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Road traffic estimation using Bluetooth sensors

Bugdol M. N., Bugdol M. D., Grzegorzek M., Mitas A. W.

Zeszyty Naukowe. Transport / Politechnika Śląska

2017

z. 96

15--25

The Bluetooth standard is a low-cost, very popular communication protocol offering a wide range of applications in many fields. In this paper, a novel system for road traffic estimation using Bluetooth sensors has been presented. The system consists of three main modules: filtration, statistical analysis of historical, and traffic estimation and prediction. The filtration module is responsible for the classification of road users and detecting measurements that should be removed. Traffic estimation has been performed on the basis of the data collected by Bluetooth measuring devices and information on external conditions (e.g., temperature), all of which have been gathered in the city of Bielsko-Biala (Poland). The obtained results are very promising. The smallest average relative error between the number of cars estimated by the model and the actual traffic was less than 10%.

New approach to traffic density estimation based on indoor and outdoor scenes from CCTV

Chmielewska A., Parzych M., Marciniak T., Dąbrowski A.

Foundations of Computing and Decision Sciences

2015

Vol. 40, No. 2

119--132

In this paper we present an algorithm for precise estimation of moving objects density (typically people and vehicles) in indoor and outdoor scenes. Automatic generation of the so-called density maps is based on video sequences acquired by surveillance systems. Our approach offers two types of solutions. The first one increments the accumulation table when a moving object is detected in a location of interest, delivering a density map of the presence of moving objects. The second algorithm increments the accumulation table only in cases of detecting a new moving object, resulting in a density map of the count of moving objects. The proposed algorithms were tested with the use of PETS 2009 database and with our own database of long-term video recordings. Finally, results of the density maps visualization and determination of the “busy hours” are presented.