Abstract
With the hasty expansion of urbanization and the overcrowding of cities, real-time traffic management system is considered to be very crucial for any smart city as it provides comfort, safety, security, and efficient time management to the people. However, while there is an increase of freight volume and the number of vehicles, length of the roads was not increasing adequately. It creates the problem of traffic congestion, prolonging traffic queues and unfortunate incidents like accidents etc leading to huge gridlocks. This issue can be addressed by incorporating smart and intelligent technologies in such a way that the overall traffic management system becomes capable of handling the traffic dynamically. In this paper, we have proposed a distributed approach to make a real time traffic analysis on the highways when an accident occurs. Based on it a smart decision can be taken by a vehicle to reduce the congestion on the lane. We have simulated our approach using the well-known network simulator ns-3.
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Javaid, S., Sufian, A., Pervaiz, S., Tanveer, M.: Smart traffic management system using Internet of Things. In: International Conference on Advanced Communication Technology, ICACT 2018, Chuncheon-si, Gangwon-do, Korea (South), pp. 393–398, February 2018
Swathi, K., Sivanagaraju, V., Manikanta, A.K.S., Kumar, D.: Traffic density control and accident indicator using WSN. Int. J. Mod. Trends Sci. Technol. 2(4), 2455–3778 (2016)
Junping, Z., Feiue, W., Kunfeng, W., WeiHua, L., Xin, X., Cheng, C.: DataDriven intelligent transportation systems: survey. IEEE Trans. Intell. Transp. Syst. 12(4), 1624–1639 (2011)
Wiering, M., Veenen, J., Vreeken, J., Koopman, A.: Intelligent traffic light control, pp. 1–30, Technical report, Department of Information and Computing Sciences, Universiteit Utrecht, 9 July 2004
Calvert, S.C., Taale, H., Snelder, M., Hoogendoorn, S.P.: Improving traffic management through consideration of uncertainty and stochastics in traffic flow. Case Stud. Transp. Policy 6(1), 81–93 (2018)
Kim, S., Kim, D.-Y., Park, J.H.: Traffic management in the mobile edge cloud to improve the quality of experience of mobile video. Comput. Commun. 118, 40–49 (2018)
Latif, S., Afzaal, H., Zafar, N.A.: Intelligent traffic monitoring and guidance system for smart city. In: 2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), Sukkur, pp. 1–6 (2018)
Liu, H.Y., Skjetne, E., Kobernus, M.: Mobile phone tracking: in support of modelling traffic-related air pollution contribution to individual exposure and its implications for public health impact assessment. Environ. Health 12(1), 93 (2013)
Manikonda, P., Yerrapragada, A.K., Annasamudram, S.S.: Intelligent traffic management system. In: 2011 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology, 20–21 October 2011, Malaysia, pp. 119–122 (2011)
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Mandal, P., Chatterjee, P., Debnath, A. (2019). An Intelligent Highway Traffic Management System for Smart City. In: Arai, K., Bhatia, R., Kapoor, S. (eds) Intelligent Computing. CompCom 2019. Advances in Intelligent Systems and Computing, vol 997. Springer, Cham. https://doi.org/10.1007/978-3-030-22871-2_1
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DOI: https://doi.org/10.1007/978-3-030-22871-2_1
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