Deep learning on traffic prediction: Methods, analysis, and future directions

X Yin, G Wu, J Wei, Y Shen, H Qi… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Traffic prediction plays an essential role in intelligent transportation system. Accurate traffic
prediction can assist route planing, guide vehicle dispatching, and mitigate traffic …

[HTML][HTML] Long-term traffic flow forecasting using a hybrid CNN-BiLSTM model

M Méndez, MG Merayo, M Núñez - Engineering Applications of Artificial …, 2023 - Elsevier
The increase of road traffic in large cities during the last years has produced that long and
short-term traffic flow forecasting is a critical need for the authorities. The availability of good …

Real‐World Wireless Network Modeling and Optimization: From Model/Data‐Driven Perspective

Y Li, S Zhang, X Ren, J Zhu, J Huang… - Chinese Journal of …, 2022 - Wiley Online Library
With the rapid development of the fifthgeneration wireless communication systems, a
profound revolution in terms of transmission capacity, energy efficiency, reliability, latency …

[HTML][HTML] Predicting traffic propagation flow in urban road network with multi-graph convolutional network

H Yang, Z Li, Y Qi - Complex & Intelligent Systems, 2024 - Springer
Traffic volume propagating from upstream road link to downstream road link is the key
parameter for designing intersection signal timing scheme. Recent works successfully used …

MobTCast: Leveraging auxiliary trajectory forecasting for human mobility prediction

H Xue, F Salim, Y Ren, N Oliver - Advances in Neural …, 2021 - proceedings.neurips.cc
Human mobility prediction is a core functionality in many location-based services and
applications. However, due to the sparsity of mobility data, it is not an easy task to predict …

Improving short-term bike sharing demand forecast through an irregular convolutional neural network

X Li, Y Xu, X Zhang, W Shi, Y Yue, Q Li - Transportation research part C …, 2023 - Elsevier
As an important task for the management of bike sharing systems, accurate forecast of travel
demand could facilitate dispatch and relocation of bicycles to improve user satisfaction. In …

Modeling multi-regional temporal correlation with gated recurrent unit and multiple linear regression for urban traffic flow prediction

TM Rajeh, T Li, C Li, MH Javed, Z Luo… - Knowledge-Based Systems, 2023 - Elsevier
Urban traffic flow prediction has received much attention in the past few years, especially
after the availability of huge traffic data. In addition, the efficacy of some existing traffic flow …

Multisize patched spatial-temporal transformer network for short-and long-term crowd flow prediction

Y Xie, J Niu, Y Zhang, F Ren - IEEE Transactions on Intelligent …, 2022 - ieeexplore.ieee.org
The prediction of urban crowds is crucial not only to traffic management but also to studies
on the city-level social phenomena, such as energy consumption, urban growth, city …

[HTML][HTML] Road traffic can be predicted by machine learning equally effectively as by complex microscopic model

A Sroczyński, A Czyżewski - Scientific reports, 2023 - nature.com
Since high-quality real data acquired from selected road sections are not always available, a
traffic control solution can use data from software traffic simulators working offline. The …

A deep learning approach for long-term traffic flow prediction with multifactor fusion using spatiotemporal graph convolutional network

X Qi, G Mei, J Tu, N Xi, F Piccialli - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
As a vital research subject in the field of intelligent transportation systems (ITSs), traffic flow
prediction using deep learning methods has attracted much attention in recent years …