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@article{160843,
        author = {CHARU ROHILLA and KRISHAN KUMAR},
        title = {MACHINE LEARNING bAES SMART TRAFFIC CONTROL SYSTEM},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {12},
        pages = {812-816},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=160843},
        abstract = {Sometimes there is a situation in which lots of vehicles on the roads get stop moving. There will be late arrival by students & employees on their work, drivers become frustrated, occurring of road accidents due to constant stopping & moving of traffic. This situation is considered as a traffic congestion problem which is very critical & it need to be controlled as it is a worldwide problem. India has a network of over 6,215,797 kilometers of road. The country which has the second largest road network in the world is India. The major cause of road accidents is lot of registered vehicles, overpopulation, less number of available roads as required and inadequate parking facilities. Despite of implementation of strict traffic rules, even-odd system, express highways, widening of roads problem continues. In this research a system has been proposed to develop a smart transportation system. The task is to collect dataset of traffic density at different intervals in each direction at each round about. According to the collected dataset, system will determine duration of green & red lights for all directions at each round about. The system will work based on the knowledge of traffic density, there will be large duration of green lights for the lane which has the more traffic density. Counting the number of vehicles & detecting the type of vehicle helps in making a smooth transportation system. },
        keywords = {RFID, GSM, YOLO, HOG, MC, R-CNN},
        month = {},
        }