Nature

Research on traffic flow prediction of progressive graph convolutional networks based on spatio-temporal self-attention mechanism

Traffic flow forecasting is a cornerstone of Intelligent Transportation Systems (ITS), aiming to infer future traffic states from historical observations to support congestion mitigation, route ...
Nature

A multi-modal attention neural network for traffic flow prediction by capturing long-short term sequence correlation

Accurate traffic flow prediction information can help traffic managers and drivers make more rational decisions and choices. To make an effective and accurate traffic flow prediction, we need to ...
EurekAlert!

From global open multi-source data to network-wide traffic flow: A large-scale case study across multiple cities

A large-scale case study across 15 cities in Europe and North America is conducted. The results demonstrate stable and satisfactory estimation accuracy across these cities, which suggests that the ...
The Drive

Red Lights Are Costing Us Billions, But Connected Car Data Offers a Solution

Add The Drive (opens in a new tab) More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results Most ...
Futurism

Uber Releases a Staggering 2 Billion Trips-Worth of Traffic Data

Add Futurism (opens in a new tab) More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Years ...