PhD defense Matej Cebecauer on 9 December 2021
Congratulations to Matej Cebecauer on the successful defense of his PhD-thesis on Enhancing Short-Term Traffic Prediction for Large-Scale Transport Networks by Spatio-Temporal Clustering
Time: Thu 2021-12-09 13.00
Location: F3, Lindstedtsvägen 26, Stockholm
Video link: https://kth-se.zoom.us/j/66844011086
Language: English
Subject area: Transport Science, Transport Systems
Doctoral student: Matej Cebecauer , Transportplanering, Urban mobility group
Opponent: Professor Francisco Camara Pereira, DTU Technical University of Denmark
Supervisor: Docent Erik Jenelius, Centrum för transportstudier, CTS, Transportplanering; Dr. Wilco Burghout, Transportplanering
Enhancing Short-Term Traffic Prediction for Large-Scale Transport Networks by Spatio-Temporal Clustering
Congestion in large cities is responsible for extra travel time, noise, air pollution, CO2 emissions, and more. Transport is one of the main recognized contributors to global warming and climate change, which is getting increasing attention from authorities and societies around the world. Better utilization of existing resources by Intelligent Transport Systems (ITS) and digital technologies are recognized by the European Commission as technologies with enormous potential to lower the negative impacts associated with high traffic volumes in urban areas.
The main focus of this work is on short-term traffic prediction, which is an essential tool in ITS. In combination with providing information, it enables proactive decisions to decrease severity of congestion that occurs regularly or is caused by incidents. The main contribution of this work is to develop a methodological framework and prove its enhancing effects on short-term prediction in the context of large-scale transport networks. It is expected to contribute to more robust and accurate predictions of ITS in traffic management centers.
