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Traffic Prediction

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하위 태스크: 1
평가표: 33
보존된 평가 기록: 192

Traffic Prediction is a task that involves forecasting traffic conditions, such as the volume of vehicles and travel time, in a specific area or along a particular road. This task is important for optimizing transportation systems and reducing traffic congestion.

<span style="color:grey; opacity: 0.6">( Image credit: BaiduTraffic )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/shuhaolii/tits24lanelevel-traffic-benchmark

공식 코드

Unifying Lane-Level Traffic Prediction from a Graph Structural Perspective: Benchmark and Baseline

https://github.com/skandium/t4c22

공식 코드

Large scale traffic forecasting with gradient boosting, Traffic4cast 2022 challenge

https://github.com/soc-ucsd/deep-lcc

공식 코드

Implementation and Experimental Validation of Data-Driven Predictive Control for Dissipating Stop-and-Go Waves in Mixed Traffic

https://github.com/sqlcow/TITAN

공식 코드

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

https://github.com/square-coder/STGODE

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Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting

https://github.com/sshleifer/Graph-WaveNet

공식 코드

Incrementally Improving Graph WaveNet Performance on Traffic Prediction

https://github.com/start2020/Multi-View_TRGRU

공식 코드

Completion and Augmentation based Spatiotemporal Deep Learning Approach for Short-Term Metro Origin-Destination Matrix Prediction under Limited Observable Data

https://github.com/start2020/msgc-seq2seq

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Incorporating Reachability Knowledge into a Multi-Spatial Graph Convolution Based Seq2Seq Model for Traffic Forecasting

https://github.com/starxingwang/ahstgnn

공식 코드

Adaptive Hybrid Spatial-Temporal Graph Neural Network for Cellular Traffic Prediction

https://github.com/suminhan/traffic-uagcrntf

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Enhancing Spatiotemporal Traffic Prediction through Urban Human Activity Analysis

https://github.com/tangxianfeng/STDN

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Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction

https://github.com/tongnie/awesome-llm4tr

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Exploring the Roles of Large Language Models in Reshaping Transportation Systems: A Survey, Framework, and Roadmap

https://github.com/tongnie/tensorlib

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Truncated tensor Schatten p-norm based approach for spatiotemporal traffic data imputation with complicated missing patterns

https://github.com/trainingl/stg4traffic

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STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction

https://github.com/tsinghua-fib-lab/Traffic-Benchmark

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Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution

https://github.com/tumeteor/neurips2019challenge

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Spatiotemporal Tile-based Attention-guided LSTMs for Traffic Video Prediction

https://github.com/uctb/uctb

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Exploring the Generalizability of Spatio-Temporal Traffic Prediction: Meta-Modeling and an Analytic Framework

https://github.com/victorchan314/arterial_traffic_flow_predictor

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A Graph Convolutional Network with Signal Phasing Information for Arterial Traffic Prediction

https://github.com/vperifan/federated-time-series-forecasting

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Federated Learning for 5G Base Station Traffic Forecasting

https://github.com/wengwenchao123/PM-DMNet

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Pattern-Matching Dynamic Memory Network for Dual-Mode Traffic Prediction

https://github.com/wenjiedu/awesome_imputation

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PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series

https://github.com/wenjiedu/brewpots

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PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series

https://github.com/wtl52656/imputation_benchmark

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An Experimental Evaluation of Imputation Models for Spatial-Temporal Traffic Data

https://github.com/xdzhelheim/staeformer

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STAEformer: Spatio-Temporal Adaptive Embedding Makes Vanilla Transformer SOTA for Traffic Forecasting

https://github.com/xinychen/transdim

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A Nonconvex Low-Rank Tensor Completion Model for Spatiotemporal Traffic Data Imputation

https://github.com/xumingxingsjtu/STTN

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Spatial-Temporal Transformer Networks for Traffic Flow Forecasting

https://github.com/yihongt/dastnet

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

https://github.com/ymlasu/para-atm-collection

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Air Traffic Controller Workload Level Prediction using Conformalized Dynamical Graph Learning

https://github.com/youxiaotu/MoGERNN

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MoGERNN: An Inductive Traffic Predictor for Unobserved Locations in Dynamic Sensing Networks

https://github.com/ywoelker/SUSTeR

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SUSTeR: Sparse Unstructured Spatio Temporal Reconstruction on Traffic Prediction

https://github.com/zachysun/taxi_traffic_benchmark

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

https://github.com/zbliu98/gram-ode

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Graph-based Multi-ODE Neural Networks for Spatio-Temporal Traffic Forecasting

https://github.com/zeonchen/sfmgtl

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Semantic-Fused Multi-Granularity Cross-City Traffic Prediction

https://github.com/zezhishao/d2stgnn

공식 코드

Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting

https://github.com/zezhishao/step

공식 코드

Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting

https://github.com/zezhishao/stid

공식 코드

Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting

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