Development of traffic congestion prediction Solution using Cellular Neural Network technology
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[1] Khadka, S.R.: Optimal traffic planning for efficient evacuation. J. Adv. College Eng. Manag. 1, 119–126 (2015)
[2] Shan, Z., Zhu, Q.: Camera location for real-time traffic state estimation in urban road network using big GPS data. ELSEVIER, 134–143 (2015)
[3] Varga, N., Bokor, L., Takács, A., Kovács, J., Virág, L.: An architecture proposal for v2x communication-centric traffic light controller systems. In: ITS Telecommunications (ITST) 15th International Conference on IEEE, pp. 1–7 (2017)
[4] Ermagun, A., Levinson, D.: Spatiotemporal traffic forecasting: review and proposed directions. Transp. Rev. 786–814 (2018)
[5] Mohamed, K., Côme, E., Oukhellou, L., Verleysen, M.: Clustering smart card data for urban mobility analysis. IEEE Trans. Intell. Transp. Syst. 18(3), 712–728 (2017)
[6] Ma, X., Dai, Z., He, Z., Ma, J., Wang, Y., Wang, Y.: Learning traffic as images: a deep convolutional neural network for large-scale transportation network speed prediction. https://arxiv.org/abs/1701.04245 (2017)
[7] Nguyen, D.-B., Dow, C.-R., Hwang, S.-F.: An efficient traffic congestion monitoring system on internet of vehicles. Hindawi Wirel. Commun. Mobile Comput. 1–17 (2018)
[8] Wang, Z., Wang, K., Zhang, H.: Application of mathematical model in road traffic control at circular intersection. In: International Conference on Information Computing and Applications, ICIA201, pp. 436–443 (2010)
[9] Kiselev, A.B., Kokoreva, A.V., Nikitin, V.E., Smirnov, N.N.: Mathematical, modelling of traffic flows on controlled roads. J. Appl. Math. Mech. 68, 933–939 (2004)
[10] Junevičius, R., Bogdevičius, M.: Mathematical modelling of network traffic flow. J. Transp. 333–338 (2010)
[11] Rajendran, S., Ayyasamy, B.: Short-term traffic prediction model for urban transportation using structure pattern and regression: an Indian contex. Appl. Sci. 2, 1–11 (2020)
[12] Thai, V.D., Dung, N.D., Tu, L.A.: Some numerical results for the problem of determining the density of vehicles. In: National Conference Selected issues of information and communication, (VNICT2021), pp. 288–294 (2021)
[13] Thai, V.D., Trung, L.V., Ha, L.M.: Solution to determine the optimal route for means of transport. In: National Conference Selected Issues of Information and Communication, (VNICT2021), pp. 142–147 (2021)
[14] Thai, V.D., Linh, L.H., Linh, N.M.: Solving Navier-stokes equation using FPGA cellular neural network chip. In: International Conference on Advances in Information and Communication Technology, ICTA2016, pp. 562–571. Springer Publishing (2016)
[15] Thai, V.D., Tung, B.V.: Solving partial differential equation using FPGA technology. In: Boundary Layer Flows - Theory, Applications and Numerical Methods (2019)