Abstract
Traffic congestion is a serious issue for urban cities. From city roads to highways, a lot of traffic problems occur everywhere in today’s world, because of exponentially increase in the number of vehicles, the traffic management system and road capacity are not efficiently compatible with vehicles traveling on them. These frequent traffic problems like traffic jams have led to the need for an efficient traffic management system. This work focuses on the design of dynamic traffic control system based on real-time vehicle density present at the traffic post and highlights the experimental verification of outdoor density estimation system combined with traffic control unit. It provides good results under mixed traffic conditions and in adverse weather. Vehicle classification and counting are done using edge computing techniques and upload data to database; based on the vehicle count, density is estimated and green channel time is calculated for particular lane of traffic post.
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Deshmukh, P., Gupta, D., Das, S.K., Sahoo, U.K. (2020). Design of a Traffic Density Management and Control System for Smart City Applications. In: Mallick, P., Balas, V., Bhoi, A., Chae, GS. (eds) Cognitive Informatics and Soft Computing. Advances in Intelligent Systems and Computing, vol 1040. Springer, Singapore. https://doi.org/10.1007/978-981-15-1451-7_49
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DOI: https://doi.org/10.1007/978-981-15-1451-7_49
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