Tag: intelligent transportation systems

Researchers at Linyi University have combined wavelet decomposition with denoising diffusion models to forecast urban traffic flow more accurately across ...

A fine-tuned three-billion-parameter vision-language model learned to halt all traffic at simulated intersections when pedestrians were in danger, cutting their ...

A new cross-domain handover framework for vehicular networks combines one-time anonymous credentials with graph-attention and federated anomaly detection, achieving strong ...

Researchers in India have developed TDE-RYOLO, a deep learning framework that combines image dehazing, a modified YOLOv9 detector, and Poisson-based ...

Researchers have developed LATM, a lightweight trust-scoring framework that evaluates V2X messages using six plausibility parameters and a 0.64 threshold ...

Researchers in Italy have built a Granger causality-guided multi-graph transformer that sharply improves traffic flow forecasting while learning interpretable directional ...

A lightweight hybrid framework combining randomized convolutional feature extraction with extreme learning machines classifies vehicles in fog, rain, and drone ...

Every morning, millions of people around the world descend into subway stations, tap their fare cards, and trust that the ...

Traffic congestion may soon become less a problem of reacting to stalled roads and more a problem of seeing the ...

In the rapidly evolving domain of intelligent transportation systems, the ability to accurately interpret complex traffic scenes despite unpredictable, adverse ...