Real time traffic congestion detection system

Abstract

In recent years, vehicle management systems have been expanded to include more fields and features. One important system which requires attention is the traffic congestion alert. All previous works on traffic congestion detection either need prior knowledge or lengthy time to detect and recognize the presence of congestion. Some other methods involve huge infrastructure in order to implement. The proposed system in this paper offers a novel method to detect congestion in real-time without any human supervision or any prior knowledge. The designed system counts the vehicles on road by detecting and paring the vehicles backlights from a real time captured image, whereas the system consumes shorter time and maybe feasible to be implemented at any highway premise. The experimental results show that the system has very high detection accuracy (99-100) %.

Vision‐based vehicle detection for road traffic congestion classification

“…Nidhal et al 13 proposed a novel method to detect congestion in real-time without any human supervision or any prior knowledge. The designed system counts the vehicles on road by detecting and coupling the vehicles back-lights from a real-time captured images, then the number of paired objects has to be compared with a certain threshold to estimate the congestion level.…”

A Knowledge Graph Framework for Detecting Traffic Events Using Stationary Cameras

“…ere have been studies using image data for tra c event detection, speci cally congestion detection. Nidhal et al [12] used features extracted from tra c image data to detect backlight pairs as a means of detecting the number of vehicles in the scene. However, the performance of the system under di erent lighting conditions was not described, nor was the denoising process which is critical in this application as it uses more ne-grained image features.…”

Automated signal pre-emption system for emergency vehicles using internet of things

“…System which turn signal green when the ambulance is approaching the junction, system tries to create a green wave, however it needs predefined timings to control signals irrespective of a road conditions [4]. Object detection is done using image processing technique [5], here vehicles backlights are captured and their two lights are paired using distance formula to confirm the vehicles count and congestion. This method gave about 95.75% to 100% accuracy.…”