Detail publikace

Estimation of traffic density map using evolutionary algorithm

PETRLÍK, J. KORČEK, P. FUČÍK, O. BESZÉDEŠ, M. SEKANINA, L.

Originální název

Estimation of traffic density map using evolutionary algorithm

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The traffic density map (TDM) represents the density of road network traffic as the number of vehicles per a specific time interval. TDMs are used by traffic experts as a base documentation for planning a new infrastructure (long-term) or by drivers for showing a current trafic status (short-term). We propose two methods for estimation of missing density values in TDMs. In the first method, the problem is formulated relatively strictly in terms of quadratic programming (QP) and a QP solver is utilized to find a solution. The second, more general method is based on a multiobjective genetic algorithm which allows us to find a reasonable compromise among several objectives that a traffic expert may formulate. These two methods can work automatically or they can be used by a traffic expert for an iterative density estimation. Results of experimental evaluation based on real and randomly generated data are presented.

Klíčová slova

Optimization and Control: Theory and Modeling,Statistical Modeling, Data Mining and Analysis

Autoři

PETRLÍK, J.; KORČEK, P.; FUČÍK, O.; BESZÉDEŠ, M.; SEKANINA, L.

Rok RIV

2012

Vydáno

17. 9. 2012

Nakladatel

IEEE Intelligent Transportation Systems Society

Místo

Anchorage

ISBN

978-1-4673-3062-6

Kniha

Proceedings of the 15th International IEEE Conference on Intelligent Transportation Systems

Strany od

632

Strany do

637

Strany počet

6

URL

BibTex

@inproceedings{BUT91286,
  author="Jiří {Petrlík} and Pavol {Korček} and Otto {Fučík} and Marián {Beszédeš} and Lukáš {Sekanina}",
  title="Estimation of traffic density map using evolutionary algorithm",
  booktitle="Proceedings of the 15th International IEEE Conference on Intelligent Transportation Systems",
  year="2012",
  pages="632--637",
  publisher="IEEE Intelligent Transportation Systems Society",
  address="Anchorage",
  doi="10.1109/ITSC.2012.6338757",
  isbn="978-1-4673-3062-6",
  url="https://www.fit.vut.cz/research/publication/9899/"
}