Results 1 to 10 of about 10,448 (165)
Improving Road Traffic Forecasting Using Air Pollution and Atmospheric Data: Experiments Based on LSTM Recurrent Neural Networks [PDF]
Sensors, 2020 Traffic flow forecasting is one of the most important use cases related to smart cities. In addition to assisting traffic management authorities, traffic forecasting can help drivers to choose the best path to their destinations.
Faraz Malik Awan +2 more
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ADSTGCN: A Dynamic Adaptive Deeper Spatio-Temporal Graph Convolutional Network for Multi-Step Traffic Forecasting [PDF]
Sensors, 2023 Multi-step traffic forecasting has always been extremely challenging due to constantly changing traffic conditions. Advanced Graph Convolutional Networks (GCNs) are widely used to extract spatial information from traffic networks.
Zhengyan Cui +3 more
doaj +2 more sources
Graph neural network for traffic forecasting: A survey
Expert Systems With Applications, 2022 Traffic forecasting is important for the success of intelligent transportation systems. Deep learning models, including convolution neural networks and recurrent neural networks, have been extensively applied in traffic forecasting problems to model spatial and temporal dependencies.
Weiwei Jiang
exaly +4 more sources
An Overview Based on the Overall Architecture of Traffic Forecasting
Data Science and EngineeringWith the exponential increase in the urban population, urban transportation systems are confronted with numerous challenges. Traffic congestion is common, traffic accidents happen frequently, and traffic environments are deteriorating. To alleviate these
Lilan Peng +4 more
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Dual Graph for Traffic Forecasting
IEEE AccessTraffic forecasting is the task of predicting future traffic based on historical traffic data. It is challenging due to the complex spatial-temporal correlation on road networks.
Long Wei +7 more
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The changing accuracy of traffic forecasts [PDF]
Transportation, 2021 Researchers have improved travel demand forecasting methods in recent decades but invested relatively little to understand their accuracy. A major barrier has been the lack of necessary data. We compiled the largest known database of traffic forecast accuracy, composed of forecast traffic, post-opening counts and project attributes for 1291 road ...
Jawad Mahmud Hoque +6 more
openaire +4 more sources
Traffic Forecasting on Traffic Moving Snippets
CoRR, 2021 arXiv
Wiedemann, Nina +1 more
openaire +5 more sources
Attention Gate in Traffic Forecasting
CoRR, 2021 Because of increased urban complexity and growing populations, more and more challenges about predicting city-wide mobility behavior are being organized. Traffic Map Movie Forecasting Challenge 2020 is secondly held in the competition track of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS). Similar to Traffic4Cast 2019,
Anh Lam, Anh Nguyen 0003, Bac Le
openaire +3 more sources
Collective Traffic Forecasting [PDF]
, 2010 Traffic forecasting has recently become a crucial task in the area of intelligent transportation systems, and in particular in the development of traffic management and control. We focus on the simultaneous prediction of the congestion state at multiple lead times and at multiple nodes of a transport network, given historical and recent information ...
LIPPI, MARCO +2 more
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Local and Global Spatial-Temporal Networks for Traffic Accident Risk Forecasting
Jisuanji kexue yu tansuo, 2021 Traffic accident forecasting is very important for urban public security, emergency treatment and construc-tion planning. However, the following problems still exist when forecasting traffic accident risk.
WANG Beibei, WAN Huaiyu, GUO Shengnan, LIN Youfang
doaj +1 more source