DENSITY DETERMINATION AND REAL TIME TRAFFIC CONTROL USING IMAGE PROCESSING

Vehicle counting is considered one of the most important applications in traffic control and management. To count vehicles, synchronous vehicle detection and tracking should be carried out. Preliminary results for developing an automated system for counting and classification of vehicles in motion, based on machine learning techniques were presented in this paper. The developed system was able to count vehicles and classify them with a reasonable accuracy. There is exigent need of efficient traffic management system in our country, as India meets with 384 road accidents every day. To reduce this congestion and unwanted time delay in traffic an advanced system is designed here in this project. With field application of this technology, the maddening chaos of traffic can be effectively channelized by distributing the time slots based on the merit of the vehicle load in certain lanes of multi junction crossing. We have successfully implemented the prototype at laboratory scale with remarkable outcome. The next step forward is to implement this schema is real life scenario for first hand results, before implementing it on the largest scale. We believe that this may bring a revolutionary change in traffic management system on its application in actual field environment.