Traffic Forecasting

Traffic forecasting aims to predict future traffic conditions using historical data and potentially external factors, enabling efficient resource allocation and improved transportation management. Current research heavily utilizes deep learning, focusing on graph neural networks (GNNs) and transformers, often combined to leverage both spatial and temporal dependencies within road networks, with a growing emphasis on handling data heterogeneity, out-of-distribution scenarios, and limited sensor coverage. These advancements hold significant potential for improving urban planning, optimizing traffic flow, and enhancing the efficiency of intelligent transportation systems.

Papers

May 8, 2024

RACH Traffic Prediction in Massive Machine Type Communications
Hossein Mehri, Hao Chen, Hani Mehrpouyan
Traffic Forecasting Traffic Pattern Massive Machine Type Communication

May 1, 2024

April 18, 2024

DST-GTN: Dynamic Spatio-Temporal Graph Transformer Network for Traffic Forecasting
Songtao Huang, Hongjin Song, Tianqi Jiang, Akbar Telikani, Jun Shen, Qingguo Zhou, Binbin Yong, Qiang Wu
Graph Transformer Traffic Forecasting Traffic Data Accurate Traffic Forecasting

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

April 3, 2024

Towards Explainable Traffic Flow Prediction with Large Language Models
Xusen Guo, Qiming Zhang, Junyue Jiang, Mingxing Peng, Meixin Zhu, Hao (Frank)Yang
Traffic Prediction Traffic Forecasting Traffic Flow Prediction Traffic Flow Forecasting

March 4, 2024

TPLLM: A Traffic Prediction Framework Based on Pretrained Large Language Models
Yilong Ren, Yue Chen, Shuai Liu, Boyue Wang, Haiyang Yu, Zhiyong Cui
Traffic Prediction Traffic Forecasting Traffic Data Pre Trained Large Language Model

March 2, 2024

COOL: A Conjoint Perspective on Spatio-Temporal Graph Neural Network for Traffic Forecasting
Wei Ju, Yusheng Zhao, Yifang Qin, Siyu Yi, Jingyang Yuan, Zhiping Xiao, Xiao Luo, Xiting Yan, Ming Zhang
Heterogeneous Graph Traffic Forecasting Temporal Graph Neural Network Spatio Temporal Graph Spatio Temporal Relationship

February 8, 2024

Mesoscale Traffic Forecasting for Real-Time Bottleneck and Shockwave Prediction
Raphael Chekroun, Han Wang, Jonathan Lee, Marin Toromanoff, Sascha Hornauer, Fabien Moutarde, Maria Laura Delle Monache
Traffic Forecasting Traffic State Estimation Shock Wave Traffic Volume Prediction

February 2, 2024

Unveiling Delay Effects in Traffic Forecasting: A Perspective from Spatial-Temporal Delay Differential Equations
Qingqing Long, Zheng Fang, Chen Fang, Chong Chen, Pengfei Wang, Yuanchun Zhou
Graph Neural Network Visual Perspective Traffic Forecasting Spatio Temporal Prediction Traffic Flow Forecasting Unveiling Camouflaged Object Delay Differential Equation

February 1, 2024

Multi-scale Traffic Pattern Bank for Cross-city Few-shot Traffic Forecasting
Zhanyu Liu, Guanjie Zheng, Yanwei Yu
Traffic Forecasting Traffic Data Traffic Datasets Multi Scale Traffic Cross City Few Shot

January 26, 2024

Continuously Evolving Graph Neural Controlled Differential Equations for Traffic Forecasting
Jiajia Wu, Ling Chen
Temporal Dependency Traffic Forecasting Traffic Network

January 22, 2024

Knowledge Distillation on Spatial-Temporal Graph Convolutional Network for Traffic Prediction
Mohammad Izadi, Mehran Safayani, Abdolreza Mirzaei
Knowledge Distillation Traffic Prediction Traffic Forecasting Spatio Temporal Graph Spatial Temporal Graph Real Time Traffic

