How to Optimise Traffic Control with Artificial Intelligence?
—Associate Professor Vilmos Simon, PhD, Head of MEDIANETS Lab Department of Networked Systems and Services, Faculty of Electric Engineering and Informatics, Budapest University of Technology and Economics
Abstract
Congestion in crowded metropolises poses significant challenges to city residents, leading to wasted time and energy, increased air pollution, and health problems. Effective management of intersections in the road network plays an important role in increasing traffic efficiency and ensuring smooth traffic flow on urban roads. ... At BME’s MEDIANETS research laboratory we are developing solutions that are able to predict the intensity of future traffic and forecast potential congestions using artificial intelligence. These predictions are used to intervene in the control of traffic lights in real time in response to the traffic conditions identified. This solution is significant and unique as no similar solution has been tested in real life situations in a large urban environment in Europe before. Our key objective is to test these solutions in real life traffic conditions too, starting in one of the world’s largest cities, Istanbul.
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Biography
Vilmos Simon received his PhD from the Budapest University of Technology and Economics (BME) in 2009. Currently he is an Associate Professor at the Department of Networked Systems and Services and Head of the Multimedia Networks and Services Laboratory. ... He has done research on mobility management, energy efficiency in mobile cellular systems and self-organized mobile networks, recently his research interests include machine learning and data analytics for smart cities and intelligent transportation management systems. He published 70+ papers in international journals and conferences, and acts as a reviewer or organizer for numerous scientific conferences.
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