Nature

An efficient intelligent transportation system for traffic flow prediction using meta-temporal hyperbolic quantum graph neural networks

Considering, growing quantity of automobiles on the road, modern transportation schemes face significant challenges such as gridlock, frequent accidents, thenconservational deterioration. When taking ...
Nature

Intelligent traffic congestion forecasting using BiLSTM and adaptive secretary bird optimizer for sustainable urban transportation

Traffic congestion forecasting is one of the major elements of the Intelligent Transportation Systems (ITS). Traffic congestion in urban road networks significantly influences sustainability by ...
EurekAlert!

A new era for green and intelligent transportation: LoRa meets distributed machine learning

In a world where urban traffic congestion and environmental concerns are escalating, innovative solutions are crucial for creating sustainable and efficient transportation systems. A groundbreaking ...
EurekAlert!

Are state-of-the-art deep learning traffic prediction models truly effective?

All of the baseline models achieve excellent performance in predicting high speed while performing extremely poorly in predicting lower ones. Specifically, even if the prediction horizon is 60 mins, a ...