Mobile QR Code QR CODE

2024

Acceptance Ratio

21%

REFERENCES

1 
J. B. Chen, D. M. Li, G. L. Zhang, and X. L. Zhang, ``Localized space-time autoregressive parameters estimation for traffic flow prediction in urban road networks,'' Applied Sciences, vol. 8, no. 2, 20, 2018.DOI
2 
Z. Chen, Y. Jiang, and D. H. Sun, ``Discrimination and prediction of traffic congestion states of urban road network based on spatio-temporal correlation,'' IEEE Access, vol. 8, pp. 3330-3342, 2020.DOI
3 
W. Elleuch, A. Wali, and A. M. Alimi, ``Neural congestion prediction system for trip modelling in heterogeneous spatio-temporal patterns,'' International Journal of Systems Science, vol. 51, no. 8, pp. 1373-1391, 2020.DOI
4 
R. A. A. Khalil, ``Building the public transportation system in Libya,'' Engineering Heritage Journal, vol. 8, no. 1, pp. 7-12, 2024.DOI
5 
R, Feng, H. Q. Cui, Q. Feng, S. X. Chen, X. N. Gu, and B. Z. Yao, ``Urban traffic congestion level prediction using a fusion-based graph convolutional network,'' IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 12, pp. 14695-14705, 2023.DOI
6 
Y. J. Guo, L. C. Yang, S. X. Hao, and J. Gao, ``Dynamic identification of urban traffic congestion warning communities in heterogeneous networks,'' Physica A - Statistical Mechanics and Its Applications, vol. 522, pp. 98-111, 2019DOI
7 
W. B. Hu, H. Wang, Z. Y. Qiu, L. P. Yan, C. Nie, and B. Du, ``An urban traffic simulation model for traffic congestion predicting and avoiding,'' Neural Computing & Applications, vol. 30, no. 6, pp. 1769-1781, 2018.DOI
8 
D. R, Huang, Z. P. Deng, S. H. Wan, B. Mi, and Y. Liu, ``Identification and prediction of urban traffic congestion via cyber-physical link optimization,'' IEEE Access, vol. 6, pp. 63268-63278, 2018.DOI
9 
R, Jia, P. C. Jiang, L. Liu, L. Z. Cui, and Y. L. Shi, ``Data driven congestion trends prediction of urban transportation,'' IEEE Internet of Things Journal, vol. 5, no. 2, pp. 581-591, 2018.DOI
10 
U, Jilani, M. Asif, M. Y. I. Zia, M. Rashid, S. Shams, and P. Otero, ``A systematic review on urban road traffic congestion,'' Wireless Personal Communications, vol. 140, pp. 81-109, 2025.DOI
11 
M. Q, Lv, Y. F. Li, T. M. Chen, and Y. L. Li, ``Urban traffic congestion index estimation with open ubiquitous data,'' Journal of Information Science and Engineering, vol. 34, no. 3, pp. 781-799, 2018.DOI
12 
B. Medina-Salgado, E. Sanchez-DelaCruz, P. Pozos-Parra, and J. E. Sierra, ``Urban traffic flow prediction techniques: A review,'' Sustainable Computing-Informatics & Systems, vol. 35, 100739, 2022.DOI
13 
E. E. Mon, H. Ochiai, C. Saivichit, and C. Aswakul, ``Bottleneck based gridlock prediction in an urban road network using long short-term memory,'' Electronics, vol. 9, no. 9, 1412, 2020.DOI
14 
M. Pi, H. Yeon, H. Son, and Y. Jang, ``Visual cause analytics for traffic congestion,'' IEEE Transactions on Visualization and Computer Graphics, vol. 27, no. 3, pp. 2186-2201, 2021.DOI
15 
B. Priambodo, A. Ahmad, and R. A. Kadir, ``Predicting traffic flow propagation based on congestion at neighbouring roads using hidden Markov model,'' IEEE Access, vol. 9, pp. 85933-85946, 2021.DOI
16 
K. Ramana, G. Srivastava, M. R. Kumar, T. R. Gadekallu, J. C. W. Lin, M. Alazab, and C. Iwendi, ``A vision transformer approach for traffic congestion prediction in urban areas,'' IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 4, pp. 3922-3934, 2023.DOI
