témavezető: Tettamanti Tamás
helyszín (magyar oldal): Dept. of Control for Transportation and Vehicle Systems helyszín rövidítés: DCTVS
A kutatási téma leírása:
a) Background:
Urban traffic congestion has become a critical problem that not only affects the people’s daily lives, but also restricts the stable development of society and economy, it also caused an increase in the idle time of vehicles, which increased the amount of pollutants discharged by vehicle per unit of mileage. Estimation of traffic flow with reasonable accuracy is essential for successful implementation of ITS (Intelligent Transportation Systems) based solutions.
b) Goal of research:
Simulation plays a fundamental role in solving road traffic problem such as urban traffic congestion. An accurate simulation is able to provide effective estimation of a given traffic network based on the mixed use of prior real-world traffic measurements and proper simulation settings. With developed traffic flow estimation model, traffic situation can be predicted before congestion occurs, then traffic manager can mitigate or avoid congestion through the intelligent control system.
c) Main tasks of research:
• State-of-the-art literature research.
• Urban road traffic modeling and simulation.
• Application of artificial intelligence for traffic estimation and control.
• Test, validation and calibration of the developed models and control algorithms via simulation.
e) Minimum expected scientific results:
• 3 papers in international SCI indexed journals (at least 1 with impact factor)
• 3 articles in international conference papers
f) Bibliography:
• Tettamanti, T., Milacski, Z. Ádám, Lőrincz, A. and Varga, I. (2015) “Iterative Calibration Method for Microscopic Road Traffic Simulators”, Periodica Polytechnica Transportation Engineering, 43(2), pp. 87-91. doi: https://doi.org/10.3311/PPtr.7685
• Tettamanti, T., Csikós, A., Varga, I. and Eleőd, A. (2015) “Iterative Calibration of VISSIM Simulator Based on Genetic Algorithm”, Acta Technica Jaurinensis, 8(2), pp. pp. 145-152. doi: 10.14513/actatechjaur.v8.n2.365.
• Cunha A.L., Bessa J.E., Setti J.R. (2009) Genetic Algorithm for the Calibration of Vehicle Performance Models of Microscopic Traffic Simulators. In: Lopes L.S., Lau N., Mariano P., Rocha L.M. (eds) Progress in Artificial Intelligence. EPIA 2009. Lecture Notes in Computer Science, vol 5816. Springer, Berlin, Heidelberg.
előírt nyelvtudás: English: proficient user ajánlott nyelvtudás (magyar oldal): Proficient user további elvárások: Advanced skills of informatics: basic programming, Matlab
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