PPTNet forecasts highway density and speed using FFT-selected periodic patterns, 2D Inception convolutions, and a Transformer decoder, then converts forecasts into congestion probabilities with a Mamdani fuzzy system.
Detection of road traffic participants using cost-effective arrayed ultrasonic sensors in low-speed traffic situations,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
PPTNet: A Hybrid Periodic Pattern-Transformer Architecture for Traffic Flow Prediction and Congestion Identification
PPTNet forecasts highway density and speed using FFT-selected periodic patterns, 2D Inception convolutions, and a Transformer decoder, then converts forecasts into congestion probabilities with a Mamdani fuzzy system.