17 
N. Ranjan, S. Bhandari, P. Khan, Y. S. Hong, and H. Kim, ``Large-scale road network congestion pattern analysis and prediction using deep convolutional autoencoder,'' Sustainability, vol. 13, no. 9, 5108, 2021.DOI
18 
S. Ranjan, Y. C. Kim, N. Ranjan, S. Bhandari, and H. Kim, ``Large-scale road network traffic congestion prediction based on recurrent high-resolution network,'' Applied Sciences, vol. 13, no. 9, 5512, 2023.DOI
19 
I. Stan, D. A. Ghere, P. I. Dan, and R. Potolea, ``Urban congestion avoidance methodology based on vehicular traffic thresholding,'' Applied Sciences, vol. 13, no. 4, 2143, 2023.DOI
20 
N. Wang, B. H. Zhang, J. Gu, H. H. Kong, S. Hu, and S. C. Lu, ``Urban road traffic spatiotemporal state estimation based on multivariate phase space-LSTM prediction,'' Applied Sciences, vol. 13, no. 21, 12079, 2023.DOI
21 
X. Wang, R. H. Zeng, F. M. Zou, L. Y. C. Liao, and F. L. Huang, ``STTF: An efficient transformer model for traffic congestion prediction,'' International Journal of Computational Intelligence Systems, vol. 16, 2, 2023.DOI
22 
X. M. Wang, Y. Chen, and J. L. Zhang, ``Urban-road average-speed prediction method based on graph convolutional networks,'' Transportation Research Record, vol. 2678, no. 5, pp. 771-788, 2024.DOI
23 
D. W. Xia, B. Q. Shen, J. Geng, Y. Hu, Y. T. Li, and H. Q. Li, ``Attention-based spatial-temporal adaptive dual-graph convolutional network for traffic flow forecasting,'' Neural Computing & Applications, vol. 35, pp. 17217-17231, 2023.DOI
24 
Z. P. Xie, W. F. Lv, S. F. Huang, Z. L. Lu, B. W. Du, and R. H. Huang, ``Sequential graph neural network for urban road traffic speed prediction,'' IEEE Access, vol. 8, pp. 63349-63358, 2020.DOI
25 
X. Xing and X. Y. Li, ``Recommendation of urban vehicle driving routes under traffic congestion: A traffic congestion regulation method considering road network equilibrium,'' Computers & Electrical Engineering, vol. 110, 108863, 2023.DOI
26 
Y. M. Xing, X. J. Ban, X. Liu, and Q. Shen, ``Large-scale traffic congestion prediction based on the symmetric extreme learning machine cluster fast learning method,'' Symmetry-Basel, vol. 11, no. 6, 730, 2019.DOI
27 
B. Yang, H. Zhang, M. X. Du, A. N. Wang, and K. Xiong, ``Urban traffic congestion alleviation system based on millimeter wave radar and improved probabilistic neural network,'' IET Radar Sonar and Navigation, vol. 18, no. 2, pp. 327-343, 2024.DOI
28 
K. Zhang, Z. X. Chu, J. P. Xing, H. G. Zhang, and Q. X. Cheng, ``Urban traffic flow congestion prediction based on a data-driven model,'' Mathematics, vol. 11, no. 19, 4075, 2023.DOI
29 
T. R. Zhang, J. A. Xu, S. R. Cong, C. S. Qu, and W. B. Zhao, ``A hybrid method of traffic congestion prediction and control,'' IEEE Access, vol. 11, pp. 36471-36491, 2023.DOI
30 
X. Y. Zheng, N. Huang, Y. N. Bai, and X. Zhang, ``A traffic-fractal-element-based congestion model considering the uneven distribution of road traffic,'' Physica A - Statistical Mechanics and Its Applications, vol. 632, no. Part 1, pp. 129354, 2023.DOI
31 
Z. J. Zheng, Z. L. Wang, S. Liu, and W. Ma, ``Exploring The spatial effects on the level of congestion caused by traffic accidents in urban road networks: A case study of Beijing,'' Travel Behaviour and Society, vol. 35, 100728, 2024.DOI