Short Term Traffic

Short-term traffic flow prediction aims to accurately forecast traffic conditions within a short timeframe, crucial for optimizing transportation systems and mitigating congestion. Current research heavily utilizes deep learning models, particularly recurrent neural networks (like LSTMs) and graph convolutional networks (GCNs), often incorporating techniques like hierarchical structures, attention mechanisms, and ensemble methods to improve accuracy and address challenges like non-stationarity and data sparsity. These advancements are improving the precision and reliability of traffic forecasts, leading to more efficient traffic management, better infrastructure planning, and enhanced real-time navigation systems. Furthermore, research is actively exploring methods to improve model transferability across different cities and incorporate diverse data sources, such as textual information and weather data, for more robust predictions.

Papers

October 16, 2024

Incorporating Long-term Data in Training Short-term Traffic Prediction Model
Xiannan Huang, Shuhan Qiu, Yan Cheng, Quan Yuan, Chao Yang
Training Data Full Model Long Term Traffic Prediction Short Term Traffic Traffic State Sequence

May 10, 2024

Enhancing Traffic Prediction with Textual Data Using Large Language Models
Xiannan Huang
Traffic Prediction Traffic Data Spatiotemporal Forecasting Short Term Traffic

July 27, 2023

HUTFormer: Hierarchical U-Net Transformer for Long-Term Traffic Forecasting
Zezhi Shao, Fei Wang, Zhao Zhang, Yuchen Fang, Guangyin Jin, Yongjun Xu
Traffic Forecasting Hierarchical Transformer Short Term Traffic Long Term Traffic Forecasting

July 11, 2023

Hybrid hidden Markov LSTM for short-term traffic flow prediction
Agnimitra Sengupta, Adway Das, S. Ilgin Guler
Recurrent Neural Network Long Short Term Memory LSTM Network Efficient Hybrid Traffic Flow Prediction Traffic Dynamic Short Term Traffic

March 31, 2023

A Slow-Shifting Concerned Machine Learning Method for Short-term Traffic Flow Forecasting
Zann Koh, Yan Qin, Yong Liang Guan, Chau Yuen
Machine Learning Traffic Data Traffic Flow Traffic Flow Forecasting Traffic Light Short Term Traffic

November 13, 2022

Similarity-based Feature Extraction for Large-scale Sparse Traffic Forecasting
Xinhua Wu, Cheng Lyu, Qing-Long Lu, Vishal Mahajan
Feature Extraction Traffic4cast Competition Travel Time Estimation Short Term Traffic Estimated Time of Arrival

October 24, 2022

Exploring the impact of weather on Metro demand forecasting using machine learning method
Yiming Hu, Yangchuan Huang, Shuying Liu, Yuanyang Qi, Danhui Bai
Machine Learning Global Impact Passenger Flow Short Term Traffic Urban Rail Transit Passenger Flow Prediction

September 27, 2022

Explainable Graph Pyramid Autoformer for Long-Term Traffic Forecasting
Weiheng Zhong, Tanwi Mallick, Hadi Meidani, Jane Macfarlane, Prasanna Balaprakash
Accurate Traffic Forecasting Short Term Traffic Long Term Traffic Forecasting

May 10, 2022

A spatial-temporal short-term traffic flow prediction model based on dynamical-learning graph convolution mechanism
Zhijun Chen, Zhe Lu, Qiushi Chen, Hongliang Zhong, Yishi Zhang, Jie Xue, Chaozhong Wu
Graph Convolution Traffic Prediction Short Term Traffic

May 1, 2022

Accurate non-stationary short-term traffic flow prediction method
Wenzheng Zhao
Long Short Term Memory Traffic Datasets Short Term Traffic

April 4, 2022

Deep-Ensemble-Based Uncertainty Quantification in Spatiotemporal Graph Neural Networks for Traffic Forecasting
Tanwi Mallick, Prasanna Balaprakash, Jane Macfarlane
Uncertainty Quantification Traffic Forecasting Convolutional Recurrent Short Term Traffic Spatiotemporal Graph Neural Network Diffusion Convolutional Recurrent Neural Network

March 8, 2022

Few-Sample Traffic Prediction with Graph Networks using Locale as Relational Inductive Biases
Mingxi Li, Yihong Tang, Wei Ma
Inductive Bias Traffic Prediction Graph Network Short Term Traffic

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 Transferable Time Series Network Wide Traffic

November 27, 2021

Learning to Transfer for Traffic Forecasting via Multi-task Learning
Yichao Lu
LeArning Abstract Multi Task Learning Traffic Forecasting Traffic4cast Competition Short Term Traffic