A survey on modern deep neural network for traffic prediction: Trends, methods and challenges

• Main Authors: TEDJOPUMOMO, David Alexander, BAO, Zhifeng, ZHENG, Baihua, CHOUDHURY, Farhana Murtaza, QIN, Kai
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Deep Neural Network; Deep Learning; Traffic Flow Prediction; Traffic Prediction; Road Network; Databases and Information Systems; Numerical Analysis and Scientific Computing; Transportation
• Online Access: https://ink.library.smu.edu.sg/sis_research/5995; https://ink.library.smu.edu.sg/context/sis_research/article/6998/viewcontent/Trajectory_Survey_TKDE.pdf
• Institution: Singapore Management University

In this modern era, traffic congestion has become a major source of negative economic and environmental impact for urban areas worldwide. One of the most efficient ways to mitigate traffic congestion is through future traffic prediction. The field of traffic prediction has evolved greatly ever since...