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PDFormer: Propagation Delay-aware Dynamic Long-range Transformer for Traffic Flow Prediction [PDF]
AAAI Conference on Artificial Intelligence, 2023 As a core technology of Intelligent Transportation System, traffic flow prediction has a wide range of applications. The fundamental challenge in traffic flow prediction is to effectively model the complex spatial-temporal dependencies in traffic data ...
Jiawei Jiang +3 more
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ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic Classification [PDF]
The Web Conference, 2022 Encrypted traffic classification requires discriminative and robust traffic representation captured from content-invisible and imbalanced traffic data for accurate classification, which is challenging but indispensable to achieve network security and ...
Xinjie Lin +5 more
semanticscholar +1 more source
Spatio-temporal Graph Convolutional Neural Network: A Deep Learning Framework for Traffic Forecasting [PDF]
International Joint Conference on Artificial Intelligence, 2017 Timely accurate traffic forecast is crucial for urban traffic control and guidance. Due to the high nonlinearity and complexity of traffic flow, traditional methods cannot satisfy the requirements of mid-and-long term prediction tasks and often neglect ...
Ting Yu, Haoteng Yin, Zhanxing Zhu
semanticscholar +1 more source
Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting [PDF]
Knowledge Discovery and Data Mining, 2021 Spatial-temporal forecasting has attracted tremendous attention in a wide range of applications, and traffic flow prediction is a canonical and typical example.
Zheng Fang +3 more
semanticscholar +1 more source
Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution [PDF]
ACM Transactions on Knowledge Discovery from Data, 2021 Traffic prediction is the cornerstone of intelligent transportation system. Accurate traffic forecasting is essential for the applications of smart cities, i.e., intelligent traffic management and urban planning. Although various methods are proposed for
Fuxian Li +5 more
semanticscholar +1 more source
T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction [PDF]
IEEE transactions on intelligent transportation systems (Print), 2018 Accurate and real-time traffic forecasting plays an important role in the intelligent traffic system and is of great significance for urban traffic planning, traffic management, and traffic control. However, traffic forecasting has always been considered
Ling Zhao +7 more
semanticscholar +1 more source
Improved F-RRT∗ Algorithm for Flight-Path Optimization in Hazardous Weather
International Journal of Aerospace Engineering, 2022 Hazardous weather has become a major cause of flight delays in recent years. With the development of satellite navigation systems, the study of flight-path optimization under hazardous weather conditions has become especially important.
Xue Qiu +6 more
doaj +1 more source
Congested traffic states in empirical observations and microscopic simulations [PDF]
Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics, 2000 We present data from several German freeways showing different kinds of congested traffic forming near road inhomogeneities, specifically lane closings, intersections, or uphill gradients. The states are localized or extended, homogeneous or oscillating.
M. Treiber, Ansgar Hennecke, D. Helbing
semanticscholar +1 more source
Collaborate or Compete? Time-Varying Incentives versus Tolling in Parallel Bottleneck
Journal of Advanced Transportation, 2023 Incentive-based traffic demand management (IBTDM) schemes redistribute traffic demand across space and time. The relationship between IBTDM and traditional tolling programs impacts financial sustainability and decision making of both programs. This study
Lin Xiao +4 more
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Journal of Advanced Transportation, 2023 Vehicle detection and tracking from unmanned aerial vehicles (UAVs) aerial images are among the main tasks of intelligent traffic systems. Especially in tasks with long distances, extensive backgrounds, and small objects, it increases the difficulty of ...
Heshan Zhang +6 more
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