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README.md
README.md
 
 

README.md

This is the folder for the relevant surveys.

2020

  • Yin X, Wu G, Wei J, et al. A Comprehensive Survey on Traffic Prediction[J]. arXiv preprint arXiv:2004.08555, 2020. Link

  • Luca M, Barlacchi G, Lepri B, et al. Deep Learning for Human Mobility: a Survey on Data and Models[J]. arXiv preprint arXiv:2012.02825, 2020. Link

  • Fan X, Xiang C, Gong L, et al. Deep learning for intelligent traffic sensing and prediction: recent advances and future challenges[J]. CCF Transactions on Pervasive Computing and Interaction, 2020: 1-21. Link

  • Boukerche A, Wang J. Machine Learning-based traffic prediction models for Intelligent Transportation Systems[J]. Computer Networks, 2020, 181: 107530. Link

  • Manibardo E L, Laña I, Del Ser J. Deep Learning for Road Traffic Forecasting: Does it Make a Difference?[J]. arXiv preprint arXiv:2012.02260, 2020. Link

  • Ye J, Zhao J, Ye K, et al. How to Build a Graph-Based Deep Learning Architecture in Traffic Domain: A Survey[J]. arXiv preprint arXiv:2005.11691, 2020. Link

  • Lee K, Eo M, Jung E, et al. Short-term Traffic Prediction with Deep Neural Networks: A Survey[J]. arXiv preprint arXiv:2009.00712, 2020. Link

  • Xie P, Li T, Liu J, et al. Urban flow prediction from spatiotemporal data using machine learning: A survey[J]. Information Fusion, 2020, 59: 1-12. Link

  • George S, Santra A K. Traffic Prediction Using Multifaceted Techniques: A Survey[J]. Wireless Personal Communications, 2020, 115(2): 1047-1106. Link

  • Haghighat A K, Ravichandra-Mouli V, Chakraborty P, et al. Applications of Deep Learning in Intelligent Transportation Systems[J]. Journal of Big Data Analytics in Transportation, 2020, 2(2): 115-145. Link

  • Boukerche A, Tao Y, Sun P. Artificial intelligence-based vehicular traffic flow prediction methods for supporting intelligent transportation systems[J]. Computer Networks, 2020, 182: 107484. Link

  • Tedjopurnomo D A, Bao Z, Zheng B, et al. A survey on modern deep neural network for traffic prediction: Trends, methods and challenges[J]. IEEE Transactions on Knowledge and Data Engineering, 2020. Link

  • Varghese V, Chikaraishi M, Urata J. Deep Learning in Transport Studies: A Meta-analysis on the Prediction Accuracy[J]. Journal of Big Data Analytics in Transportation, 2020: 1-22. Link

2019

  • Pavlyuk D. Feature selection and extraction in spatiotemporal traffic forecasting: a systematic literature review[J]. European Transport Research Review, 2019, 11(1): 6. Link

2018

  • Shi X, Yeung D Y. Machine learning for spatiotemporal sequence forecasting: A survey[J]. arXiv preprint arXiv:1808.06865, 2018. Link