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FUJDIAK, R. MAŠEK, P. MLÝNEK, P. MIŠUREC, J. MUTHANNA, A.
Original Title
Advanced Optimization Method for Improving the Urban Traffic Management
Type
conference paper
Language
English
Original Abstract
The Smart City as a concept of future cities anticipates the smart and efficient traffic management. Current situation of traffic management did not offer a sufficient solution and it is not wise to use the current technology to improve the traffic situation on the city roads. This paper deals with advanced methods for optimization, the genetic algorithms, for using in urban traffic management. Implementation of genetic algorithm and also implementation of classical static solution were provided. We try to prove the advantages of modern optimization methods, which could bring more fluent traffic to the cities and solve the current challenges as i.e. high emissions, big delay, higher probability of accidents. The paper provides comparison measurements of static and dynamic solution in discrete time, discussion of the possible implementation in praxis and evaluation of the advantages and disadvantages for both methods.
Keywords
Traffic Management, Genetic Algorithms, Optimalization methods, Smart cities
Authors
FUJDIAK, R.; MAŠEK, P.; MLÝNEK, P.; MIŠUREC, J.; MUTHANNA, A.
Released
22. 4. 2016
Location
St. Petersburg
ISBN
978-952-68397-3-8
Book
Proceedings of the 18th FRUCT & ISPIT Conference, 18-22 April 2016, Technopark of ITMO University, Saint-Petersburg, Russia. FRUCT Oy, Finland.
Pages from
48
Pages to
53
Pages count
6
URL
https://ieeexplore.ieee.org/document/7561507
BibTex
@inproceedings{BUT124124, author="Radek {Fujdiak} and Pavel {Mašek} and Petr {Mlýnek} and Jiří {Mišurec} and Ammar {Muthanna}", title="Advanced Optimization Method for Improving the Urban Traffic Management", booktitle="Proceedings of the 18th FRUCT & ISPIT Conference, 18-22 April 2016, Technopark of ITMO University, Saint-Petersburg, Russia. FRUCT Oy, Finland.", year="2016", pages="48--53", address="St. Petersburg", doi="10.1109/FRUCT-ISPIT.2016.7561507", isbn="978-952-68397-3-8", url="https://ieeexplore.ieee.org/document/7561507" }