Traffic Queue Length and Pressure Estimation for Road Networks with Geometric Deep Learning Algorithms

Due to urbanization and the increase of individual mobility, in most metropolitan areas around the world congestion and inefficient traffic management occur. Highly necessary intelligent traffic control systems, which are able to reduce congestion, rely on measurements of traffic situations in urban...

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Veröffentlicht in:	arXiv.org 2019-05
1. Verfasser:	Ehlers, Simon F G
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Computer simulation Control tasks Deep learning Highways Intersections Lane changing Machine learning Metropolitan areas Network reliability Queues Queuing theory Roads Sensors Shock waves Spatial data Stability Topology Traffic congestion Traffic control Traffic flow Traffic management Urbanization
Online-Zugang:	Volltext
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