January 19, 2024

Spatial-temporal Forecasting for Regions without Observations
Xinyu Su, Jianzhong Qi, Egemen Tanin, Yanchuan Chang, Majid Sarvi
Region Specific Traffic Forecasting Evolving Observation Spatio Temporal Forecasting Spatiotemporal Pattern Air Quality Forecasting

January 16, 2024

SpecSTG: A Fast Spectral Diffusion Framework for Probabilistic Spatio-Temporal Traffic Forecasting
Lequan Lin, Dai Shi, Andi Han, Junbin Gao
Traffic Forecasting Traffic Datasets Spatio Temporal Graph Temporal Traffic Spectral Graph Convolution Spectral Diffusion

January 11, 2024

Wavelet-Inspired Multiscale Graph Convolutional Recurrent Network for Traffic Forecasting
Qipeng Qian, Tanwi Mallick
Graph Neural Network Traffic Forecasting Spatiotemporal Graph

January 1, 2024

Graph Neural Networks in Intelligent Transportation Systems: Advances, Applications and Trends
Hourun Li, Yusheng Zhao, Zhengyang Mao, Yifang Qin, Zhiping Xiao, Jiaqi Feng, Yiyang Gu, Wei Ju, Xiao Luo, Ming Zhang
Graph Neural Network Timely Survey Traffic Forecasting Intelligent Transportation System Traffic Network

December 19, 2023

Dynamic Frequency Domain Graph Convolutional Network for Traffic Forecasting
Yujie Li, Zezhi Shao, Yongjun Xu, Qiang Qiu, Zhaogang Cao, Fei Wang
Dynamic Graph Graph Convolution Traffic Prediction Traffic Forecasting Traffic Data Spatial Dependence

December 14, 2023

A Sparse Cross Attention-based Graph Convolution Network with Auxiliary Information Awareness for Traffic Flow Prediction
Lingqiang Chen, Qinglin Zhao, Guanghui Li, Mengchu Zhou, Chenglong Dai, Yiming Feng
Many Sparse Graph Convolutional Network Graph Convolution Traffic Forecasting Traffic Flow Prediction Graph Convolutional Auxiliary Information GCN Based

December 6, 2023

Adaptive Dependency Learning Graph Neural Networks
Abishek Sriramulu, Nicolas Fourrier, Christoph Bergmeir
Graph Neural Network Traffic Forecasting Multivariate Forecasting

Traffic Forecasting

Papers

RACH Traffic Prediction in Massive Machine Type Communications

WEST GCN-LSTM: Weighted Stacked Spatio-Temporal Graph Neural Networks for Regional Traffic Forecasting

Counterfactual Explanations for Deep Learning-Based Traffic Forecasting

DST-GTN: Dynamic Spatio-Temporal Graph Transformer Network for Traffic Forecasting

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

Towards Explainable Traffic Flow Prediction with Large Language Models

TPLLM: A Traffic Prediction Framework Based on Pretrained Large Language Models

COOL: A Conjoint Perspective on Spatio-Temporal Graph Neural Network for Traffic Forecasting

Mesoscale Traffic Forecasting for Real-Time Bottleneck and Shockwave Prediction

Unveiling Delay Effects in Traffic Forecasting: A Perspective from Spatial-Temporal Delay Differential Equations

Multi-scale Traffic Pattern Bank for Cross-city Few-shot Traffic Forecasting

Continuously Evolving Graph Neural Controlled Differential Equations for Traffic Forecasting

Knowledge Distillation on Spatial-Temporal Graph Convolutional Network for Traffic Prediction

Spatial-temporal Forecasting for Regions without Observations

SpecSTG: A Fast Spectral Diffusion Framework for Probabilistic Spatio-Temporal Traffic Forecasting

Wavelet-Inspired Multiscale Graph Convolutional Recurrent Network for Traffic Forecasting

Graph Neural Networks in Intelligent Transportation Systems: Advances, Applications and Trends

Dynamic Frequency Domain Graph Convolutional Network for Traffic Forecasting

A Sparse Cross Attention-based Graph Convolution Network with Auxiliary Information Awareness for Traffic Flow Prediction

Adaptive Dependency Learning Graph Neural Networks