Real-Time Traffic Congestion Detection Technology in Intelligent Transportation Systems

With the acceleration of urbanization and the increase in the number of motor vehicles, traffic congestion has become a global problem. Intelligent transportation systems (ITS) and their core components, real-time traffic congestion detection technology, provide new solutions to this problem. This study utilizes a variety of sensors and information transmission technologies, including ground induction coils, video surveillance cameras, GPS, etc., to collect real-time data on traffic flow, vehicle speed, and vehicle density. By feeding this data into advanced traffic models and combining machine learning and data mining techniques, the research aims to improve the accuracy of traffic congestion predictions. The expected research result is that this technology can effectively optimize traffic flow, reduce traffic accidents, reduce environmental pollution, and ultimately improve the overall efficiency and sustainability of urban transportation.