Publication detail

Estimation of traffic density map using evolutionary algorithm

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

Original Title

Estimation of traffic density map using evolutionary algorithm

Type

conference paper

Language

English

Original Abstract

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.

Keywords

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

Authors

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

RIV year

2012

Released

17. 9. 2012

Publisher

IEEE Intelligent Transportation Systems Society

Location

Anchorage

ISBN

978-1-4673-3062-6

Book

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

Pages from

632

Pages to

637

Pages count

6

URL

https://www.fit.vut.cz/research/publication/9899/

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/"
}