Traffic Datasets

Traffic datasets are crucial for developing and evaluating intelligent transportation systems, aiming to improve traffic prediction, management, and safety. Current research focuses on addressing the spatio-temporal heterogeneity and incompleteness of traffic data using advanced deep learning models, such as graph neural networks, transformers, and recurrent neural networks, often incorporating attention mechanisms and other techniques to enhance accuracy and efficiency. These advancements are significant for improving urban planning, optimizing resource allocation, and enabling more effective real-time traffic control and autonomous driving systems. The development and sharing of large, high-quality, and diverse traffic datasets, including those incorporating event-based data and 3D LiDAR information, are also key areas of ongoing work.

Papers

March 29, 2024

eTraM: Event-based Traffic Monitoring Dataset
Aayush Atul Verma, Bharatesh Chakravarthi, Arpitsinh Vaghela, Hua Wei, Yezhou Yang
Event Camera Traffic Datasets Traffic Monitoring Human Presence Detection

March 5, 2024

TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts
Hyunwook Lee, Sungahn Ko
Spatio Temporal Mixture Component Expert Knowledge Temporal Dependency Temporal Attention Traffic Datasets Traffic Pattern Accurate Traffic Forecasting

February 5, 2024

Efficient and Interpretable Traffic Destination Prediction using Explainable Boosting Machines
Yasin Yousif, Jörg Müller
Autonomous Driving High Efficiency Traffic Prediction Traffic Datasets Explainable Boosting Machine Argoverse Motion Forecasting

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 24, 2024

An Enhanced Analysis of Traffic Intelligence in Smart Cities Using Sustainable Deep Radial Function
Ayad Ghany Ismaeel, S. J. Jereesha Mary, C. Anitha, Jaganathan Logeshwaran, Sarmad Nozad Mahmood, Sameer Alani, Akram H. Shather
Smart City Radial Basis Function Traffic Datasets Improved Analysis Urban Traffic Management Radial Function Traffic Intelligence

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 15, 2024

CarSpeedNet: A Deep Neural Network-based Car Speed Estimation from Smartphone Accelerometer
Barak Or
Deeper Network Traffic Datasets Accelerometer Data Vehicle Speed

January 5, 2024

Predicting Traffic Flow with Federated Learning and Graph Neural with Asynchronous Computations Network
Muhammad Yaqub, Shahzad Ahmad, Malik Abdul Manan, Imran Shabir Chuhan
Graph Neural Traffic Datasets Traffic Flow Spatial Temporal Graph Federated Graph Neural Network

December 11, 2023

Regional Correlation Aided Mobile Traffic Prediction with Spatiotemporal Deep Learning
JeongJun Park, Lusungu J. Mwasinga, Huigyu Yang, Syed M. Raza, Duc-Tai Le, Moonseong Kim, Min Young Chung, Hyunseung Choo
Traffic Prediction Traffic Datasets Spatiotemporal Deep Learning

December 8, 2023

Synthesizing Traffic Datasets using Graph Neural Networks
Daniel Rodriguez-Criado, Maria Chli, Luis J. Manso, George Vogiatzis
Graph Neural Network Conditional Generative Adversarial Network Traffic Scenario Traffic Simulation Traffic Datasets

November 19, 2023

SOccDPT: Semi-Supervised 3D Semantic Occupancy from Dense Prediction Transformers trained under memory constraints
Aditya Nalgunda Ganesh
Semantic Segmentation Traffic Datasets Memory Constraint Semantic Occupancy 3D Semantic Occupancy Dense Prediction Transformer

November 6, 2023

MultiSPANS: A Multi-range Spatial-Temporal Transformer Network for Traffic Forecast via Structural Entropy Optimization
Dongcheng Zou, Senzhang Wang, Xuefeng Li, Hao Peng, Yuandong Wang, Chunyang Liu, Kehua Sheng, Bo Zhang
Traffic Prediction Traffic Forecasting Temporal Transformer Traffic Datasets Attention Computation Spatiotemporal Pattern Entropy Optimization

October 31, 2023

October 2, 2023

SWMLP: Shared Weight Multilayer Perceptron for Car Trajectory Speed Prediction using Road Topographical Features
Sarah Almeida Carneiro, Giovanni Chierchia, Jean Charléty, Aurélie Chataignon, Laurent Najman
Traffic Data Traffic Datasets Vehicle Trajectory Prediction Traffic Pattern Speed Prediction

August 29, 2023

A Comparative Study of Loss Functions: Traffic Predictions in Regular and Congestion Scenarios
Yangxinyu Xie, Tanwi Mallick
Loss Function Comparative Study Traffic Prediction Traffic Forecasting Traffic Datasets Traffic Speed Traffic Congestion Congestion Prediction

August 17, 2023

Cross-city Few-Shot Traffic Forecasting via Traffic Pattern Bank
Zhanyu Liu, Guanjie Zheng, Yanwei Yu
Traffic Forecasting Traffic Data Traffic Datasets Cross City Cross City Few Shot

August 11, 2023

Uncertainty Quantification for Image-based Traffic Prediction across Cities
Alexander Timans, Nina Wiedemann, Nishant Kumar, Ye Hong, Martin Raubal
Uncertainty Quantification Urban Environment Traffic Prediction Traffic Forecasting Traffic Datasets Traffic Pattern Spatiotemporal Traffic

June 12, 2023

Dynamic Causal Graph Convolutional Network for Traffic Prediction
Junpeng Lin, Ziyue Li, Zhishuai Li, Lei Bai, Rui Zhao, Chen Zhang
Temporal Dependency Traffic Prediction Traffic Datasets Spatiotemporal Correlation Traffic Congestion Propagation

May 31, 2023

Quality In / Quality Out: Assessing Data quality in an Anomaly Detection Benchmark
José Camacho, Katarzyna Wasielewska, Marta Fuentes-García, Rafael Rodríguez-Gómez
Anomaly Detection Data Quality Traffic Datasets Network Optimization Anomaly Detection Benchmark Driving Network

Traffic Datasets

Papers

eTraM: Event-based Traffic Monitoring Dataset

TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts

Efficient and Interpretable Traffic Destination Prediction using Explainable Boosting Machines

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

An Enhanced Analysis of Traffic Intelligence in Smart Cities Using Sustainable Deep Radial Function

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

CarSpeedNet: A Deep Neural Network-based Car Speed Estimation from Smartphone Accelerometer

Predicting Traffic Flow with Federated Learning and Graph Neural with Asynchronous Computations Network

Regional Correlation Aided Mobile Traffic Prediction with Spatiotemporal Deep Learning

Synthesizing Traffic Datasets using Graph Neural Networks

SOccDPT: Semi-Supervised 3D Semantic Occupancy from Dense Prediction Transformers trained under memory constraints

MultiSPANS: A Multi-range Spatial-Temporal Transformer Network for Traffic Forecast via Structural Entropy Optimization

Distil the informative essence of loop detector data set: Is network-level traffic forecasting hungry for more data?

Decision-Making for Autonomous Vehicles with Interaction-Aware Behavioral Prediction and Social-Attention Neural Network

SWMLP: Shared Weight Multilayer Perceptron for Car Trajectory Speed Prediction using Road Topographical Features

A Comparative Study of Loss Functions: Traffic Predictions in Regular and Congestion Scenarios

Cross-city Few-Shot Traffic Forecasting via Traffic Pattern Bank

Uncertainty Quantification for Image-based Traffic Prediction across Cities

Dynamic Causal Graph Convolutional Network for Traffic Prediction

Quality In / Quality Out: Assessing Data quality in an Anomaly Detection Benchmark