Traffic Congestion Prediction

Traffic congestion prediction aims to forecast traffic flow and congestion levels, enabling proactive traffic management and improved urban planning. Current research heavily utilizes graph convolutional networks (GCNs) and other deep learning architectures, often incorporating multimodal data sources like sensor readings, GPS trajectories, and even video imagery, to capture complex spatio-temporal dependencies. These advanced models are improving prediction accuracy and expanding to larger geographical scales, offering significant potential for optimizing transportation systems and mitigating the negative impacts of congestion. The field is also exploring more sophisticated methods for handling event-based predictions, such as congestion onset and duration.

Papers

August 2, 2024

IBB Traffic Graph Data: Benchmarking and Road Traffic Prediction Model
Eren Olug, Kiymet Kaya, Resul Tugay, Sule Gunduz Oguducu
Benchmark Platform Traffic Prediction Traffic Data Traffic Congestion Prediction

January 16, 2024

MA2GCN: Multi Adjacency relationship Attention Graph Convolutional Networks for Traffic Prediction using Trajectory data
Zhengke Sun, Yuliang Ma
Graph Convolutional Network Trajectory Data GPS Trajectory Future Traffic Vehicle Trajectory Data Traffic Congestion Prediction

November 15, 2023

Spatio-Temporal Graph Neural Point Process for Traffic Congestion Event Prediction
Guangyin Jin, Lingbo Liu, Fuxian Li, Jincai Huang
Traffic Prediction Temporal Graph Neural Network Neural Point Process Traffic Congestion Prediction

September 16, 2022

Traffic Congestion Prediction using Deep Convolutional Neural Networks: A Color-coding Approach
Mirza Fuad Adnan, Nadim Ahmed, Imrez Ishraque, Md. Sifath Al Amin, Md. Sumit Hasan
Deep Convolutional Neural Network Traffic Video Traffic Congestion Prediction Color Coding

August 23, 2022

Large-Scale Traffic Congestion Prediction based on Multimodal Fusion and Representation Mapping
Bodong Zhou, Jiahui Liu, Songyi Cui, Yaping Zhao
Convolutional Neural Network Multimodal Fusion Map Representation Grid Congestion Large Scale Real World Traffic Congestion Prediction Traffic Congestion Propagation

June 22, 2022

Traffic Congestion Prediction Using Machine Learning Techniques
Rafed Muhammad Yasir, Dr. Naushin Nower, Dr. Mohammad Shoyaib
Machine Learning Predictive Model Traffic Data Weather Data Grid Congestion Traffic Congestion Traffic Congestion Prediction

Traffic Congestion Prediction

Papers

IBB Traffic Graph Data: Benchmarking and Road Traffic Prediction Model

MA2GCN: Multi Adjacency relationship Attention Graph Convolutional Networks for Traffic Prediction using Trajectory data

Spatio-Temporal Graph Neural Point Process for Traffic Congestion Event Prediction

Traffic Congestion Prediction using Deep Convolutional Neural Networks: A Color-coding Approach

Large-Scale Traffic Congestion Prediction based on Multimodal Fusion and Representation Mapping

Traffic Congestion Prediction Using Machine Learning Techniques