Accurate Traffic Prediction

Accurate traffic prediction aims to forecast traffic flow and congestion, enabling improved transportation management and urban planning. Current research heavily utilizes deep learning models, particularly graph neural networks (GNNs) and recurrent neural networks (RNNs) like LSTMs, often incorporating multi-granularity data and spatio-temporal dependencies to enhance prediction accuracy and reliability. These advancements are crucial for optimizing traffic control, improving navigation systems, and mitigating congestion, particularly in large-scale transportation networks and during emergency situations like hurricane evacuations. Furthermore, research is exploring techniques like transfer learning and multi-task learning to address data scarcity and improve model generalizability across different cities and scenarios.

Papers

September 26, 2024

A Time Series is Worth Five Experts: Heterogeneous Mixture of Experts for Traffic Flow Prediction
Guangyu Wang, Yujie Chen, Ming Gao, Zhiqiao Wu, Jiafu Tang, Jiabi Zhao
Expert Knowledge Traffic Prediction Object Centric Learning Traffic Flow Prediction Multiple Expert Heterogeneous Medium Accurate Traffic Prediction

August 23, 2024

Causally-Aware Spatio-Temporal Multi-Graph Convolution Network for Accurate and Reliable Traffic Prediction
Pingping Dong, Xiao-Lin Wang, Indranil Bose, Kam K. H. Ng, Xiaoning Zhang, Xiaoge Zhang
Traffic Prediction Accurate Traffic Prediction

June 17, 2024

Deploying scalable traffic prediction models for efficient management in real-world large transportation networks during hurricane evacuations
Qinhua Jiang, Brian Yueshuai He, Changju Lee, Jiaqi Ma
High Efficiency Traffic Forecasting Traffic Network Hurricane Evacuation Traffic Speed Accurate Traffic Prediction Traffic Volume Prediction

May 14, 2024

FLEXIBLE: Forecasting Cellular Traffic by Leveraging Explicit Inductive Graph-Based Learning
Duc Thinh Ngo, Kandaraj Piamrat, Ons Aouedi, Thomas Hassan, Philippe Raipin-Parvédy
Traffic Prediction Extension Study Spatio Temporal Forecasting Graph Based Learning Accurate Traffic Prediction Inductive Task

April 8, 2024

STMGF: An Effective Spatial-Temporal Multi-Granularity Framework for Traffic Forecasting
Zhengyang Zhao, Haitao Yuan, Nan Jiang, Minxiao Chen, Ning Liu, Zengxiang Li
Traffic Forecasting Traffic Data Road Network Accurate Traffic Prediction Traffic State Sequence

October 26, 2023

Improving Traffic Density Forecasting in Intelligent Transportation Systems Using Gated Graph Neural Networks
Razib Hayat Khan, Jonayet Miah, S M Yasir Arafat, M M Mahbubul Syeed, Duc M Ca
Graph Neural Network Traffic Prediction Traffic Forecasting Intelligent Transportation System Accurate Traffic Prediction

October 24, 2023

Enhancing Traffic Prediction with Learnable Filter Module
Yuanshao Zhu, Yongchao Ye, Xiangyu Zhao, James J. Q. Yu
Spatio Temporal Traffic Prediction Traffic Data Learnable Filter Accurate Traffic Prediction

February 23, 2023

Semantic-Fused Multi-Granularity Cross-City Traffic Prediction
Kehua Chen, Yuxuan Liang, Jindong Han, Siyuan Feng, Meixin Zhu, Hai Yang
Fine Grained Traffic Prediction Multi Granularity Semantic Fusion Accurate Traffic Prediction

February 21, 2023

A Dynamic Temporal Self-attention Graph Convolutional Network for Traffic Prediction
Ruiyuan Jiang, Shangbo Wang, Yuli Zhang
Long Short Term Memory Self Attention Traffic Datasets Accurate Traffic Prediction

