Pavleski, Daniel and Koltovska Nechoska, Daniela and Ivanjko, Edouard (2020) Development of TSCLab: A Tool for Evaluation of the Effectiveness of Adaptive Traffic Control Systems. In: New Technologies, Development and Application II. NT 2019. Lecture Notes in Networks and Systems. Springer, Cham. ISBN 978-3-030-18071-3
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Abstract
Adaptive Traffic Control Systems (ATCS) have been widely implemented for urban traffic control due to their capability to alleviate congestion. ATCS adjust the signal programs of signalized intersections in real time according to the measured fluctuations of traffic flow. This results in an improvement of the efficiency of traffic operations of urban networks. The process of evaluating the effectiveness of complex ATCS is challenging and presents an open problem. The most important issue is to identify whether the ATCS fulfills the goals and needs it was envisioned to achieve. For this, different measures of effectiveness with in-depth insights into the traffic situations of the controlled signalized intersection are required. In this paper, development of TSCLab (Traffic Signal Control Laboratory), a MATLAB based tool for evaluation of ATCS is presented. TSCLab can gather and visualize relevant data, which describe the performance of ATCS (green time duration, maximum green time utilization ratio, percent of arrived vehicles on green, etc.) in real time, in a VISSIM based microscopic simulation environment using different traffic scenarios. It can also process the gathered data to evaluate the effectiveness of the analyzed ATCS after simulation. To proof the capabilities of TSCLab, the effectiveness of the UTOPIA/SPOT ATCS using an isolated signalized urban intersection as the use case has been evaluated.
Item Type: | Book Section |
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Subjects: | Scientific Fields (Frascati) > Engineering and Technology > Other engineering and technologies |
Divisions: | Faculty of Technical Sciences |
Depositing User: | Prof. d-r. Daniela Koltovska Nechoska |
Date Deposited: | 15 Sep 2020 07:03 |
Last Modified: | 15 Sep 2020 07:04 |
URI: | https://eprints.uklo.edu.mk/id/eprint/5715 |
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