Traffic Forecasting - Groups

METR-LA Traffic Forecasting Dataset

The METR-LA traffic forecasting dataset contains time series data from 16 sensors.

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Traffic4cast challenge 2019

Traffic4cast challenge 2019 dataset contains 100 billion probe points covering 3 cities (Berlin, Istanbul and Moscow) throughout a year.

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METR-LA, PEMS-BAY, AJILE12

The dataset used for traffic forecasting and brain network analysis.

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HUTFormer: Hierarchical U-Net Transformer for Long-Term Traffic Forecasting

Traffic forecasting, which aims to predict traffic conditions based on historical observations, has been an enduring research topic and is widely recognized as an essential...

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Graph-Based U-Net

The Graph-Based U-Net model is used for traffic prediction.

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SWIN-Transformer

The SWIN-Transformer model is used for traffic map prediction.

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Traﬃc4cast 2021

The Traﬃc4cast 2021 competition provides a unique data set derived from industrial scale trajectories of raw GPS position ﬁxes, with latitude, longitude, time stamp, as well as...

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Seattle-Loop

The Seattle-Loop dataset is a highway speed dataset collected from 323 loop detectors in the Greater Seattle Area.

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Urban-core

The Urban-core dataset is an urban speed dataset containing data collected from DTG (Digital Tacho Graph) on Seoul Taxis.

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Progressive Graph Convolutional Networks for Spatial-Temporal Traffic Forecas...

The complex spatial-temporal correlations in traffic data make the traffic forecasting problem challenging. The proposed model captures the time-varying spatial correlations by...

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Trafﬁc4cast 2021 - Temporal and Spatial Few-Shot Transfer Learning in Trafﬁc ...

The dataset provided for the two tasks consists of 10 different cities from around the world over the course of 2 years. The cities have been split into 3 categories: Core...

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Traffic dataset

The Traffic dataset records the occupation rate of highway systems in California, USA.

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PeMS-BAY

The trafﬁc forecasting problem can be categorized into three types, namely, based on the length of prediction, i.e., short-term (less than 30 min) and long term(30 ∼ 60 min).

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PeMSD7

Trafﬁc speed prediction is a crucial task for many key purposes in intelligent trafﬁc systems and urban planning.

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3D Temporal Graph Convolutional Networks (3D-TGCN)

Spatio-temporal prediction plays an important role in many application areas especially in trafﬁc domain. However, due to complicated spatio-temporal dependency and high...

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Zhuzhou and Baoding datasets

Zhuzhou and Baoding are two real-world datasets used in this paper for irregular traffic forecasting.

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Traffic

The dataset used in this paper for stochastic time series forecasting.

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METR-LA dataset

The METR-LA dataset contains speed profiles, given in miles per hour (mph), of 207 sensor locations collected from the loop detector on the highways of Los Angeles County.

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PEMS-BAY Dataset

The dataset from the California Transportation Agency contains average trafﬁc speed.

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Ring-BJ

Ring-BJ is a real-world traffic network dataset generated by ourselves.

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26 datasets found