December 13, 2022

Smart Journey in Istanbul: A Mobile Application in Smart Cities for Traffic Estimation by Harnessing Time Series
Senem Tanberk, Mustafa Can
Time Series Traffic Data Mobile Application Smart City Traffic Congestion Accurate Traffic Prediction Traffic Estimation

November 18, 2022

Multi-task Learning for Sparse Traffic Forecasting
Jiezhang Li, Junjun Li, Yue-Jiao Gong
Multi Task Learning Traffic Dynamic Traffic4cast Competition Accurate Traffic Prediction Future Traffic

October 31, 2022

Large scale traffic forecasting with gradient boosting, Traffic4cast 2022 challenge
Martin Lumiste, Andrei Ilie
Challenge Task Traffic Prediction Traffic Forecasting Gradient Boosting Traffic4cast Competition Accurate Traffic Prediction Accurate Traffic Forecasting

July 22, 2022

Automated Dilated Spatio-Temporal Synchronous Graph Modeling for Traffic Prediction
Guangyin Jin, Fuxian Li, Jinlei Zhang, Mudan Wang, Jincai Huang
Temporal Dependency Traffic Prediction Accurate Traffic Prediction

February 11, 2022

A Graph-based U-Net Model for Predicting Traffic in unseen Cities
Luca Hermes, Barbara Hammer, Andrew Melnik, Riza Velioglu, Markus Vieth, Malte Schilling
Traffic Forecasting Traffic Data Traffic Efficiency Spatial Generalization Accurate Traffic Prediction Road Topology Graph U Net

February 8, 2022

Domain Adversarial Spatial-Temporal Network: A Transferable Framework for Short-term Traffic Forecasting across Cities
Yihong Tang, Ao Qu, Andy H. F. Chow, William H. K. Lam, S. C. Wong, Wei Ma
Urban Environment Task Transferability Traffic Forecasting Internet Service Domain Accurate Traffic Prediction Accurate Traffic Forecasting Short Term Traffic Network Wide Traffic Transferable Time Series

November 3, 2021

Multistep traffic speed prediction: A deep learning based approach using latent space mapping considering spatio-temporal dependencies
Shatrughan Modi, Jhilik Bhattacharya, Prasenjit Basak
Latent Space Constructive Approach Temporal Dependency Traffic Prediction Traffic Flow Prediction Traffic Speed Accurate Traffic Prediction Accurate Traffic Forecasting

Accurate Traffic Prediction

Papers

A Time Series is Worth Five Experts: Heterogeneous Mixture of Experts for Traffic Flow Prediction

Causally-Aware Spatio-Temporal Multi-Graph Convolution Network for Accurate and Reliable Traffic Prediction

Deploying scalable traffic prediction models for efficient management in real-world large transportation networks during hurricane evacuations

FLEXIBLE: Forecasting Cellular Traffic by Leveraging Explicit Inductive Graph-Based Learning

STMGF: An Effective Spatial-Temporal Multi-Granularity Framework for Traffic Forecasting

Improving Traffic Density Forecasting in Intelligent Transportation Systems Using Gated Graph Neural Networks

Enhancing Traffic Prediction with Learnable Filter Module

Semantic-Fused Multi-Granularity Cross-City Traffic Prediction

A Dynamic Temporal Self-attention Graph Convolutional Network for Traffic Prediction

Smart Journey in Istanbul: A Mobile Application in Smart Cities for Traffic Estimation by Harnessing Time Series

Multi-task Learning for Sparse Traffic Forecasting

Large scale traffic forecasting with gradient boosting, Traffic4cast 2022 challenge

Automated Dilated Spatio-Temporal Synchronous Graph Modeling for Traffic Prediction

A Graph-based U-Net Model for Predicting Traffic in unseen Cities

Domain Adversarial Spatial-Temporal Network: A Transferable Framework for Short-term Traffic Forecasting across Cities

Multistep traffic speed prediction: A deep learning based approach using latent space mapping considering spatio-temporal dependencies