nonlinear connection between traffic data and successfully forecasts traffic flow.

This chapter discusses traffic flow analysis in the context of technologies for intelligent transportation systems (ITS) from three important perspectives. First, we look at traffic flow from a transport engineering perspective so as to set the context in terms of the application domain.