Publications (4)0 Total impact
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Bartłomiej Płaczek
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ABSTRACT: Microscopic traffic models have recently gained considerable importance as a
mean of optimising traffic control strategies. Computationally efficient and
sufficiently accurate microscopic traffic models have been developed based on
the cellular automata theory. However, the real-time application of the
available cellular automata models in traffic control systems is a difficult
task due to their discrete and stochastic nature. This paper introduces a novel
method of traffic streams modelling, which combines cellular automata and fuzzy
calculus. The introduced fuzzy cellular traffic model eliminates main drawbacks
of the cellular automata approach i.e. necessity of multiple Monte Carlo
simulations and calibration issues. Experimental results show that the
evolution of a simulated traffic stream in the proposed fuzzy cellular model is
consistent with that observed for stochastic cellular automata. The comparison
of both methods confirms that the computational cost of traffic simulation is
considerably lower for the proposed model. The model is suitable for real-time
applications in traffic control systems.
12/2011;
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Bartłomiej Płaczek
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ABSTRACT: This paper introduces a fuzzy cellular model of road traffic that was
intended for on-line applications in traffic control. The presented model uses
fuzzy sets theory to deal with uncertainty of both input data and simulation
results. Vehicles are modelled individually, thus various classes of them can
be taken into consideration. In the proposed approach, all parameters of
vehicles are described by means of fuzzy numbers. The model was implemented in
a simulation of vehicles queue discharge process. Changes of the queue length
were analysed in this experiment and compared to the results of NaSch cellular
automata model.
12/2011;
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Bartłomiej Płaczek
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ABSTRACT: In this paper a method is proposed for performance evaluation of road traffic
control systems. The method is designed to be implemented in an on-line
simulation environment, which enables optimisation of adaptive traffic control
strategies. Performance measures are computed using a fuzzy cellular traffic
model, formulated as a hybrid system combining cellular automata and fuzzy
calculus. Experimental results show that the introduced method allows the
performance to be evaluated using imprecise traffic measurements. Moreover, the
fuzzy definitions of performance measures are convenient for uncertainty
determination in traffic control decisions.
12/2011;
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Bartłomiej Płaczek
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ABSTRACT: In this paper a vision-based vehicles recognition method is presented.
Proposed method uses fuzzy description of image segments for automatic
recognition of vehicles recorded in image data. The description takes into
account selected geometrical properties and shape coefficients determined for
segments of reference image (vehicle model). The proposed method was
implemented using reasoning system with fuzzy rules. A vehicles recognition
algorithm was developed based on the fuzzy rules describing shape and
arrangement of the image segments that correspond to visible parts of a
vehicle. An extension of the algorithm with set of fuzzy rules defined for
different reference images (and various vehicle shapes) enables vehicles
classification in traffic scenes. The devised method is suitable for
application in video sensors for road traffic control and surveillance systems.
12/2011;
