SPCCP-Miner: Towards the Discovery of Congested Junctions

Traffic congestion occurs when the total traffic volume on the road network exceeds the road's capacity, disrupting normal traffic flow and causing psychological stress for city residents. Junctions as the focal points of traffic volume in urban road networks, play a crucial role in alleviating traffic congestion through their rational planning. Thus, to assist traffic management departments in alleviating traffic congestion, we present a system called SPCCP-Miner (SubPrevalent Co-Location Congestion Pattern Miner) to discover congested junctions. The system identifies congested intersections based on spatial-temporal data mining by discovering sub-prevalent patterns. In addition, by utilizing density peak clustering algorithm, the system's efficiency has been effectively enhanced. Upon analyzing the congested junctions discovered by the system, users can make decisions to remit traffic congestion, such as extending the green time. Experimental evaluations using real-world datasets validate the system's efficacy.