Author : Tushar P Sharma and Kumbharde M.V.

With increment in urbanization and socio- prudent development, the quantity of vehicles in significant metropolitan urban areas is expanding step by step. Along these lines, traffic blockage is turning into a significant worry of metropolitan urban communities everywhere throughout the world. This outcome in gigantic air contamination, loss of important time and cash of residents. Consequently, traffic congestion observing of various street fragments is extremely fundamental for breaking down the issue related with smooth portability. Distinguishing the dangerous street fragments inside the city is one of the significant activities for the vehicle power to survey the street condition. That will help the administration organizations or strategy creators to improve traffic rules and guidelines. This work distinguishes traffic congestion design which can order the diverse street sections dependent on traffic density and normal speed of vehicles. The traffic parameters are caught by in- street stationary sensors conveyed in street fragments. The proposed system utilizes k-means clustering algorithm to arrange the diverse street portions.

Keywords: Clustering; in-road sensors; traffic congestion pattern; k- means;