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SE-MAConvLSTM: A deep learning framework for short-term traffic flow prediction combining Squeeze-and-Excitation Network and Multi-Attention Convolutional LSTM Network. [PDF]
PLoS OneZhu R +6 more
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ST-D3DDARN: Urban traffic flow prediction based on spatio-temporal decoupled 3D DenseNet with attention ResNet. [PDF]
PLoS OneChen J, Yang G, Zhang Z, Wang W.
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Traffic Flow Prediction with Vehicle Trajectories
Proceedings of the AAAI Conference on Artificial Intelligence, 2021This paper proposes a spatiotemporal deep learning framework, Trajectory-based Graph Neural Network (TrGNN), that mines the underlying causality of flows from historical vehicle trajectories and incorporates that into road traffic prediction. The vehicle trajectory transition patterns are studied to explicitly model the spatial traffic demand via graph
Mingqian Li +5 more
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Fuzzy Prediction of Metro Traffic Flow
2019 International Conference on Fuzzy Theory and Its Applications (iFUZZY), 2019With the rapid development of urban metro traffic, the prediction and evacuation of metro pedestrian flow is of great significance to metro traffic scheduling. In this paper, the fuzzy logic method is used to predict and simulate the pedestrian flow of the metro, which is feasible to predict the pedestrian flow of the metro station and provide a ...
Huan Wen, Xuanming Zhao, Xinchao Chen
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Short-term traffic flow prediction: From the perspective of traffic flow decomposition
Neurocomputing, 2020Abstract Some researchers treat traffic flow as an entirety while predicting short-term traffic flow. Through analyzing real-world traffic flow, we have found that urban traffic shows a stable changing process along with random disturbs. An alternative way is to decompose traffic flow into two components: periodicity and volatility.
Li Chen +4 more
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Predicting information flows in network traffic
Journal of the American Society for Information Science and Technology, 2002AbstractIn optimizing information flows in networks, it would be useful to predict aspects of the network traffic. Yet, the notion of predicting network traffic does not appear in the relevant literature reporting analysis of network traffic. This literature is both well developed and skeptical about the value of traditional time series analysis on ...
Melvin J. Hinich, Robert E. Molyneux
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Traffic Flow Prediction with Parallel Data
2018 21st International Conference on Intelligent Transportation Systems (ITSC), 2018Traffic prediction is an elemental function of Intelligent Transportation Systems, and accurate and timely prediction is of great significance to both traffic management agencies and individual drivers. With the development of deep learning and big data, deep neural networks (DNN) achieve superior performances in traffic prediction.
Yuanyuan Chen 0003 +3 more
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Utilizing Automatic Traffic Counters to Predict Traffic Flow Speed
2019 12th International Conference on Developments in eSystems Engineering (DeSE), 2019In the era of the Fourth Industrial Revolution, one of the key drivers of change is a sharing economy or so called “uberization”. Uberization is especially rapidly developing in the service sector, in particular – when organizing individual passenger transportation by taxi services.
Ahmed Adnan Makki +4 more
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An Intelligent Combination Algorithm for Traffic Flow Prediction
2020 7th International Conference on Dependable Systems and Their Applications (DSA), 2020The research on traffic flow prediction has gained the considerable social value, especially for the short-term traffic flow prediction. The prediction of traffic flow is the theoretical basis of intelligent transportation as well as the key technology in traffic flow induction system.
Cheng Li, Liang Kou, Xu Zhang
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