Nowadays Road traffic is major issue of developing and under developing countries. With the rampant increase of traffic, the society faces major traffic threats including life threats and environmental threat, thus traffic management is gruesome problem to address. The consequences of poor traffic management include road accidents, jamming of traffic, pollution and many more that can be life threatening. Living in 21 st century with the emergence of technology and applicability of smart cities provides a perfect solution to curb traffic issues. Keeping in view the deadlock and congestion in traffic, this work provides solution by indigently detecting and prioritizing the vehicles and non-vehicles. The research involves implementation and comparison of two state of art algorithms Aggregated channel feature and Point Tracker. Further, the algorithms are enhanced by improving traffic management in terms of identifying category of transport, prioritizing the traffic which contains vehicle and non-vehicles on basis of size of vehicle, type of vehicle, emergency situation and provide the priority to resolve the deadlock. Further, the proposed enhanced point tracker algorithm includes the emergency detection in case of accident and provide an alternative route to neighboring vehicles and non-vehicles. Enhanced ACF has detected true positive rate of 80%, 89%, has detected true positive rate of 69% and 79% having non-vehicle detected with assigned priority. Enhanced point tracker has detected true positive rate of 88%, 94%, and 86% having vehicles, non- vehicles and assigned priority.