Publication Details
Estimation of missing values in traffic density maps
Korček Pavol, Ing., Ph.D. (DCSY)
Fučík Otto, doc. Dr. Ing. (DCSY)
Beszédeš Marián
Sekanina Lukáš, prof. Ing., Ph.D. (DCSY)
Optimization and Control: Theory and Modeling,Statistical Modeling, Data Mining
and Analysis
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.
@inproceedings{BUT91286,
author="Jiří {Petrlík} and Pavol {Korček} and Otto {Fučík} and Marián {Beszédeš} and Lukáš {Sekanina}",
title="Estimation of missing values in traffic density maps",
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/"
}