Traffic-Cascade: Mining and visualizing lifecycles of traffic congestion events using public bus trajectories

• Main Authors: KWEE, Agus Trisnajaya, CHIANG, Meng-Fen, PRASETYO, Philips Kokoh, LIM, Ee-peng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Data mining; Anomaly detection; Visualization; Traffic congestion; Databases and Information Systems; Transportation
• Online Access: https://ink.library.smu.edu.sg/sis_research/4260; https://ink.library.smu.edu.sg/context/sis_research/article/5263/viewcontent/Traffic_Cascade_2018_pv_oa.pdf
• Institution: Singapore Management University

As road transportation supports both economic and social activities in developed cities, it is important to maintain smooth traffic on all highways and local roads. Whenever possible, traffic congestions should be detected early and resolved quickly. While existing traffic monitoring dashboard syste...