Local Gaussian processes for efficient fine-grained traffic speed prediction

• Main Authors: LE, Truc Viet, OENTARYO, Richard, LIU, Siyuan, LAU, Hoong Chuin
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Gaussian process; matrix factorization; spatiotemporal clustering; traffic speed; urban computing; Artificial Intelligence and Robotics; Computer Sciences; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/3862; https://ink.library.smu.edu.sg/context/sis_research/article/4864/viewcontent/Local_Gaussian_Traffic_2017_afv.pdf
• Institution: Singapore Management University

Traffic speed is a key indicator for the efficiency of an urban transportation system. Accurate modeling of the spatiotemporally varying traffic speed thus plays a crucial role in urban planning and development. This paper addresses the problem of efficient fine-grained traffic speed prediction usin...