Short-term traffic forecasting: An adaptive ST-KNN model that considers spatial heterogeneity

Accurate and robust short-term traffic forecasting is a critical issue in intelligent transportation systems and real-time traffic-related applications. Existing short-term traffic forecasting approaches adopt fixed model structures and assume traffic correlations between adjacent road segments with...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Computers, environment and urban systems environment and urban systems, 2018-09, Vol.71, p.186-198
Hauptverfasser:	Cheng, Shifen, Lu, Feng, Peng, Peng, Wu, Sheng
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive spatiotemporal k-nearest neighbor model Autocorrelation functions Dependence Driving conditions Forecasting Heterogeneity Highways Intelligent transportation systems Intelligent vehicle highway systems K-nearest neighbors algorithm Model accuracy Parameters Prediction models Short-term traffic forecasting Spatial analysis Spatial heterogeneity Traffic Traffic congestion Traffic flow Traffic models Traffic patterns Weight Windows (intervals)
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!