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Development of TSCLab: A Tool for Evaluation of the Effectiveness of Adaptive Traffic Control Systems

  • Daniel Pavleski
  • Daniela Koltovska Nechoska
  • Edouard IvanjkoEmail author
Conference paper
  • 733 Downloads
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 76)

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.

Keywords

Intelligent Transport Systems Adaptive Traffic Control System Isolated signalized urban intersection Evaluation of effectiveness 

Notes

Acknowledgement

The authors would like to thank the companies PTV Group and SWARCO MIZAR S.r.l., the Traffic management and control center of the City of Skopje, and the Faculty of Transport and Traffic Sciences, University of Zagreb for supporting the work published in this paper.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Daniel Pavleski
    • 1
  • Daniela Koltovska Nechoska
    • 2
  • Edouard Ivanjko
    • 3
    Email author
  1. 1.Traffic Department of the City of SkopjeSkopjeRepublic of Macedonia
  2. 2.Faculty of Technical SciencesSt. Kliment Ohridski UniversityBitolaRepublic of Macedonia
  3. 3.Department of Intelligent Transportation Systems, Faculty of Transport and Traffic SciencesUniversity of ZagrebZagrebRepublic of Croatia

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