Learning congestion propagation behaviors for traffic prediction

• Main Authors: Sun, Yidan, He, Peilan, Jiang, Guiyuan, Lam, Siew-Kei
• Other Authors: School of Computer Science and Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2021
• Subjects: Engineering::Computer science and engineering::Computer applications::Social and behavioral sciences; Traffic Prediction; Congestion Propagation; Deep Learning
• Online Access: https://hdl.handle.net/10356/153857
• Institution: Nanyang Technological University

Traffic prediction is a challenging task as the traffic flow is influenced by many seasonal, stochastic, and structural factors. In addition, the spatial and temporal distribution of traffic flow can induce direct and indirect congestion propagation patterns. While existing works have attempted to model s...