Context-aware graph convolutional network for dynamic origin-destination prediction

• Main Authors: NATHANIEL, Juan, ZHENG, Baihua
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Graph Convolutional Network (GCN); Markov Chain; public transportation; OD prediction; explainable AI (XAI); Databases and Information Systems; Theory and Algorithms; Transportation
• Online Access: https://ink.library.smu.edu.sg/sis_research/6922; https://ink.library.smu.edu.sg/context/sis_research/article/7925/viewcontent/Paper__1_.pdf
• Institution: Singapore Management University

A robust Origin-Destination (OD) prediction is key to urban mobility. A good forecasting model can reduce operational risks and improve service availability, among many other upsides. Here, we examine the use of Graph Convolutional Net-work (GCN) and its hybrid Markov-Chain (GCN-MC) variant to perfo...